title
Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib)

description
This Python data science course will take you from knowing nothing about Python to coding and analyzing data with Python using tools like Pandas, NumPy, and Matplotlib. 💻 Code: https://github.com/datapublishings/Course-python-data-science This is a hands-on course and you will practice everything you learn step-by-step. This course was created by Maxwell Armi. You can check out more of his data science videos on his YouTube channel here: https://www.youtube.com/c/AISciencesLearn 🎥 Learn more about Data Science with videos from freeCodeCamp's Data Science Playlist: https://www.youtube.com/playlist?list=PLWKjhJtqVAblQe2CCWqV4Zy3LY01Z8aF1 ⭐️ Course Contents ⭐️ ⌨️ (0:00:00) Introduction to the Course and Outline ⌨️ (0:03:53) The Basics of Programming ⌨️ (1:11:35) Why Python ⌨️ (1:33:09) How to Install Anaconda and Python ⌨️ (1:37:25) How to Launch a Jupyter Notebook ⌨️ (1:46:28) How to Code in the iPython Shell ⌨️ (1:53:33) Variables and Operators in Python ⌨️ (2:27:45) Booleans and Comparisons in Python ⌨️ (2:55:37) Other Useful Python Functions ⌨️ (3:20:04) Control Flow in Python ⌨️ (5:11:52) Functions in Python ⌨️ (6:41:47) Modules in Python ⌨️ (7:30:04) Strings in Python ⌨️ (8:23:57) Other Important Python Data Structures: Lists, Tuples, Sets, and Dictionaries ⌨️ (9:36:10) The NumPy Python Data Science Library ⌨️ (11:04:12) The Pandas Python Data Science Python Library ⌨️ (12:01:31) The Matplotlib Python Data Science Library ⌨️ (12:09:00) Example Project: A COVID19 Trend Analysis Data Analysis Tool Built with Python Libraries

detail
{'title': 'Python for Data Science - Course for Beginners (Learn Python, Pandas, NumPy, Matplotlib)', 'heatmap': [{'end': 20425.804, 'start': 19976.201, 'weight': 1}], 'summary': 'A comprehensive python for data science course covers python basics, functions, control flow, string handling, data structures, numpy, pandas, and visualization. it includes mastering python, algorithms, expressions, pseudocodes, ipython, variables, comparison operators, boolean data types, functions, sorting, modules, default values, string handling, data structures, and numpy array operations, emphasizing real-world applications and problem-solving with practical examples.', 'chapters': [{'end': 382.33, 'segs': [{'end': 111.631, 'src': 'embed', 'start': 83.791, 'weight': 5, 'content': [{'end': 90.918, 'text': 'Obviously, we will start from the very beginning, very, very beginning, which means we will start from how to install Python.', 'start': 83.791, 'duration': 7.127}, {'end': 96.442, 'text': 'For example, we will start from there and then we will see what are variables.', 'start': 91.098, 'duration': 5.344}, {'end': 105.288, 'text': 'I mean very, very beginning and then progressively we will be moving on and on and on to data structures, to complex structures.', 'start': 96.622, 'duration': 8.666}, {'end': 111.631, 'text': 'but that transition from zero to onwards, that transition will be very, very smooth.', 'start': 105.288, 'duration': 6.343}], 'summary': 'A tutorial on python starting from installation, covering variables, data structures, and smooth progression.', 'duration': 27.84, 'max_score': 83.791, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI83791.jpg'}, {'end': 255.37, 'src': 'embed', 'start': 222.534, 'weight': 7, 'content': [{'end': 225.215, 'text': 'We are not covering exception handling.', 'start': 222.534, 'duration': 2.681}, {'end': 231.277, 'text': "We're not doing web development or any general kind of tasks that are doable in Python.", 'start': 225.555, 'duration': 5.722}, {'end': 233.218, 'text': 'We are not focusing on those things.', 'start': 231.297, 'duration': 1.921}, {'end': 236.82, 'text': 'Everybody solves different problems every day.', 'start': 234.359, 'duration': 2.461}, {'end': 241.724, 'text': 'Some problems are easy to solve and some are difficult.', 'start': 238.863, 'duration': 2.861}, {'end': 245.246, 'text': 'And yet some are impossible to solve.', 'start': 243.045, 'duration': 2.201}, {'end': 248.447, 'text': 'They are called unsolvable problems.', 'start': 246.086, 'duration': 2.361}, {'end': 255.37, 'text': 'But think about different instances of the same problem one needs to solve again and again.', 'start': 249.927, 'duration': 5.443}], 'summary': 'This session excludes exception handling and web development, focusing on solving various daily problems.', 'duration': 32.836, 'max_score': 222.534, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI222534.jpg'}, {'end': 318.719, 'src': 'embed', 'start': 282.195, 'weight': 0, 'content': [{'end': 284.917, 'text': 'How to come up with the automated solution??', 'start': 282.195, 'duration': 2.722}, {'end': 291.28, 'text': 'To come up with a general solution that works for every instance of some problem?', 'start': 286.398, 'duration': 4.882}, {'end': 292.241, 'text': 'that is one thing.', 'start': 291.28, 'duration': 0.961}, {'end': 298.184, 'text': 'But to get that solution running on a computer is yet another thing.', 'start': 294.082, 'duration': 4.102}, {'end': 308.797, 'text': 'Problem solving deals with formalizing a general solution that works for every instance.', 'start': 300.435, 'duration': 8.362}, {'end': 318.719, 'text': 'And programming languages like Python deals with the running of that solution on a computer.', 'start': 310.057, 'duration': 8.662}], 'summary': 'Problem solving involves creating a general solution for every instance, while programming languages like python run those solutions on a computer.', 'duration': 36.524, 'max_score': 282.195, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI282195.jpg'}], 'start': 0.109, 'title': 'Python for data science beginners and data processing', 'summary': "Covers mastering python for beginners in data science, including problem solving and the importance of python. it also discusses python's power in handling large amounts of data for understanding, visualization, cleaning, and processing.", 'chapters': [{'end': 199.079, 'start': 0.109, 'title': 'Mastering python for data science beginners', 'summary': 'Focuses on mastering python for beginners in data science, covering problem solving, the importance of python for data science, and a comprehensive learning path that transitions from basic concepts to complex data structures, equipping learners with a general understanding of programming languages.', 'duration': 198.97, 'highlights': ['The course is designed for beginners with no prior programming experience, focusing on problem solving and starting with the basics of Python, including installation and variables.', 'The chapter emphasizes the importance of Python in data science and its role in solving data science problems.', 'The course covers a comprehensive learning path, from basic Python concepts to complex data structures, facilitating a smooth transition and enabling understanding of programming languages in general.']}, {'end': 382.33, 'start': 199.079, 'title': 'Python for data processing', 'summary': 'Discusses the power of python in handling large amounts of data for understanding, visualization, cleaning, and processing, while not focusing on oop, exception handling, web development, or general tasks, and emphasizes the transition from problem solving to running solutions with python.', 'duration': 183.251, 'highlights': ['Python is very powerful in handling large amounts of data for understanding, visualization, cleaning, and processing, making it an optimal choice for automating solutions for repetitive tasks.', 'The chapter emphasizes the transition from problem solving to running solutions with Python, making it easier and quicker.', 'The chapter does not cover OOP, exception handling, web development, or general tasks in Python.', 'Automating solutions for repetitive tasks, such as sorting sale records, is beneficial if the number of instances is huge.', 'Python simplifies the transition from problem solving to running solutions, showcasing its strength in data processing.']}], 'duration': 382.221, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI109.jpg', 'highlights': ['Python simplifies the transition from problem solving to running solutions, showcasing its strength in data processing.', 'The course covers a comprehensive learning path, from basic Python concepts to complex data structures, facilitating a smooth transition and enabling understanding of programming languages in general.', 'Python is very powerful in handling large amounts of data for understanding, visualization, cleaning, and processing, making it an optimal choice for automating solutions for repetitive tasks.', 'The chapter emphasizes the importance of Python in data science and its role in solving data science problems.', 'The course is designed for beginners with no prior programming experience, focusing on problem solving and starting with the basics of Python, including installation and variables.', 'Automating solutions for repetitive tasks, such as sorting sale records, is beneficial if the number of instances is huge.', 'The chapter emphasizes the transition from problem solving to running solutions with Python, making it easier and quicker.', 'The chapter does not cover OOP, exception handling, web development, or general tasks in Python.']}, {'end': 2813.86, 'segs': [{'end': 497.672, 'src': 'embed', 'start': 438.631, 'weight': 2, 'content': [{'end': 444.396, 'text': 'I mean, at the job place, there are sales records, and you have to pick the email of the customer with maximum sales.', 'start': 438.631, 'duration': 5.765}, {'end': 458.469, 'text': 'B said, oh, okay, but wait, what should I do with the email that I just picked? Then A said, oh, there is another record called priority records.', 'start': 444.957, 'duration': 13.512}, {'end': 460.53, 'text': 'Just write that email after eight hours.', 'start': 458.689, 'duration': 1.841}, {'end': 463.193, 'text': 'Just write that email in priority records.', 'start': 461.171, 'duration': 2.022}, {'end': 465.645, 'text': "And then B said, that's it.", 'start': 464.465, 'duration': 1.18}, {'end': 466.866, 'text': "That's all your job.", 'start': 466.005, 'duration': 0.861}, {'end': 473.187, 'text': "And A said, after so relaxed, A said, yes, that's my job.", 'start': 467.646, 'duration': 5.541}, {'end': 473.928, 'text': "That's all.", 'start': 473.568, 'duration': 0.36}, {'end': 483.99, 'text': 'Now think A leaves and later that day receives a call from B.', 'start': 476.588, 'duration': 7.402}, {'end': 486.551, 'text': "And B said, I don't really know what to do.", 'start': 483.99, 'duration': 2.561}, {'end': 493.173, 'text': 'Can you tell me step by step what to do? Focus on again.', 'start': 487.451, 'duration': 5.722}, {'end': 497.672, 'text': "I'm reading this particular sentence again.", 'start': 494.731, 'duration': 2.941}], 'summary': 'Job involves picking customer email with maximum sales and adding it to priority records.', 'duration': 59.041, 'max_score': 438.631, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI438631.jpg'}, {'end': 1100.71, 'src': 'embed', 'start': 1077.044, 'weight': 1, 'content': [{'end': 1086.515, 'text': 'they might have worked for a different number of hours and each employee can have a different hourly rate depending upon the capacity of the employee or the job,', 'start': 1077.044, 'duration': 9.471}, {'end': 1087.937, 'text': 'nature the employee is doing, and so on.', 'start': 1086.515, 'duration': 1.422}, {'end': 1098.749, 'text': 'So if we want to compute pay of all employees one by one, the procedure of computing pay stays the same.', 'start': 1090.783, 'duration': 7.966}, {'end': 1100.71, 'text': 'The instances, they differ.', 'start': 1099.369, 'duration': 1.341}], 'summary': 'Employees work varying hours and have different hourly rates based on capacity and job nature.', 'duration': 23.666, 'max_score': 1077.044, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI1077044.jpg'}, {'end': 2393.9, 'src': 'embed', 'start': 2362.368, 'weight': 4, 'content': [{'end': 2367.29, 'text': 'That is just our convention for this kind of problem, for this problem, just for this code.', 'start': 2362.368, 'duration': 4.922}, {'end': 2373.216, 'text': "And I'm not talking about any particular programming language yet.", 'start': 2368.21, 'duration': 5.006}, {'end': 2374.838, 'text': 'This is just a list of numbers.', 'start': 2373.516, 'duration': 1.322}, {'end': 2384.389, 'text': "And let's say we want a procedure that finds out the minimum value of any list.", 'start': 2376.56, 'duration': 7.829}, {'end': 2393.9, 'text': 'Well, first of all, why this problem has multiple instances? Well, we need to come up with a solution that works for any list.', 'start': 2385.41, 'duration': 8.49}], 'summary': 'Developing a procedure to find the minimum value of any list.', 'duration': 31.532, 'max_score': 2362.368, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI2362368.jpg'}, {'end': 2727.498, 'src': 'embed', 'start': 2701.638, 'weight': 0, 'content': [{'end': 2713.814, 'text': 'Um, so first we take a variable, We are assuming here that the list is supplied to us, the total number of elements in the list is supplied to us.', 'start': 2701.638, 'duration': 12.176}, {'end': 2720.196, 'text': 'So we first take the minimum value, which we really want to compute, the minimum value we want to compute.', 'start': 2714.515, 'duration': 5.681}, {'end': 2723.897, 'text': 'But any list can be supplied in this procedure.', 'start': 2720.896, 'duration': 3.001}, {'end': 2724.697, 'text': "so what's the procedure??", 'start': 2723.897, 'duration': 0.8}, {'end': 2727.498, 'text': 'The minimum value that we want to compute?', 'start': 2725.297, 'duration': 2.201}], 'summary': 'Procedure to compute the minimum value from a supplied list.', 'duration': 25.86, 'max_score': 2701.638, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI2701638.jpg'}], 'start': 382.33, 'title': 'Algorithm expressions and pseudocodes', 'summary': 'Discusses algorithm expressions, pseudocodes, and transitioning to programming languages, particularly python, emphasizing unambiguous step-by-step procedures and the use of pseudocode for expressing algorithms.', 'chapters': [{'end': 438.371, 'start': 382.33, 'title': 'Job delegation and misunderstanding', 'summary': 'Illustrates a conversation between a and b regarding job delegation and misunderstanding, where a instructs b to handle email of the customer with the maximum sales every eight hours, resulting in confusion for b.', 'duration': 56.041, 'highlights': ["B misunderstands A's job delegation, leading to confusion and uncertainty about the task at hand.", 'A instructs B to handle the email of the customer with the maximum sales every eight hours, emphasizing the specific task to be performed.', 'A mentions the presence of sales records from which B can obtain the required information, providing clarity on the data source for the task.']}, {'end': 869.313, 'start': 438.631, 'title': 'Communication of step-by-step solution', 'summary': 'Explains a step-by-step solution for selecting the email of the customer with the maximum sales from sales records, emphasizing the importance of clear communication and providing a general solution applicable to every instance.', 'duration': 430.682, 'highlights': ['A describes a step-by-step solution for selecting the email with maximum sales from sales records, emphasizing the importance of clear communication.', 'Emphasizing the relevance of a general solution, A communicates the importance of providing a step-by-step solution applicable to every instance.', 'A explains the transition from a step-by-step solution in plain English to a more concise and unique procedure known as pseudocode, which is a significant aspect in problem-solving.']}, {'end': 1077.044, 'start': 869.473, 'title': 'Algorithm expressions and pseudocodes', 'summary': 'Discusses the concept of algorithm expressions and pseudocodes, emphasizing the need for unambiguous step-by-step procedures, and the transition to using pseudocodes and eventually programming languages, particularly python, for expressing algorithms.', 'duration': 207.571, 'highlights': ['The chapter discusses the concept of algorithm expressions and pseudocodes, emphasizing the need for unambiguous step-by-step procedures', 'The transition to using pseudocodes and eventually programming languages, particularly Python, for expressing algorithms']}, {'end': 1621.973, 'start': 1077.044, 'title': 'Computing employee pay procedure', 'summary': 'Discusses the procedure for computing employee pay by taking into account different working hours and rates, emphasizing the use of pseudocode as a feasible way to express algorithms.', 'duration': 544.929, 'highlights': ['The procedure for computing employee pay involves taking input of hours and rate for each employee, followed by the calculation of pay using the formula: pay = hours * rate.', 'Emphasizing the importance of using expressive and concise keywords in pseudocode to describe the solution of the problem, ensuring that each statement has a unique meaning and describes the flow of the process.', 'Comparing the feasibility of using pseudocode over flowchart for expressing algorithms, highlighting that pseudocode is more feasible when the goal is to convert it into code of a programming language.']}, {'end': 2813.86, 'start': 1622.493, 'title': 'Algorithm for making tea', 'summary': 'Describes the process of making tea, including the variations in ingredients based on individual preferences, and the use of flowcharts and pseudocode to represent the procedure. it also introduces the concept of loops and highlights the transition from pseudocode to python code for problem-solving.', 'duration': 1191.367, 'highlights': ['The procedure of making tea should stay the same, while the instances, which means the different people want T in a different kind of combination, may vary.', 'Two different algorithms may just vary because of the sequence of statements, even if you have the same statements.', 'The purpose of this slide was just to make you convinced and make you comfortable with this pseudocode and flowchart.', 'We will not be talking about flowcharts any further from here on.', "We're going to actually solve a problem of finding out minimum value from a list of values sometimes called the searching problem.", 'We want to come up with a procedure that always finds out the minimum value in that list.']}], 'duration': 2431.53, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI382330.jpg', 'highlights': ['The transition to using pseudocodes and eventually programming languages, particularly Python, for expressing algorithms', 'The chapter discusses the concept of algorithm expressions and pseudocodes, emphasizing the need for unambiguous step-by-step procedures', 'Emphasizing the importance of using expressive and concise keywords in pseudocode to describe the solution of the problem, ensuring that each statement has a unique meaning and describes the flow of the process', 'A explains the transition from a step-by-step solution in plain English to a more concise and unique procedure known as pseudocode, which is a significant aspect in problem-solving', 'A describes a step-by-step solution for selecting the email with maximum sales from sales records, emphasizing the importance of clear communication', 'The procedure for computing employee pay involves taking input of hours and rate for each employee, followed by the calculation of pay using the formula: pay = hours * rate']}, {'end': 6505.715, 'segs': [{'end': 2845.903, 'src': 'embed', 'start': 2813.86, 'weight': 3, 'content': [{'end': 2819.401, 'text': 'Remember the value of n for this particular example is six and counter here is two.', 'start': 2813.86, 'duration': 5.541}, {'end': 2826.842, 'text': 'So, because counter has value two, while two is less or equal to six.', 'start': 2820.241, 'duration': 6.601}, {'end': 2835.144, 'text': 'first, check whether this condition is true or false, because if this condition is true, then you will go to the body of the loop.', 'start': 2826.842, 'duration': 8.302}, {'end': 2839.32, 'text': 'Then this whole box will execute.', 'start': 2835.664, 'duration': 3.656}, {'end': 2845.903, 'text': 'If this condition becomes false, then you will exit the loop and will go out.', 'start': 2840.221, 'duration': 5.682}], 'summary': 'Using a loop with n=6 and counter=2, execute the body if condition is true.', 'duration': 32.043, 'max_score': 2813.86, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI2813860.jpg'}, {'end': 3043.459, 'src': 'embed', 'start': 3015.232, 'weight': 1, 'content': [{'end': 3019.874, 'text': 'we will go and pick the third entry And now the third entry will be in V.', 'start': 3015.232, 'duration': 4.642}, {'end': 3022.594, 'text': 'The V will now contain zero.', 'start': 3019.874, 'duration': 2.72}, {'end': 3025.875, 'text': 'Previously it contained minus four, now it will contain zero.', 'start': 3022.954, 'duration': 2.921}, {'end': 3029.116, 'text': 'Min value is containing minus four now.', 'start': 3026.615, 'duration': 2.501}, {'end': 3033.017, 'text': 'So zero is smaller than minus four? No.', 'start': 3029.916, 'duration': 3.101}, {'end': 3036.657, 'text': 'If zero is smaller than minus four, then do this.', 'start': 3034.077, 'duration': 2.58}, {'end': 3038.718, 'text': 'But zero is not smaller than minus four.', 'start': 3037.177, 'duration': 1.541}, {'end': 3040.238, 'text': 'Then go to the else part.', 'start': 3039.158, 'duration': 1.08}, {'end': 3043.459, 'text': 'And else part is just saying, just go on, do nothing.', 'start': 3040.558, 'duration': 2.901}], 'summary': 'Picking the third entry results in v containing zero instead of minus four.', 'duration': 28.227, 'max_score': 3015.232, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI3015232.jpg'}, {'end': 3181.222, 'src': 'embed', 'start': 3148.38, 'weight': 0, 'content': [{'end': 3151.542, 'text': "So that's how we search the minimum.", 'start': 3148.38, 'duration': 3.162}, {'end': 3167.512, 'text': 'This return is also a keyword, which means if we just use that function, if we just use that pseudocode for this different kind of lists,', 'start': 3151.962, 'duration': 15.55}, {'end': 3171.635, 'text': 'with its sizes, whatever the list, this was just one example.', 'start': 3167.512, 'duration': 4.123}, {'end': 3174.457, 'text': 'If we change the list, the procedure will work.', 'start': 3171.695, 'duration': 2.762}, {'end': 3181.222, 'text': 'bug in the code was the increment counter statement was not there.', 'start': 3176.878, 'duration': 4.344}], 'summary': 'Demonstrates a search algorithm with a bug fix.', 'duration': 32.842, 'max_score': 3148.38, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI3148380.jpg'}, {'end': 5170.804, 'src': 'embed', 'start': 5135.394, 'weight': 6, 'content': [{'end': 5152.844, 'text': 'PyCharm If I discuss PyCharm, however, if I discuss some of its properties, let me just discuss first that the PyCharm is by the company JetBeans.', 'start': 5135.394, 'duration': 17.45}, {'end': 5163.508, 'text': 'If you have never used JetBeans other IDEs like Java IDE, then running your first code successfully can eat up a little bit of your time.', 'start': 5153.824, 'duration': 9.684}, {'end': 5166.509, 'text': 'Actually, a lot amount of your time maybe.', 'start': 5163.988, 'duration': 2.521}, {'end': 5170.804, 'text': 'such as setting up an interpreter, PyCharm.', 'start': 5167.682, 'duration': 3.122}], 'summary': 'Pycharm by jetbeans can consume a lot of time for setting up an interpreter.', 'duration': 35.41, 'max_score': 5135.394, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI5135394.jpg'}, {'end': 6113.28, 'src': 'embed', 'start': 6090.658, 'weight': 7, 'content': [{'end': 6098.488, 'text': 'if you press shift enter, the cell will run and the new the, the cursor, will go into the new cell.', 'start': 6090.658, 'duration': 7.83}, {'end': 6100.03, 'text': 'and there are a lot of controls.', 'start': 6098.488, 'duration': 1.542}, {'end': 6102.393, 'text': 'you should be seeing most of them.', 'start': 6100.03, 'duration': 2.363}, {'end': 6110.158, 'text': 'i mean getting A good grip on these controls will help you moving in this Jupyter Notebook very quickly.', 'start': 6102.393, 'duration': 7.765}, {'end': 6113.28, 'text': "For example, this is a Python tutorial, that's a Markdown cell.", 'start': 6110.338, 'duration': 2.942}], 'summary': 'Learn to efficiently navigate jupyter notebook with keyboard shortcuts and controls.', 'duration': 22.622, 'max_score': 6090.658, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI6090658.jpg'}, {'end': 6316.005, 'src': 'embed', 'start': 6292.217, 'weight': 10, 'content': [{'end': 6299.359, 'text': 'um, so this notebook is really really powerful, jupyter notebook, and coding in it is not just the coding.', 'start': 6292.217, 'duration': 7.142}, {'end': 6301.52, 'text': 'i mean it is preparing a document.', 'start': 6299.359, 'duration': 2.161}, {'end': 6304.221, 'text': 'if you want to prepare a document, you want to describe anything,', 'start': 6301.52, 'duration': 2.701}, {'end': 6309.123, 'text': 'you want to add images and at the end of the day it will be an html document for you.', 'start': 6304.221, 'duration': 4.902}, {'end': 6312.104, 'text': 'it can be shared on web.', 'start': 6309.123, 'duration': 2.981}, {'end': 6312.844, 'text': "i mean it's ready.", 'start': 6312.104, 'duration': 0.74}, {'end': 6316.005, 'text': 'uh, nothing, we we want to further finish it.', 'start': 6312.844, 'duration': 3.161}], 'summary': 'Jupyter notebook is a powerful tool for creating documents with coding, images, and sharing as html on the web.', 'duration': 23.788, 'max_score': 6292.217, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI6292217.jpg'}, {'end': 6482.845, 'src': 'embed', 'start': 6454.77, 'weight': 11, 'content': [{'end': 6460.872, 'text': 'but remember, previously in in jupyter notebook we type shift enter to run a particular command.', 'start': 6454.77, 'duration': 6.102}, {'end': 6464.033, 'text': 'here we just press enter and everything will work.', 'start': 6460.872, 'duration': 3.161}, {'end': 6471.515, 'text': 'if you want to clear the screen here, whatever the whatever we typed here, if you want to clear that, just press ctrl l.', 'start': 6464.033, 'duration': 7.482}, {'end': 6474.396, 'text': 'if you are on windows, ctrl l will work on windows.', 'start': 6471.515, 'duration': 2.881}, {'end': 6482.845, 'text': 'now ipython is just like uh, you can use the python in in this particular shell, just like a calculator.', 'start': 6475.976, 'duration': 6.869}], 'summary': 'In ipython, press enter to run commands and use ctrl l to clear the screen.', 'duration': 28.075, 'max_score': 6454.77, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI6454770.jpg'}], 'start': 2813.86, 'title': 'Python for data science', 'summary': "Covers a range of topics including searching for the minimum value in a list, pseudocode for sorting, python's simplicity and popularity, advantages of python for data science with 72,000 available packages, and popular python ides for data science with jupyter notebook's dominance backed by statistical evidence.", 'chapters': [{'end': 3181.222, 'start': 2813.86, 'title': 'Searching minimum value in a list', 'summary': 'Explains the process of searching for the minimum value in a list using pseudocode with a specific example, demonstrating the iterative comparison and selection process, resulting in the identification of the minimum value as -10.', 'duration': 367.362, 'highlights': ['The process of searching for the minimum value in a list is demonstrated through an example where the minimum value is identified as -10.', 'The iterative comparison and selection process is explained in detail, where each value in the list is compared to the current minimum value and updated if a smaller value is encountered.', 'The concept of using pseudocode for generalizing the process of finding the minimum value in lists of various sizes and compositions is introduced, highlighting the adaptability of the procedure.']}, {'end': 3789.501, 'start': 3181.662, 'title': 'Pseudocode for sorting and problem solving', 'summary': 'Introduces a pseudocode for finding the minimum value and its position in a list, followed by a pseudocode for sorting a list in ascending order, with a plan to convert these pseudocodes to python in the next video.', 'duration': 607.839, 'highlights': ['The pseudocode describes a simple concept of finding the minimum value and its position in a list by traversing the list element by element and updating the minimum value and position if a smaller value is found.', 'The algorithm for sorting a list involves using the previously defined minimum finding algorithm to find the minimum value from the list and populating a new sorted list while decrementing the size of the original list.', 'The chapter plans to convert the pseudocodes to Python in the next video, highlighting the transition from pseudocode to actual programming code and the differences in syntax and indexing between the two.']}, {'end': 4414.782, 'start': 3791.141, 'title': 'Pseudocode similarity to python', 'summary': "Explains how pseudocode highly resembles actual python code, emphasizing python's simplicity, expressiveness, and its ability to perform tasks with fewer lines of code, as well as highlighting the beginner-friendly nature of python programming. it also discusses the history and features of python, including its open-source nature, readability, and integration capabilities.", 'duration': 623.641, 'highlights': ["Python's simplicity and expressiveness make it highly similar to pseudocode, with the ability to perform tasks with fewer lines of code.", "Python's beginner-friendly nature is emphasized, making it easier for new data scientists to understand with its simple syntax and better readability.", "Python's history, including its introduction in the 1980s and official launch in 1989, is highlighted, along with its creator, Guido van Rossum, and its open-source accessibility for commercial purposes."]}, {'end': 4942.65, 'start': 4414.983, 'title': 'Python for data science', 'summary': "Highlights the advantages of python for data science, including its ease of use, extensive community support, and the abundance of data processing tools and packages, with around 72,000 available packages in the python package index and python's popularity leading to 85% of total job opportunities in the field of programming.", 'duration': 527.667, 'highlights': ["Python's popularity leads to 85% of total job opportunities in programming", 'Around 72,000 packages available in Python package index', "Python's ease of use and extensive community support", "Python's importance in data science and machine learning"]}, {'end': 5911.592, 'start': 4943.51, 'title': 'Best python ides for data science', 'summary': "Presents an overview of popular python ides for data science, including jupyter notebook, pycharm, and spyder, and provides statistical evidence showing jupyter notebook's dominance in popularity and usage among data science professionals, students, and across different regions.", 'duration': 968.082, 'highlights': ['Jupyter Notebook stands out as the most popular Python IDE for data science, as evidenced by statistical data showing its dominance in popularity and usage across different regions and among data science professionals, students, and in different work sectors.', 'PyCharm is highlighted for its better performance in handling large-scale coding projects, support for Anaconda, and powerful debugging capabilities, but its memory-intensive nature and slower startup time are noted as drawbacks.', 'Spyder, a lightweight and open-source IDE, is lauded for its integration with essential data-centric libraries, MATLAB-esque look and feel, and features such as syntax highlighting, code completion, and static code analysis.', 'The chapter also provides installation guidance for Python and Jupyter Notebook, with a recommendation to use the Anaconda distribution for an easier setup.']}, {'end': 6505.715, 'start': 5911.592, 'title': 'Mastering python: jupyter notebook basics', 'summary': 'Introduces the jupyter notebook interface, covering file management, cell types, keyboard shortcuts, and the versatility of the notebook in creating documents with code, markdown, latex, and html, ultimately enabling users to download the document in various formats, and emphasizes its significance in creating a complete python notebook.', 'duration': 594.123, 'highlights': ['Jupyter Notebook allows users to create documents with code, markdown, LaTeX, and HTML, and download the document in various formats such as PDF, notebook file, Python file, or slides.', 'The chapter emphasizes the significance of Jupyter Notebook in creating a complete Python notebook with descriptions and code, which can be shared as an HTML document on the web.', 'The interface of Jupyter Notebook is explained, covering file management, cell types, and keyboard shortcuts, providing a comprehensive understanding of its functionalities.']}], 'duration': 3691.855, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI2813860.jpg', 'highlights': ["Python's popularity leads to 85% of total job opportunities in programming", "Python's importance in data science and machine learning", "Python's simplicity and expressiveness make it highly similar to pseudocode, with the ability to perform tasks with fewer lines of code", "Python's beginner-friendly nature is emphasized, making it easier for new data scientists to understand with its simple syntax and better readability", 'Around 72,000 packages available in Python package index', 'Jupyter Notebook stands out as the most popular Python IDE for data science, as evidenced by statistical data showing its dominance in popularity and usage across different regions and among data science professionals, students, and in different work sectors', 'The process of searching for the minimum value in a list is demonstrated through an example where the minimum value is identified as -10', 'The iterative comparison and selection process is explained in detail, where each value in the list is compared to the current minimum value and updated if a smaller value is encountered', 'The concept of using pseudocode for generalizing the process of finding the minimum value in lists of various sizes and compositions is introduced, highlighting the adaptability of the procedure', 'The pseudocode describes a simple concept of finding the minimum value and its position in a list by traversing the list element by element and updating the minimum value and position if a smaller value is found', 'The algorithm for sorting a list involves using the previously defined minimum finding algorithm to find the minimum value from the list and populating a new sorted list while decrementing the size of the original list', 'The chapter plans to convert the pseudocodes to Python in the next video, highlighting the transition from pseudocode to actual programming code and the differences in syntax and indexing between the two', "Python's history, including its introduction in the 1980s and official launch in 1989, is highlighted, along with its creator, Guido van Rossum, and its open-source accessibility for commercial purposes", 'PyCharm is highlighted for its better performance in handling large-scale coding projects, support for Anaconda, and powerful debugging capabilities, but its memory-intensive nature and slower startup time are noted as drawbacks', 'Spyder, a lightweight and open-source IDE, is lauded for its integration with essential data-centric libraries, MATLAB-esque look and feel, and features such as syntax highlighting, code completion, and static code analysis', 'Jupyter Notebook allows users to create documents with code, markdown, LaTeX, and HTML, and download the document in various formats such as PDF, notebook file, Python file, or slides', 'The chapter emphasizes the significance of Jupyter Notebook in creating a complete Python notebook with descriptions and code, which can be shared as an HTML document on the web', 'The interface of Jupyter Notebook is explained, covering file management, cell types, and keyboard shortcuts, providing a comprehensive understanding of its functionalities', "Python's ease of use and extensive community support", 'The chapter also provides installation guidance for Python and Jupyter Notebook, with a recommendation to use the Anaconda distribution for an easier setup']}, {'end': 9533.761, 'segs': [{'end': 6876.418, 'src': 'embed', 'start': 6845.764, 'weight': 3, 'content': [{'end': 6852.692, 'text': 'For example, this is a variable name X, Y is a variable name Y, XY is a variable name itself.', 'start': 6845.764, 'duration': 6.928}, {'end': 6857.627, 'text': 'Now, these variables, they can store different kind of data.', 'start': 6853.524, 'duration': 4.103}, {'end': 6868.573, 'text': 'I mean whenever you want a particular data to be used again and again, it is better to save that data or label that data by a symbol,', 'start': 6857.727, 'duration': 10.846}, {'end': 6869.734, 'text': 'by a descriptive name.', 'start': 6868.573, 'duration': 1.161}, {'end': 6876.418, 'text': 'so that you can retrieve that data by using that label or symbol.', 'start': 6870.911, 'duration': 5.507}], 'summary': 'Variables x and y store different kinds of data for retrieval.', 'duration': 30.654, 'max_score': 6845.764, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI6845764.jpg'}, {'end': 8124.015, 'src': 'embed', 'start': 8092.828, 'weight': 2, 'content': [{'end': 8102.482, 'text': "So let's first press escape, then M just to change it to markdown and then escape one for heading, big heading.", 'start': 8092.828, 'duration': 9.654}, {'end': 8105.767, 'text': "And here I write, let's say operators.", 'start': 8103.303, 'duration': 2.464}, {'end': 8111.308, 'text': "and shift enter, it's runs and automatically then go to code.", 'start': 8106.906, 'duration': 4.402}, {'end': 8113.81, 'text': "okay, now let's say i have a variable.", 'start': 8111.308, 'duration': 2.502}, {'end': 8118.592, 'text': "so let's say what kind of variables i already have in the previous video.", 'start': 8113.81, 'duration': 4.782}, {'end': 8120.093, 'text': 'we use that.', 'start': 8118.592, 'duration': 1.501}, {'end': 8124.015, 'text': 'so we already have these kind of variables with us.', 'start': 8120.093, 'duration': 3.922}], 'summary': 'Demonstration of changing format to markdown and discussing variables.', 'duration': 31.187, 'max_score': 8092.828, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI8092828.jpg'}, {'end': 9079.229, 'src': 'embed', 'start': 9036.867, 'weight': 4, 'content': [{'end': 9038.288, 'text': 'False and true is false.', 'start': 9036.867, 'duration': 1.421}, {'end': 9040.569, 'text': 'False and false is false.', 'start': 9038.868, 'duration': 1.701}, {'end': 9052.113, 'text': 'So if you apply and operator and keyword to combine the two Boolean variables together, if both are true, then and will result a true.', 'start': 9041.489, 'duration': 10.624}, {'end': 9054.752, 'text': 'Otherwise, AND will result false.', 'start': 9052.771, 'duration': 1.981}, {'end': 9067.337, 'text': 'Other than this AND, there is another operator keyword OR.', 'start': 9056.513, 'duration': 10.824}, {'end': 9072.7, 'text': 'So this results false if both are false.', 'start': 9068.238, 'duration': 4.462}, {'end': 9079.229, 'text': 'false or false is false.', 'start': 9076.866, 'duration': 2.363}], 'summary': "Using 'and' operator: true and true = true, using 'or' operator: false or false = false", 'duration': 42.362, 'max_score': 9036.867, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI9036867.jpg'}, {'end': 9334.407, 'src': 'embed', 'start': 9302.971, 'weight': 0, 'content': [{'end': 9305.253, 'text': 'so these are our variables.', 'start': 9302.971, 'duration': 2.282}, {'end': 9310.557, 'text': "let's press who's to see what are the states of.", 'start': 9305.253, 'duration': 5.304}, {'end': 9313.22, 'text': 'so a is a boolean variable with value true.', 'start': 9310.557, 'duration': 2.663}, {'end': 9315.181, 'text': 'b is a boolean variable with value true.', 'start': 9313.22, 'duration': 1.961}, {'end': 9317.804, 'text': 'c is a boolean variable with value false.', 'start': 9315.181, 'duration': 2.623}, {'end': 9319.465, 'text': 'so now a is true.', 'start': 9317.804, 'duration': 1.661}, {'end': 9320.526, 'text': 'b is true.', 'start': 9319.465, 'duration': 1.061}, {'end': 9321.667, 'text': 'c is false.', 'start': 9320.526, 'duration': 1.141}, {'end': 9327.242, 'text': 'so that means let me print print A and B.', 'start': 9321.667, 'duration': 5.575}, {'end': 9334.407, 'text': 'What do you think? What will be the result? Let me print A and C.', 'start': 9327.242, 'duration': 7.165}], 'summary': 'Variables a, b, and c are boolean with respective values true, true, and false. printing a and b will result in true. printing a and c will result in true and false.', 'duration': 31.436, 'max_score': 9302.971, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI9302971.jpg'}, {'end': 9412.116, 'src': 'embed', 'start': 9368.504, 'weight': 1, 'content': [{'end': 9374.188, 'text': "or in another variable, let's say a is true or c is false.", 'start': 9368.504, 'duration': 5.684}, {'end': 9375.189, 'text': 'so what do you think?', 'start': 9374.188, 'duration': 1.001}, {'end': 9378.311, 'text': 'what will be the result here?', 'start': 9375.189, 'duration': 3.122}, {'end': 9381.594, 'text': 'because or gives false, when both are false.', 'start': 9378.311, 'duration': 3.283}, {'end': 9386.509, 'text': 'here, a is true, so the value of d will be true.', 'start': 9382.188, 'duration': 4.321}, {'end': 9395.47, 'text': 'further, not a, because a is true, not a will be false.', 'start': 9386.509, 'duration': 8.961}, {'end': 9398.091, 'text': 'similarly, not b.', 'start': 9395.47, 'duration': 2.621}, {'end': 9399.251, 'text': 'b is true.', 'start': 9398.091, 'duration': 1.16}, {'end': 9402.272, 'text': 'so not b will be false.', 'start': 9399.251, 'duration': 3.021}, {'end': 9404.512, 'text': 'not c.', 'start': 9402.272, 'duration': 2.24}, {'end': 9405.372, 'text': 'c is true.', 'start': 9404.512, 'duration': 0.86}, {'end': 9408.473, 'text': 'c is false, so not c will be true.', 'start': 9405.372, 'duration': 3.101}, {'end': 9412.116, 'text': 'similarly, not d.', 'start': 9408.473, 'duration': 3.643}], 'summary': 'Logical operations result in true for a=1, b=1, c=0, d=1.', 'duration': 43.612, 'max_score': 9368.504, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI9368504.jpg'}], 'start': 6505.715, 'title': 'Introduction to ipython and variables in python', 'summary': 'Introduces the enhanced variant of ipython shell called jupyter notebooks, highlighting its better interfaces and features, and later discusses the concept of variables in python, including different data types such as integers, floats, complex numbers, and strings. it also covers memory management, variable deletion, and the dynamic typing feature of python. it emphasizes that python supports various data types and highlights the upcoming discussion on arithmetic operators.', 'chapters': [{'end': 6736.393, 'start': 6505.715, 'title': 'Ipython shell and variables', 'summary': 'Discusses the use of ipython shell as a calculator allowing the use of variables to save and reuse results, demonstrating the flexibility and functionality of python for complex calculations and programming.', 'duration': 230.678, 'highlights': ['The IPython shell allows for complex Python coding and can be used as a calculator, enabling the declaration and retrieval of variables for saving and reusing results.', 'Using variables in Python provides the ability to save and retrieve results, allowing for the combination of multiple results to achieve complex computations.', "The flexibility of Python's IPython shell enables the saving and reusing of previous results using variables, providing support for complex calculations and programming tasks.", 'The use of variables in Python, even in a calculator context, demonstrates the capability to save and reuse results, offering greater functionality than traditional calculators.']}, {'end': 7193.041, 'start': 6737.194, 'title': 'Introduction to ipython and variables in python', 'summary': 'Introduces the enhanced variant of ipython shell called jupyter notebooks, highlighting its better interfaces and features, and later discusses the concept of variables in python, including different data types such as integers, floats, complex numbers, and strings.', 'duration': 455.847, 'highlights': ['The Jupyter notebook is an enhanced variant of IPython shell, offering better interfaces and features, which several people prefer over the traditional IPython shell.', 'Variables in Python store data and can be used later on, with examples of variable names and their purpose in storing and retrieving data.', 'Different data types in Python such as integers, floats, complex numbers, and strings are explained with examples of their usage and how they are assigned to variables.']}, {'end': 7790.293, 'start': 7193.041, 'title': 'Python variables and data types', 'summary': 'Explains variables in python, including integer, float, and string data types, and multiple assignment. it also covers memory management, variable deletion, and the dynamic typing feature of python. it emphasizes that python supports various data types and highlights the upcoming discussion on arithmetic operators.', 'duration': 597.252, 'highlights': ['Python supports various data types, including integer, float, complex, and string.', 'Explanation of multiple assignment and changing variable types based on assigned values.', 'Memory management and variable deletion in Python.', 'Dynamic typing feature of Python, where the assigned content determines the variable type.', 'Upcoming discussion on arithmetic operators and operations on variables.']}, {'end': 8355.879, 'start': 7791.633, 'title': 'Arithmetic operators in python', 'summary': 'Covers the usage of arithmetic operators in python, including addition, subtraction, division, multiplication, floor division, and power computation, with examples and explanations of data type interactions and type casting.', 'duration': 564.246, 'highlights': ['The chapter covers the usage of arithmetic operators in Python, including addition, subtraction, division, multiplication, floor division, and power computation.', 'Examples and explanations of data type interactions and type casting are provided.', 'The result of adding an integer with a floating point number is a floating point number due to type casting.']}, {'end': 9533.761, 'start': 8355.879, 'title': 'Python variables, operators, and boolean data type', 'summary': "Introduces python variables, operators for string concatenation and division, the default variable underscore, naming conventions for variables, and the boolean data type. the naming convention for variable names is discussed, and it is concluded that a variable name cannot start with a digit. the chapter also covers the boolean data type, its two states 'true' and 'false', and the logical operators 'and', 'or', and 'not'. comparison operators are introduced, and examples of using these operators with boolean variables are given.", 'duration': 1177.882, 'highlights': ['A variable name cannot start with a digit', "Introduction to Boolean data type and logical operators 'and', 'or', and 'not'", 'Introduction to comparison operators']}], 'duration': 3028.046, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI6505715.jpg', 'highlights': ['The Jupyter notebook is an enhanced variant of IPython shell, offering better interfaces and features, which several people prefer over the traditional IPython shell.', 'The chapter covers the usage of arithmetic operators in Python, including addition, subtraction, division, multiplication, floor division, and power computation.', 'Python supports various data types, including integer, float, complex, and string.', 'Memory management and variable deletion in Python.', "Introduction to Boolean data type and logical operators 'and', 'or', and 'not'"]}, {'end': 11874.755, 'segs': [{'end': 9866.233, 'src': 'embed', 'start': 9823.312, 'weight': 7, 'content': [{'end': 9826.753, 'text': "And I'm comparing three double equals to 3.0.", 'start': 9823.312, 'duration': 3.441}, {'end': 9829.734, 'text': 'One is integer, another is a floating point number.', 'start': 9826.753, 'duration': 2.981}, {'end': 9831.615, 'text': "So what will be the result? Let's see.", 'start': 9830.314, 'duration': 1.301}, {'end': 9840.209, 'text': 'The result is true because they are comparing the values by discarding the decimal position.', 'start': 9832.642, 'duration': 7.567}, {'end': 9851.68, 'text': "Further, let's see, three is smaller or equal to, so let's say x is equal to four.", 'start': 9841.39, 'duration': 10.29}, {'end': 9866.233, 'text': "y is equal to 9 and z is equal to, let's say, 8.3, and r is equal to minus 3.", 'start': 9852.948, 'duration': 13.285}], 'summary': 'Comparing 3==3.0 resulted in true. evaluating 3<=x, y, z, r.', 'duration': 42.921, 'max_score': 9823.312, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI9823312.jpg'}, {'end': 10028.82, 'src': 'embed', 'start': 9984.124, 'weight': 0, 'content': [{'end': 9987.386, 'text': 'Let me just say Z is larger than Y.', 'start': 9984.124, 'duration': 3.262}, {'end': 9990.428, 'text': 'Let me just check Z is larger than Y.', 'start': 9987.386, 'duration': 3.042}, {'end': 9993.33, 'text': 'Z is larger than Y, just to tell you.', 'start': 9990.428, 'duration': 2.902}, {'end': 9997.012, 'text': 'So this is true, this is false.', 'start': 9994.27, 'duration': 2.742}, {'end': 10000.574, 'text': 'Both N of these.', 'start': 9998.713, 'duration': 1.861}, {'end': 10003.496, 'text': 'or let me switch the.', 'start': 10000.574, 'duration': 2.922}, {'end': 10005.897, 'text': 'let me switch this thing.', 'start': 10003.496, 'duration': 2.401}, {'end': 10006.878, 'text': 'R equals to X.', 'start': 10005.897, 'duration': 0.981}, {'end': 10018.294, 'text': 'just want to show you the precedence of r and x is smaller than y.', 'start': 10008.408, 'duration': 9.886}, {'end': 10025.078, 'text': 'so now, if you see, this is false, this is true.', 'start': 10018.294, 'duration': 6.784}, {'end': 10028.82, 'text': 'false and true is true.', 'start': 10025.078, 'duration': 3.742}], 'summary': 'Z is larger than y, r equals x, showing precedence and comparison results.', 'duration': 44.696, 'max_score': 9984.124, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI9984124.jpg'}, {'end': 10663.154, 'src': 'embed', 'start': 10632.802, 'weight': 12, 'content': [{'end': 10635.902, 'text': 'This A is called argument to a function print.', 'start': 10632.802, 'duration': 3.1}, {'end': 10639.763, 'text': 'Similarly, round is a function, 4.6 is an argument.', 'start': 10636.422, 'duration': 3.341}, {'end': 10642.423, 'text': 'Round is a function, 4.3 is an argument.', 'start': 10640.403, 'duration': 2.02}, {'end': 10647.004, 'text': 'We will see functions in details and we will be writing our own functions as well.', 'start': 10642.983, 'duration': 4.021}, {'end': 10654.525, 'text': 'But for now, just bear with me that functions are these kind of features that are available.', 'start': 10647.604, 'duration': 6.921}, {'end': 10658.546, 'text': 'However, we will be writing our own functions later on.', 'start': 10655.545, 'duration': 3.001}, {'end': 10663.154, 'text': 'So this particular function accepts two arguments.', 'start': 10660.333, 'duration': 2.821}], 'summary': 'Introduction to functions, including examples with 4.6 and 4.3 as arguments.', 'duration': 30.352, 'max_score': 10632.802, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI10632802.jpg'}, {'end': 10795.18, 'src': 'embed', 'start': 10752.938, 'weight': 5, 'content': [{'end': 10774.927, 'text': "However, if you call this round function with more than one argument, for example 4.556789,, let's say or with argument let's say two.", 'start': 10752.938, 'duration': 21.989}, {'end': 10780.773, 'text': 'that means the result should be only two decimal places after the decimal point.', 'start': 10774.927, 'duration': 5.846}, {'end': 10783.57, 'text': 'So in this case the result is 4.56,.', 'start': 10781.849, 'duration': 1.721}, {'end': 10792.618, 'text': 'and the reason is this five is rounded based on the next digit and the next digit is larger than five.', 'start': 10783.57, 'duration': 9.048}, {'end': 10793.618, 'text': 'hence it is rounded up.', 'start': 10792.618, 'duration': 1}, {'end': 10795.18, 'text': 'So 4.56.', 'start': 10794.339, 'duration': 0.841}], 'summary': 'The round function rounds numbers to two decimal places if called with more than one argument, such as 4.556789, resulting in 4.56 due to rounding up.', 'duration': 42.242, 'max_score': 10752.938, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI10752938.jpg'}, {'end': 10917.886, 'src': 'embed', 'start': 10894.636, 'weight': 2, 'content': [{'end': 10901.481, 'text': 'for example, in this particular case, the quotient is five and the remainder is two, because if five is divided by,', 'start': 10894.636, 'duration': 6.845}, {'end': 10910.541, 'text': 'if twenty seven is divided by five, the result is five, but then the remainder is two, And the result is returned in a kind of an ordered pair.', 'start': 10901.481, 'duration': 9.06}, {'end': 10917.886, 'text': 'And these kind of collection in which we have two or more elements.', 'start': 10911.401, 'duration': 6.485}], 'summary': 'In this case, the quotient is five and the remainder is two when twenty seven is divided by five.', 'duration': 23.25, 'max_score': 10894.636, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI10894636.jpg'}, {'end': 10971.674, 'src': 'embed', 'start': 10942.662, 'weight': 1, 'content': [{'end': 10944.123, 'text': 'but right now we will.', 'start': 10942.662, 'duration': 1.461}, {'end': 10949.066, 'text': 'a tuple is just an ordered list which we will see in detail.', 'start': 10944.123, 'duration': 4.943}, {'end': 10955.642, 'text': "so let's see the working of the stiff mode function in in Jupyter Notebook.", 'start': 10949.066, 'duration': 6.576}, {'end': 10955.962, 'text': "let's see.", 'start': 10955.642, 'duration': 0.32}, {'end': 10961.586, 'text': "So let's say we have div mode.", 'start': 10956.582, 'duration': 5.004}, {'end': 10971.674, 'text': "Let's say for example we have 34 and then we have let's say 10 or maybe let's say nine.", 'start': 10962.827, 'duration': 8.847}], 'summary': 'Introduction to tuple and stiff mode function in jupyter notebook.', 'duration': 29.012, 'max_score': 10942.662, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI10942662.jpg'}, {'end': 11073.398, 'src': 'embed', 'start': 10995.27, 'weight': 3, 'content': [{'end': 11003.917, 'text': "so if you see the G, the type of G, if you just type the type of, if you just print the type of G, it's a tuple which we will see in details.", 'start': 10995.27, 'duration': 8.647}, {'end': 11007.841, 'text': 'And if you see the contents of G.', 'start': 11004.618, 'duration': 3.223}, {'end': 11015.585, 'text': 'if you see the contents of G, the contents of G are three and seven, And if you want to access each element independently,', 'start': 11007.841, 'duration': 7.744}, {'end': 11025.946, 'text': 'then you can access the first element, because if there are multiple elements in a variable, normally that kind of variables are called collections.', 'start': 11015.585, 'duration': 10.361}, {'end': 11027.387, 'text': 'that we will see in detail later on.', 'start': 11025.946, 'duration': 1.441}, {'end': 11034.088, 'text': 'And these are the indexing, the positioning is start by zero rather than one.', 'start': 11028.167, 'duration': 5.921}, {'end': 11034.588, 'text': 'So G.', 'start': 11034.148, 'duration': 0.44}, {'end': 11044.86, 'text': 'zero means the first element of G, which is three in this case, and the second element of G is one at at one, which is seven.', 'start': 11034.588, 'duration': 10.272}, {'end': 11046.541, 'text': 'so this is basically.', 'start': 11044.86, 'duration': 1.681}, {'end': 11053.866, 'text': 'this is called the index or position of of elements or data in in this particular collection.', 'start': 11046.541, 'duration': 7.325}, {'end': 11057.268, 'text': 'we will see these indexing and all these kind of collections in detail.', 'start': 11053.866, 'duration': 3.402}, {'end': 11065.873, 'text': 'uh, in, uh, in the, in the data structures course, when we will see arrays and strings and, uh, different kind of structures.', 'start': 11057.268, 'duration': 8.605}, {'end': 11070.116, 'text': 'but, and div mode sometimes is uh, is basically uh.', 'start': 11065.873, 'duration': 4.243}, {'end': 11073.398, 'text': 'sometimes it is helpful.', 'start': 11071.436, 'duration': 1.962}], 'summary': 'The variable g is a tuple with elements 3 and 7, indexed from 0, useful for data structures.', 'duration': 78.128, 'max_score': 10995.27, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI10995270.jpg'}], 'start': 9534.161, 'title': 'Comparison operators and boolean data type', 'summary': "Covers comparison operators for checking equality, inequality, less than, greater than, less than or equal to, and greater than or equal to, with examples provided for each, and concludes with a preview of the next video on using these operators in jupyter. it also explains comparison operations in python, including examples of using comparison operators such as less than, equal to, and not equal to, and demonstrates how the results are stored in variables of boolean type, with examples showing the results of different comparisons and the precedence of 'and' and 'or' operators. additionally, it explains the precedence of logical operators in python, highlighting the importance of parentheses to specify the order of operations, and demonstrates the use of the round function in python, illustrating its capability to round floating point numbers to the nearest integer and its ability to accept additional arguments for more specific rounding. moreover, it covers the round function's behavior with different arguments, the div mode function returning quotient and remainder, and the isinstance function checking data type, with examples and use cases. the chapter also introduces the 'is instance' function to check if a value belongs to a specific data type, demonstrating examples with integers, floats, and complex numbers. it also explains the 'power' function to calculate exponentiation and modulus, and introduces the 'input' function to receive user input, with emphasis on the data type conversion and potential errors.", 'chapters': [{'end': 9653.712, 'start': 9534.161, 'title': 'Comparison operators and boolean data type', 'summary': 'Covers comparison operators for checking equality, inequality, less than, greater than, less than or equal to, and greater than or equal to, with examples provided for each, and concludes with a preview of the next video on using these operators in jupyter.', 'duration': 119.551, 'highlights': ['The result of comparison is always a Boolean, either true or false, for example, x is not equal to y results in true if x and y have different values.', 'The chapter covers comparison operators such as less than, greater than, less or equal to, and greater than or equal to, providing examples to illustrate their usage.', 'The next video will focus on using these operators in Jupyter and combining them with ANDs and ORs.']}, {'end': 10092.337, 'start': 9654.747, 'title': 'Comparison operations in python', 'summary': "Explains comparison operations in python, including examples of using comparison operators such as less than, equal to, and not equal to, and demonstrates how the results are stored in variables of boolean type, with examples showing the results of different comparisons and the precedence of 'and' and 'or' operators.", 'duration': 437.59, 'highlights': ['Comparison results are always boolean, either true or false.', 'Examples of comparison operations include 2 is less than 3, 3 equals to 4, and 3 double equals to 3.0, with the results being true and false.', 'The type of the result variable storing the comparison outcome is boolean.', "Demonstration of the precedence of 'and' and 'or' operators in determining the overall result of multiple comparisons."]}, {'end': 10752.918, 'start': 10094.648, 'title': 'Boolean comparisons and python functions', 'summary': 'Explains the precedence of logical operators in python, highlighting the importance of parentheses to specify the order of operations, and demonstrates the use of the round function in python, illustrating its capability to round floating point numbers to the nearest integer and its ability to accept additional arguments for more specific rounding.', 'duration': 658.27, 'highlights': ['The chapter emphasizes the importance of using parentheses to specify the order of operations for logical operators in Python, to avoid confusion and ensure the correct result.', 'It demonstrates the use of the round function in Python, showcasing its ability to round floating point numbers to the nearest integer and its capability to accept additional arguments for more specific rounding, such as rounding to a specified number of decimal places.', 'The chapter discusses the implementation of the round function in Python, explaining its behavior when accepting different input arguments, emphasizing the flexibility and versatility of the function.']}, {'end': 11223.268, 'start': 10752.938, 'title': 'Python functions and data types', 'summary': "Covers the round function's behavior with different arguments, the div mode function returning quotient and remainder, and the isinstance function checking data type, with examples and use cases.", 'duration': 470.33, 'highlights': ['The round function rounds the number based on the next digit and the next digit being larger than five, resulting in 4.56 when called with two arguments, and 4.55 when called with three, showcasing its behavior with different arguments.', 'The div mode function divides and returns the quotient and remainder, demonstrated with an example of 27 divided by 5, resulting in a tuple (5, 2), providing insights on its functionality and output format.', 'The isInstance function checks if a given value belongs to a specific data type, such as using it to verify if 1 is an integer, highlighting its utility in data validation and handling different input types.']}, {'end': 11874.755, 'start': 11223.308, 'title': 'Built-in functions in python', 'summary': "Introduces the 'is instance' function to check if a value belongs to a specific data type, demonstrating examples with integers, floats, and complex numbers. it also explains the 'power' function to calculate exponentiation and modulus, and introduces the 'input' function to receive user input, with emphasis on the data type conversion and potential errors.", 'duration': 651.447, 'highlights': ["The 'is instance' function checks if a value belongs to a specific data type, providing examples with integers, floats, and complex numbers.", "The 'power' function calculates exponentiation and modulus, with examples of computing 2 raised to the power 4 and its remainder by 7.", "The 'input' function is introduced for receiving user input, with emphasis on data type conversion and potential errors, illustrating the conversion of entered string to integer and float."]}], 'duration': 2340.594, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI9534161.jpg', 'highlights': ['The result of comparison is always a Boolean, for example, x is not equal to y results in true if x and y have different values.', 'The chapter covers comparison operators such as less than, greater than, less or equal to, and greater than or equal to, providing examples to illustrate their usage.', 'The next video will focus on using these operators in Jupyter and combining them with ANDs and ORs.', 'The round function rounds the number based on the next digit and the next digit being larger than five, resulting in 4.56 when called with two arguments, and 4.55 when called with three, showcasing its behavior with different arguments.', 'The div mode function divides and returns the quotient and remainder, demonstrated with an example of 27 divided by 5, resulting in a tuple (5, 2), providing insights on its functionality and output format.', "The 'is instance' function checks if a value belongs to a specific data type, providing examples with integers, floats, and complex numbers.", "The 'power' function calculates exponentiation and modulus, with examples of computing 2 raised to the power 4 and its remainder by 7.", "The 'input' function is introduced for receiving user input, with emphasis on data type conversion and potential errors, illustrating the conversion of entered string to integer and float.", 'The chapter emphasizes the importance of using parentheses to specify the order of operations for logical operators in Python, to avoid confusion and ensure the correct result.', 'The round function showcases its ability to round floating point numbers to the nearest integer and its capability to accept additional arguments for more specific rounding, such as rounding to a specified number of decimal places.', 'The isInstance function checks if a given value belongs to a specific data type, such as using it to verify if 1 is an integer, highlighting its utility in data validation and handling different input types.', 'The type of the result variable storing the comparison outcome is boolean.', "Demonstration of the precedence of 'and' and 'or' operators in determining the overall result of multiple comparisons.", 'Examples of comparison operations include 2 is less than 3, 3 equals to 4, and 3 double equals to 3.0, with the results being true and false.']}, {'end': 13547.704, 'segs': [{'end': 12065.931, 'src': 'embed', 'start': 12036.57, 'weight': 0, 'content': [{'end': 12039.841, 'text': 'So A is some number the user will supply when the code will run.', 'start': 12036.57, 'duration': 3.271}, {'end': 12042.931, 'text': 'B is some number the user will supply when the code will run.', 'start': 12039.861, 'duration': 3.07}, {'end': 12048.766, 'text': 'Now, once you have A and B in front of you, obviously the user will supply that on the fly.', 'start': 12044.065, 'duration': 4.701}, {'end': 12058.269, 'text': "You don't know what the value of A and B are because when the program will run, only at that time the A will be populated and B will be populated.", 'start': 12048.786, 'duration': 9.483}, {'end': 12065.931, 'text': "Your task is whatever the value of A is that you don't know, whatever the value of B is that you don't know, the user will supply those values.", 'start': 12058.649, 'duration': 7.282}], 'summary': 'The user will supply unknown values for a and b when running the code.', 'duration': 29.361, 'max_score': 12036.57, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI12036570.jpg'}, {'end': 12311.324, 'src': 'embed', 'start': 12274.387, 'weight': 10, 'content': [{'end': 12277.409, 'text': 'this is the indentation that defines the block of a.', 'start': 12274.387, 'duration': 3.022}, {'end': 12281.212, 'text': "let's say, if I want to print a, then I want to print.", 'start': 12277.409, 'duration': 3.803}, {'end': 12301.64, 'text': "let's say, I am still inside if condition condition and I so whatever that starts from this, whatever that starts from,", 'start': 12281.212, 'duration': 20.428}, {'end': 12311.324, 'text': "whatever that starts from this alignment, if i write something here, let's say x is equal to 5.", 'start': 12301.64, 'duration': 9.684}], 'summary': 'Demonstrates indentation for defining a block, with an example of if condition and variable assignment.', 'duration': 36.937, 'max_score': 12274.387, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI12274387.jpg'}, {'end': 12806.284, 'src': 'embed', 'start': 12745.812, 'weight': 2, 'content': [{'end': 12752.277, 'text': 'Then we applied another if condition to check if a is greater than b, then print a.', 'start': 12745.812, 'duration': 6.465}, {'end': 12764.632, 'text': 'The else clause or the else part of if is as the name suggests, if this condition is true.', 'start': 12754.028, 'duration': 10.604}, {'end': 12769.573, 'text': 'sorry, if this condition is true, this particular condition is true, then go there.', 'start': 12764.632, 'duration': 4.941}, {'end': 12775.535, 'text': 'If this is not true, which means else, if this is true, then go there, else go there.', 'start': 12770.374, 'duration': 5.161}, {'end': 12779.497, 'text': 'So if this is true, then you land here.', 'start': 12776.336, 'duration': 3.161}, {'end': 12782.758, 'text': 'If this is false, then you land in else part for sure.', 'start': 12779.797, 'duration': 2.961}, {'end': 12790.171, 'text': 'And this else is, I mean, if B is greater than A, if that condition is true, then you print this thing.', 'start': 12784.286, 'duration': 5.885}, {'end': 12795.235, 'text': 'Otherwise, A might be greater than B or A might be equal to B.', 'start': 12790.751, 'duration': 4.484}, {'end': 12797.117, 'text': 'Either way, you land in else part.', 'start': 12795.235, 'duration': 1.882}, {'end': 12806.284, 'text': 'So this if and else, they both have this alignment, but then the block of else started from this particular alignment.', 'start': 12797.717, 'duration': 8.567}], 'summary': 'Explaining if-else conditions and their alignment in code.', 'duration': 60.472, 'max_score': 12745.812, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI12745812.jpg'}, {'end': 13240.634, 'src': 'embed', 'start': 13174.826, 'weight': 7, 'content': [{'end': 13182.151, 'text': 'So you will land in else part and B will be printed and then a statement will be printed which is not an F.', 'start': 13174.826, 'duration': 7.325}, {'end': 13186.274, 'text': 'So yeah, so B is printed and not an F.', 'start': 13182.151, 'duration': 4.123}, {'end': 13192.657, 'text': 'If B is 10, then what will happen? A equals to B, that is false, so you will not land here.', 'start': 13186.274, 'duration': 6.383}, {'end': 13196.458, 'text': 'Else if A is larger than B, true, you will land here.', 'start': 13193.377, 'duration': 3.081}, {'end': 13198.459, 'text': 'Because you land here, else will not execute.', 'start': 13196.518, 'duration': 1.941}, {'end': 13202.74, 'text': 'So A will be printed, and then not an if.', 'start': 13199.219, 'duration': 3.521}, {'end': 13210.022, 'text': "If A is 10 and B is also 10, let's say, then you have equal, yeah.", 'start': 13203.54, 'duration': 6.482}, {'end': 13212.303, 'text': "So that's else if.", 'start': 13210.602, 'duration': 1.701}, {'end': 13215.564, 'text': 'Okay, so.', 'start': 13214.503, 'duration': 1.061}, {'end': 13224.281, 'text': "That's about if-else-if or short form is lf-else structure.", 'start': 13218.436, 'duration': 5.845}, {'end': 13231.226, 'text': 'In the next video we will be talking more about this if-else-if-else structure in a bit more detail,', 'start': 13224.881, 'duration': 6.345}, {'end': 13238.492, 'text': 'and we will also be giving you a short form of this kind of else-if-else-if-else-if structure.', 'start': 13231.226, 'duration': 7.266}, {'end': 13240.634, 'text': 'So hope to see you in the next video.', 'start': 13238.912, 'duration': 1.722}], 'summary': 'Explaining if-else-if structure and comparison scenarios.', 'duration': 65.808, 'max_score': 13174.826, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI13174826.jpg'}, {'end': 13495.242, 'src': 'embed', 'start': 13444.275, 'weight': 3, 'content': [{'end': 13455.1, 'text': "To enhance readability, it is good to include a space after the variable and space, but don't actually write the space inside that,", 'start': 13444.275, 'duration': 10.825}, {'end': 13459.582, 'text': 'because larger and equal to they combine without space is an operator.', 'start': 13455.1, 'duration': 4.482}, {'end': 13467.485, 'text': "So if A is larger than 85, then print, let's say, A grade.", 'start': 13460.382, 'duration': 7.103}, {'end': 13491.86, 'text': 'L if a is larger or equal to 80 and a is smaller than 85.', 'start': 13475.65, 'duration': 16.21}, {'end': 13495.242, 'text': 'So let me write this in a more readable form.', 'start': 13491.86, 'duration': 3.382}], 'summary': 'Explaining the importance of including spaces after variables, and providing examples of conditional statements for readability.', 'duration': 50.967, 'max_score': 13444.275, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI13444275.jpg'}, {'end': 13547.704, 'src': 'embed', 'start': 13523.605, 'weight': 1, 'content': [{'end': 13532.192, 'text': 'Although not writing the parentheses is also okay, but writing the parentheses make code a little more readable.', 'start': 13523.605, 'duration': 8.587}, {'end': 13541.362, 'text': 'So, for example, if a is smaller than 85 and a is larger than 80, If that is true, so remember,', 'start': 13533.013, 'duration': 8.349}, {'end': 13545.023, 'text': 'AND is true only when the left side is true and right side, both are true.', 'start': 13541.362, 'duration': 3.661}, {'end': 13547.704, 'text': 'Then this whole condition becomes true.', 'start': 13545.563, 'duration': 2.141}], 'summary': "Writing parentheses makes code more readable, and 'and' is true when both sides are true.", 'duration': 24.099, 'max_score': 13523.605, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI13523605.jpg'}], 'start': 11876.076, 'title': 'Python functions, control flow, and if conditions', 'summary': 'Covers the implementation and usage of functions in python, including the power function, and explains the concept of control flow using if conditions to determine and print the larger of two user-supplied values. it also delves into understanding if conditions in jupyter notebook and demonstrates the use of if conditions to print the bigger number out of two input numbers, achieving the task with examples resulting in 45 and 22. additionally, it explains the if-else and else-if structures in python, including examples and their execution flow, and illustrates how to use nested if-else statements and a short form of if-else structure, along with demonstrating a nested if-else structure to determine grades based on marks input by the user.', 'chapters': [{'end': 12232.04, 'start': 11876.076, 'title': 'Python functions and control flow', 'summary': 'Covers the implementation and usage of functions in python, including the power function, and explains the concept of control flow using if conditions to determine and print the larger of two user-supplied values.', 'duration': 355.964, 'highlights': ['The power function in Python is discussed, including options with no arguments, two arguments, and remainder with three arguments.', 'The usage of the help function in Python to retrieve information about built-in functions is explained.', 'The upcoming video will focus on comparisons and decision-making in Python, introducing the concept of control flow.', 'The concept of control flow in Python is introduced, demonstrating the usage of if conditions to determine and print the larger of two user-supplied values.']}, {'end': 12491.32, 'start': 12232.66, 'title': 'Understanding if conditions in jupyter notebook', 'summary': "Explains the concept of if conditions in jupyter notebook, illustrating how to use if statements to control the flow of code execution based on conditions, and demonstrating the impact of different input values on the program's output.", 'duration': 258.66, 'highlights': ['The if condition in Jupyter Notebook can contain a whole block of code, not limited to a single line, allowing for the execution of multiple lines of code based on the condition being true.', 'The if condition in Jupyter Notebook allows for the control of code execution based on specific conditions, as demonstrated by the comparison of input values A and B to determine which statements are executed.', 'The explanation includes examples of input values for A and B, showing how the if condition determines which statements are executed based on whether the condition is true or false.']}, {'end': 12745.812, 'start': 12491.32, 'title': 'Using if conditions to print the bigger number', 'summary': 'Explains the use of if conditions to print the bigger number out of two input numbers, demonstrating the comparison operators and logical flow, achieving the task with examples resulting in 45 and 22.', 'duration': 254.492, 'highlights': ['The chapter explains the use of if conditions to print the bigger number out of two input numbers, demonstrating the comparison operators and logical flow, achieving the task with examples resulting in 45 and 22.', 'The if conditions are used to compare the input numbers and determine the larger one, showcasing the logical flow and execution of the if statements.', 'The code effectively uses nested if conditions to accurately print the larger number based on the user input, demonstrating the functionality and logic behind nested if statements.']}, {'end': 13547.704, 'start': 12745.812, 'title': 'Understanding if-else structure in python', 'summary': 'Explains the if-else and else-if structures in python, including examples and their execution flow, illustrating how to use nested if-else statements and a short form of if-else structure. it also demonstrates a nested if-else structure to determine grades based on marks input by the user.', 'duration': 801.892, 'highlights': ['The chapter explains the if-else and else-if structures in Python, including examples and their execution flow', 'Illustrates how to use nested if-else statements', 'Demonstrates a nested if-else structure to determine grades based on marks input by the user', 'Explains a short form of if-else structure']}], 'duration': 1671.628, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI11876076.jpg', 'highlights': ['The power function in Python is discussed, including options with no arguments, two arguments, and remainder with three arguments.', 'The usage of the help function in Python to retrieve information about built-in functions is explained.', 'The concept of control flow in Python is introduced, demonstrating the usage of if conditions to determine and print the larger of two user-supplied values.', 'The if condition in Jupyter Notebook can contain a whole block of code, not limited to a single line, allowing for the execution of multiple lines of code based on the condition being true.', 'The chapter explains the use of if conditions to print the bigger number out of two input numbers, demonstrating the comparison operators and logical flow, achieving the task with examples resulting in 45 and 22.', 'The chapter explains the if-else and else-if structures in Python, including examples and their execution flow', 'The code effectively uses nested if conditions to accurately print the larger number based on the user input, demonstrating the functionality and logic behind nested if statements.', 'Illustrates how to use nested if-else statements', 'Demonstrates a nested if-else structure to determine grades based on marks input by the user', 'Explains a short form of if-else structure', 'The upcoming video will focus on comparisons and decision-making in Python, introducing the concept of control flow.']}, {'end': 15006.065, 'segs': [{'end': 13631.84, 'src': 'embed', 'start': 13548.684, 'weight': 1, 'content': [{'end': 13559.266, 'text': 'And I promised you that I will show you the power of comparisons and actually combining the Boolean variables using ANDs and ORs and stuff like so.', 'start': 13548.684, 'duration': 10.582}, {'end': 13561.286, 'text': 'So here you are seeing the one.', 'start': 13559.766, 'duration': 1.52}, {'end': 13601.096, 'text': "In that case, let's say print, Let's say A minus blade and lf if A is smaller than 80 and A is bigger or equal to 75.", 'start': 13562.346, 'duration': 38.75}, {'end': 13604.197, 'text': "If that's the case, then what should we do?", 'start': 13601.096, 'duration': 3.101}, {'end': 13610.281, 'text': 'Let me omit the parenthesis just to show that, whether writing parenthesis or not, writing parenthesis is perfectly okay.', 'start': 13604.577, 'duration': 5.704}, {'end': 13616.224, 'text': 'I just recommend to write parenthesis so the code becomes much more readable than otherwise.', 'start': 13611.341, 'duration': 4.883}, {'end': 13623.788, 'text': "Okay, then we have print, let's say B grade.", 'start': 13618.345, 'duration': 5.443}, {'end': 13631.84, 'text': "and let's say one more lf.", 'start': 13626.198, 'duration': 5.642}], 'summary': 'Demonstrating the power of comparisons and combining boolean variables using ands and ors for conditions in python.', 'duration': 83.156, 'max_score': 13548.684, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI13548684.jpg'}, {'end': 14440.128, 'src': 'embed', 'start': 14395.594, 'weight': 0, 'content': [{'end': 14402.758, 'text': 'or you may have an if condition inside that else part here, for example, you can write an if condition here if whatever.', 'start': 14395.594, 'duration': 7.164}, {'end': 14403.758, 'text': 'that is also.', 'start': 14402.758, 'duration': 1}, {'end': 14405.739, 'text': 'that is also perfectly fine.', 'start': 14403.758, 'duration': 1.981}, {'end': 14410.922, 'text': 'so if a is larger than 20, then you print this.', 'start': 14405.739, 'duration': 5.183}, {'end': 14414.264, 'text': 'if a is larger than 30, then this, for example.', 'start': 14410.922, 'duration': 3.342}, {'end': 14440.128, 'text': 'and let me write the else part here, else print, uh, less or equal to 30, and we can print inside the nested, inside the else part of nested.', 'start': 14414.264, 'duration': 25.864}], 'summary': 'Demonstrating use of if-else conditions and nested if-else with multiple examples.', 'duration': 44.534, 'max_score': 14395.594, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI14395594.jpg'}, {'end': 14660.006, 'src': 'embed', 'start': 14626.722, 'weight': 4, 'content': [{'end': 14631.285, 'text': 'Sometimes you may get confused whether this else belongs to this if or that if.', 'start': 14626.722, 'duration': 4.563}, {'end': 14635.889, 'text': 'Well, the indentation defines this else belong to what.', 'start': 14632.146, 'duration': 3.743}, {'end': 14642.512, 'text': 'OK, I end this control flow indentation here.', 'start': 14637.228, 'duration': 5.284}, {'end': 14650.219, 'text': 'So from next video, we are jumping toward loops.', 'start': 14643.313, 'duration': 6.906}, {'end': 14660.006, 'text': "But before loops, I just want to I just want to write a lengthy program in if else if they're combinations.", 'start': 14651.159, 'duration': 8.847}], 'summary': 'Indentation defines control flow; next video focuses on loops.', 'duration': 33.284, 'max_score': 14626.722, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI14626722.jpg'}], 'start': 13548.684, 'title': 'Python if conditions', 'summary': 'Explores boolean variables, comparisons, nested if structures, and indentation in python. it showcases the use of ands, ors, if-elif-else structures, and nested if statements. the content presents a program-solving task and emphasizes the importance of proper indentation for defining blocks and structures.', 'chapters': [{'end': 13631.84, 'start': 13548.684, 'title': 'Boolean variables and comparisons', 'summary': 'Demonstrates the power of comparisons and combining boolean variables using ands and ors to create conditional statements in python, showcasing an example with a and b grades.', 'duration': 83.156, 'highlights': ['The chapter focuses on demonstrating the power of comparisons and combining Boolean variables using ANDs and ORs in Python.', 'The example showcases using conditional statements to determine A and B grades based on specified conditions.', 'The importance of writing parentheses for readability in code is emphasized.']}, {'end': 14067.006, 'start': 13631.84, 'title': 'Nested if structure', 'summary': 'Demonstrates the implementation of if-elif-else structures and nested if conditions, showcasing the use of multiple comparisons and simulating an else statement using elif. it also introduces the concept of nested if conditions, highlighting the ability to create deep structures based on logic.', 'duration': 435.166, 'highlights': ['The chapter demonstrates the implementation of if-elif-else structures and nested if conditions.', 'It showcases the use of multiple comparisons and simulating an else statement using elif.', 'It introduces the concept of nested if conditions, highlighting the ability to create deep structures based on logic.']}, {'end': 14562.159, 'start': 14067.006, 'title': 'Understanding nested if statements', 'summary': "Explains the concept of nested if statements, emphasizing the importance of indentation and illustrating the execution flow with examples, demonstrating how conditions determine the program's output.", 'duration': 495.153, 'highlights': ['Nested if statements explained', 'Importance of indentation in defining statement placement', 'Example of program execution with nested if statements']}, {'end': 15006.065, 'start': 14562.159, 'title': 'Python indentation and if conditions', 'summary': 'Discusses the importance of indentation in python, emphasizing the significance of proper indentation for defining blocks and structures. it also presents a program-solving task, requiring the user to find the integer portion of a floating-point number and determine if it is even or odd.', 'duration': 443.906, 'highlights': ['The chapter emphasizes the significance of proper indentation in Python for defining blocks and structures, highlighting the importance of indentation over using curly brackets as in other languages like C++.', 'The program-solving task requires the user to find the integer portion of a floating-point number and determine if it is even or odd, presenting various scenarios for different user inputs and emphasizing the need for checking according to the input.', 'The chapter introduces the concept of comments in Python, distinguishing between single-line and multi-line comments and their usage for code description and problem statement.']}], 'duration': 1457.381, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI13548684.jpg', 'highlights': ['The program-solving task requires finding the integer portion of a floating-point number and determining if it is even or odd, presenting various scenarios for different user inputs and emphasizing the need for checking according to the input.', 'The chapter emphasizes the significance of proper indentation in Python for defining blocks and structures, highlighting the importance of indentation over using curly brackets as in other languages like C++.', 'The chapter demonstrates the implementation of if-elif-else structures and nested if conditions, showcasing the use of multiple comparisons and simulating an else statement using elif.', 'The chapter focuses on demonstrating the power of comparisons and combining Boolean variables using ANDs and ORs in Python, with an example showcasing using conditional statements to determine A and B grades based on specified conditions.', 'The importance of writing parentheses for readability in code is emphasized.', 'Nested if statements explained, highlighting the importance of indentation in defining statement placement and providing an example of program execution with nested if statements.', 'The chapter introduces the concept of comments in Python, distinguishing between single-line and multi-line comments and their usage for code description and problem statement.']}, {'end': 16536.023, 'segs': [{'end': 15045.316, 'src': 'embed', 'start': 15007.35, 'weight': 0, 'content': [{'end': 15009.351, 'text': 'else do what?', 'start': 15007.35, 'duration': 2.001}, {'end': 15011.733, 'text': "so let's write this structure first.", 'start': 15009.351, 'duration': 2.382}, {'end': 15018.997, 'text': 'if X is positive, then what we have to do, and if X is negative, then what we have to do.', 'start': 15011.733, 'duration': 7.264}, {'end': 15021.598, 'text': 'so if X is positive, then what we do?', 'start': 15018.997, 'duration': 2.601}, {'end': 15029.658, 'text': 'we we just So.', 'start': 15021.598, 'duration': 8.06}, {'end': 15030.158, 'text': 'what should we do??', 'start': 15029.658, 'duration': 0.5}, {'end': 15031.239, 'text': "I'm just stuck here.", 'start': 15030.458, 'duration': 0.781}, {'end': 15043.834, 'text': "How can we extract the decimal portion, the portion without this particular thing? How can we extract that? That's tricky.", 'start': 15031.94, 'duration': 11.894}, {'end': 15045.316, 'text': "That's kind of tricky.", 'start': 15044.114, 'duration': 1.202}], 'summary': 'Discussion on handling positive and negative values, as well as extracting decimal portions.', 'duration': 37.966, 'max_score': 15007.35, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI15007350.jpg'}, {'end': 15334.34, 'src': 'embed', 'start': 15299.093, 'weight': 5, 'content': [{'end': 15302.636, 'text': 'But when we will round, we will get 46 and 46 minus 1.', 'start': 15299.093, 'duration': 3.543}, {'end': 15304.798, 'text': 'We will dive into this particular if condition.', 'start': 15302.636, 'duration': 2.162}, {'end': 15305.238, 'text': "Let's see.", 'start': 15304.818, 'duration': 0.42}, {'end': 15309.102, 'text': 'Oh, the result is 45.', 'start': 15305.258, 'duration': 3.844}, {'end': 15310.283, 'text': 'We are still moving very well.', 'start': 15309.102, 'duration': 1.181}, {'end': 15312.705, 'text': "Great That's great.", 'start': 15311.203, 'duration': 1.502}, {'end': 15314.807, 'text': 'So, okay.', 'start': 15313.365, 'duration': 1.442}, {'end': 15316.808, 'text': "Let's play with it.", 'start': 15316.128, 'duration': 0.68}, {'end': 15318.169, 'text': "Let's give 0.2.", 'start': 15317.469, 'duration': 0.7}, {'end': 15319.771, 'text': 'The result should be 0.', 'start': 15318.169, 'duration': 1.602}, {'end': 15331.419, 'text': "It is 0, right? Let's run it again and give it, let's say, four.", 'start': 15319.771, 'duration': 11.648}, {'end': 15332.139, 'text': "That's it.", 'start': 15331.819, 'duration': 0.32}, {'end': 15333.42, 'text': 'The result should be four now.', 'start': 15332.38, 'duration': 1.04}, {'end': 15334.34, 'text': 'It is four.', 'start': 15333.96, 'duration': 0.38}], 'summary': 'Testing results: 46-1=45, 0.2*0=0, 0.2*4=4', 'duration': 35.247, 'max_score': 15299.093, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI15299093.jpg'}, {'end': 15878.066, 'src': 'embed', 'start': 15847.12, 'weight': 7, 'content': [{'end': 15849.621, 'text': "That's an expression that results a Boolean value.", 'start': 15847.12, 'duration': 2.501}, {'end': 15854.004, 'text': 'While this condition is true, you will stay in this block.', 'start': 15850.181, 'duration': 3.823}, {'end': 15859.569, 'text': 'and after executing whole block, once you check this condition again.', 'start': 15854.964, 'duration': 4.605}, {'end': 15864.153, 'text': 'if this condition is again true, you will dive into this block again.', 'start': 15859.569, 'duration': 4.584}, {'end': 15867.376, 'text': 'then check the condition, dive into the block, then check the condition.', 'start': 15864.153, 'duration': 3.223}, {'end': 15868.637, 'text': 'dive into the block.', 'start': 15867.376, 'duration': 1.261}, {'end': 15872.32, 'text': 'as long as this condition stays true, you stay in the block.', 'start': 15868.637, 'duration': 3.683}, {'end': 15878.066, 'text': 'you, you move inside the block once this condition is false, then you exit this while loop.', 'start': 15872.32, 'duration': 5.746}], 'summary': 'Explains the concept of a while loop, stating that it continues as long as the condition is true.', 'duration': 30.946, 'max_score': 15847.12, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI15847120.jpg'}, {'end': 16032.284, 'src': 'embed', 'start': 15989.012, 'weight': 2, 'content': [{'end': 15996.834, 'text': "So let's go to Jupyter just to get our hands on this loop, for example.", 'start': 15989.012, 'duration': 7.822}, {'end': 16002.155, 'text': "Let's say x is, again, let's say int or n.", 'start': 15997.254, 'duration': 4.901}, {'end': 16002.615, 'text': "Let's take n.", 'start': 16002.155, 'duration': 0.46}, {'end': 16010.557, 'text': 'n is int input.', 'start': 16005.015, 'duration': 5.542}, {'end': 16013.618, 'text': 'let me make this a little bigger.', 'start': 16010.557, 'duration': 3.061}, {'end': 16020.08, 'text': "just to, let's say that input and input is a number.", 'start': 16013.618, 'duration': 6.462}, {'end': 16021.56, 'text': "let's say n.", 'start': 16020.08, 'duration': 1.48}, {'end': 16024.661, 'text': 'i is your certain.', 'start': 16021.56, 'duration': 3.101}, {'end': 16032.284, 'text': "let's say, let's say one while i is smaller than n.", 'start': 16024.661, 'duration': 7.623}], 'summary': 'Demonstrating a loop in jupyter with integer input n.', 'duration': 43.272, 'max_score': 15989.012, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI15989012.jpg'}, {'end': 16131.173, 'src': 'embed', 'start': 16061.374, 'weight': 3, 'content': [{'end': 16082.358, 'text': "let's say, and then you say print, for example, this is iteration number, and then you just print i, that's the iteration number i of the loop,", 'start': 16061.374, 'duration': 20.984}, {'end': 16084.059, 'text': "that's the iteration number i.", 'start': 16082.358, 'duration': 1.701}, {'end': 16091.236, 'text': "This is just a string and that's a variable.", 'start': 16086.292, 'duration': 4.944}, {'end': 16092.717, 'text': 'Its value will be printed.', 'start': 16091.696, 'duration': 1.021}, {'end': 16096.981, 'text': 'This print function takes as many arguments as you pass.', 'start': 16093.598, 'duration': 3.383}, {'end': 16101.625, 'text': 'So you can write a comma here and continue whatever you want to print.', 'start': 16097.581, 'duration': 4.044}, {'end': 16104.287, 'text': "That's a very flexible function.", 'start': 16102.065, 'duration': 2.222}, {'end': 16109.847, 'text': 'Okay, then what you do, you say, okay, i plus equals to 1.', 'start': 16104.927, 'duration': 4.92}, {'end': 16115.288, 'text': 'By the way, this i plus equals to 1 is the same as i equals i plus 1.', 'start': 16109.847, 'duration': 5.441}, {'end': 16120.37, 'text': 'You see, I have just commented here just to explain what this is doing.', 'start': 16115.288, 'duration': 5.082}, {'end': 16128.192, 'text': "If I just write i equals i plus 1, that is also correct in Python, but that's kind of a shorthand.", 'start': 16120.85, 'duration': 7.342}, {'end': 16131.173, 'text': "Okay, and that's it.", 'start': 16129.132, 'duration': 2.041}], 'summary': 'Demonstrates use of print function, iteration, and shorthand in python.', 'duration': 69.799, 'max_score': 16061.374, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI16061374.jpg'}, {'end': 16302.184, 'src': 'embed', 'start': 16272.272, 'weight': 6, 'content': [{'end': 16275.233, 'text': "let's say n is, let's say n is 5.", 'start': 16272.272, 'duration': 2.961}, {'end': 16276.824, 'text': 'i equals 1.', 'start': 16275.233, 'duration': 1.591}, {'end': 16278.135, 'text': '1 is less than 5.', 'start': 16276.824, 'duration': 1.311}, {'end': 16282.837, 'text': 'yes, one is not an even number.', 'start': 16278.135, 'duration': 4.702}, {'end': 16283.817, 'text': 'so go to else.', 'start': 16282.837, 'duration': 0.98}, {'end': 16289.859, 'text': 'part else means pause, which means go on and then increment i.', 'start': 16283.817, 'duration': 6.042}, {'end': 16291.66, 'text': 'this print statement is outside the loop.', 'start': 16289.859, 'duration': 1.801}, {'end': 16295.341, 'text': 'this is this is aligned with this, while this is not inside the body of the loop.', 'start': 16291.66, 'duration': 3.681}, {'end': 16299.623, 'text': 'otherwise it should have been intent indented inside.', 'start': 16295.341, 'duration': 4.282}, {'end': 16300.783, 'text': 'now i is incremented.', 'start': 16299.623, 'duration': 1.16}, {'end': 16302.184, 'text': 'i becomes two.', 'start': 16300.783, 'duration': 1.401}], 'summary': 'Loop through n=5, check odd numbers, print i=2', 'duration': 29.912, 'max_score': 16272.272, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI16272272.jpg'}], 'start': 15007.35, 'title': 'Extracting decimal and integer portion, if conditions, and loops', 'summary': 'Discusses extracting decimal and integer portions using the round function, handling negative numbers, and the concept of if conditions and loops. it emphasizes the functionality of while loops, if conditions within loops, and the impact of break and continue statements on loop iterations.', 'chapters': [{'end': 15250.971, 'start': 15007.35, 'title': 'Extracting decimal and integer portion', 'summary': 'Discusses extracting the decimal and integer portions of a given positive number using the round function and conditional statements, aiming to determine the integer portion by subtracting 1 from the rounded value if it exceeds the original number.', 'duration': 243.621, 'highlights': ['The chapter discusses using the round function and conditional statements to determine the integer portion by subtracting 1 from the rounded value if it exceeds the original number.', 'It explores scenarios where the rounded value is larger than the original number and how to accurately derive the integer portion in such cases.', 'The approach involves checking if the rounded value is larger than the original number and subtracting one to obtain the integer portion, otherwise, considering the rounded value itself as the integer portion.']}, {'end': 15868.637, 'start': 15250.971, 'title': 'Understanding if conditions and loops', 'summary': 'Discusses the working of the round function to extract integer portions, handling negative numbers, and then delves into the concept of if conditions and the repetitive nature of loops, showcasing how to print numbers up to a given input and the utility of loops in reducing code repetition.', 'duration': 617.666, 'highlights': ['The round function extracts the integer portion of a number and handles positive and negative numbers, as demonstrated by examples such as 25.3 yielding 25 and -9.5 yielding -9.', 'The discussion progresses to handling negative numbers and extracting the integer portion, with examples and explanations of the logic involved.', 'The chapter then demonstrates the use of if conditions to determine if an integer portion is even or odd, providing examples like 22.6 being even and -87.3 being odd.', 'The chapter concludes with an introduction to loops, explaining their function and showcasing an example of using a while loop to print numbers up to a given input, emphasizing the reduction in code repetition.']}, {'end': 16536.023, 'start': 15868.637, 'title': 'Understanding while loops and control statements', 'summary': 'Explains the functionality of while loops, with specific examples and explanations, emphasizing the significance of loops in repetitive structures and interesting problems. it also delves into the usage of if conditions within the loop and the impact of break and continue statements on loop iterations.', 'duration': 667.386, 'highlights': ['While loop functionality and significance in repetitive structures and interesting problems', 'Demonstration of if conditions within the loop for making specific decisions at each iteration', 'Explanation of the impact of break and continue statements on loop behavior']}], 'duration': 1528.673, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI15007350.jpg', 'highlights': ['The round function extracts the integer portion of a number and handles positive and negative numbers, as demonstrated by examples such as 25.3 yielding 25 and -9.5 yielding -9.', 'The chapter discusses using the round function and conditional statements to determine the integer portion by subtracting 1 from the rounded value if it exceeds the original number.', 'The approach involves checking if the rounded value is larger than the original number and subtracting one to obtain the integer portion, otherwise, considering the rounded value itself as the integer portion.', 'The chapter then demonstrates the use of if conditions to determine if an integer portion is even or odd, providing examples like 22.6 being even and -87.3 being odd.', 'Demonstration of if conditions within the loop for making specific decisions at each iteration', 'The discussion progresses to handling negative numbers and extracting the integer portion, with examples and explanations of the logic involved.', 'While loop functionality and significance in repetitive structures and interesting problems', 'Explanation of the impact of break and continue statements on loop behavior', 'The chapter concludes with an introduction to loops, explaining their function and showcasing an example of using a while loop to print numbers up to a given input, emphasizing the reduction in code repetition.', 'It explores scenarios where the rounded value is larger than the original number and how to accurately derive the integer portion in such cases.']}, {'end': 17962.722, 'segs': [{'end': 17734.871, 'src': 'embed', 'start': 17709.985, 'weight': 0, 'content': [{'end': 17716.111, 'text': 'The break will execute, which means the loop should have one more iteration, but the break just disrupt that.', 'start': 17709.985, 'duration': 6.126}, {'end': 17724.02, 'text': 'one more iteration that should be there, because the loop could not complete its iteration due to this certain condition.', 'start': 17716.952, 'duration': 7.068}, {'end': 17729.405, 'text': 'this else part of the loop will not execute and you will go directly outside this loop.', 'start': 17724.02, 'duration': 5.385}, {'end': 17732.308, 'text': "so let's run this code and see the result.", 'start': 17729.405, 'duration': 2.903}, {'end': 17734.871, 'text': 'so you can see this apple 4.9 outside the loop.', 'start': 17732.308, 'duration': 2.563}], 'summary': "The loop should have one more iteration, but the break disrupts it, resulting in 'apple 4.9' outside the loop.", 'duration': 24.886, 'max_score': 17709.985, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI17709985.jpg'}, {'end': 17788.552, 'src': 'embed', 'start': 17763.67, 'weight': 2, 'content': [{'end': 17771.574, 'text': 'because you may confuse this else with the else of if condition and you may think something else and the program behave in a different way.', 'start': 17763.67, 'duration': 7.904}, {'end': 17777.678, 'text': 'So either way, if you want to use else, else for a for loop is there in Python.', 'start': 17772.275, 'duration': 5.403}, {'end': 17782.248, 'text': 'Okay, just one more example of for loop.', 'start': 17779.326, 'duration': 2.922}, {'end': 17785.31, 'text': 'And here we use dictionary.', 'start': 17782.688, 'duration': 2.622}, {'end': 17788.552, 'text': "I'm introducing some data structures here just for fun.", 'start': 17785.93, 'duration': 2.622}], 'summary': "Python allows using 'else' for 'for' loops, including dictionaries.", 'duration': 24.882, 'max_score': 17763.67, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI17763670.jpg'}, {'end': 17866.178, 'src': 'embed', 'start': 17841.222, 'weight': 5, 'content': [{'end': 17849.145, 'text': "All I'm showing you that this for loop is very, very handy of iterating over different data structures and a lot of data and stuff.", 'start': 17841.222, 'duration': 7.923}, {'end': 17858.672, 'text': 'whereas while loop is more handy in checking the conditions and stuff, although you can do all the stuff using while loop.', 'start': 17851.587, 'duration': 7.085}, {'end': 17866.178, 'text': 'you can all this stuff using for loop, but one is better over the other in certain, in certain situations.', 'start': 17858.672, 'duration': 7.506}], 'summary': 'For loop is handy for iterating over data, while loop is better for checking conditions.', 'duration': 24.956, 'max_score': 17841.222, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI17841222.jpg'}, {'end': 17962.722, 'src': 'embed', 'start': 17909.853, 'weight': 3, 'content': [{'end': 17915.038, 'text': 'So now you can see the key is A, the value is 10, the key is B, the value is minus 19,.', 'start': 17909.853, 'duration': 5.185}, {'end': 17916.899, 'text': 'the key is C, the value is ABC.', 'start': 17915.038, 'duration': 1.861}, {'end': 17926.889, 'text': 'So this for loop is really really handy in iterating over a lot of data structures and stuff, although it has other applications as well,', 'start': 17917.96, 'duration': 8.929}, {'end': 17928.17, 'text': 'but this is handy.', 'start': 17926.889, 'duration': 1.281}, {'end': 17929.862, 'text': 'OK, great.', 'start': 17929.241, 'duration': 0.621}, {'end': 17934.545, 'text': "So that's about loops, for loops and while loops.", 'start': 17931.062, 'duration': 3.483}, {'end': 17938.228, 'text': 'These are two kinds of loops in important.', 'start': 17934.645, 'duration': 3.583}, {'end': 17942.611, 'text': 'These are two important kind of loops in there in Python.', 'start': 17938.248, 'duration': 4.363}, {'end': 17950.177, 'text': 'In the next video, I will directly go to Jupyter and Jupyter Notebook and we will be practicing for this.', 'start': 17943.191, 'duration': 6.986}, {'end': 17952.838, 'text': 'for loops or while loops.', 'start': 17950.877, 'duration': 1.961}, {'end': 17957.94, 'text': 'we will be practicing the loops we will be doing actually examples of nested loops.', 'start': 17952.838, 'duration': 5.102}, {'end': 17961.321, 'text': 'we will be actually solving a problem, like we did in the if conditions.', 'start': 17957.94, 'duration': 3.381}, {'end': 17962.722, 'text': 'we solved a problem previously.', 'start': 17961.321, 'duration': 1.401}], 'summary': 'Iterating over data with for loops and while loops in python, with a focus on practicing and solving problems.', 'duration': 52.869, 'max_score': 17909.853, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI17909853.jpg'}], 'start': 16536.804, 'title': 'Python loops and control statements', 'summary': "Covers the application of 'break' and 'continue' statements, lists, for loops, and else clause in python. it includes examples and detailed explanations, with a mention of the impact on loop execution and scenarios where the else part of the loop will not execute.", 'chapters': [{'end': 16960.813, 'start': 16536.804, 'title': 'Looping and control statements', 'summary': "Covers the application of 'break' and 'continue' statements in python loops, demonstrating their functionality and impact on loop execution, with a brief mention of the upcoming 'for' loop explanation.", 'duration': 424.009, 'highlights': ["The use of 'break' statement to exit a loop when a condition is met, as demonstrated with an example of breaking a while loop when i is divisible by 9, resulting in no further iterations and immediate loop termination.", "Demonstration of 'continue' statement's functionality to skip subsequent code execution and move to the next iteration when a condition is met, illustrated by an example where code after 'continue' is not executed if i is not divisible by 9.", "Introduction of the upcoming explanation on 'for' loop, highlighting its similarity with the 'while' loop and the mention of exploring its details and applications in the next video."]}, {'end': 17293.65, 'start': 16960.813, 'title': 'Lists and for loop in python', 'summary': 'Covers the concept of lists and for loops in python, including indexing, appending, and iterating through a range, with examples and detailed explanations.', 'duration': 332.837, 'highlights': ['The chapter covers the concept of lists and for loops in Python', 'Iterating through a range of numbers from 0 to 9', 'Appending elements to a list using for loop', 'Indexing and accessing elements in a list']}, {'end': 17507.931, 'start': 17293.79, 'title': 'For loop and else clause in python', 'summary': "Introduces the for loop in python, demonstrating how to iterate over a range and explaining the else clause's purpose, with an example of iterating over a set and printing its elements.", 'duration': 214.141, 'highlights': ['The else part in Python for loop will only execute if the for loop completes its iterations.', 'Demonstrating iterating over a set in Python using a for loop and printing its elements.', 'Introduction to for loop in Python and iterating over a range to populate a list.']}, {'end': 17962.722, 'start': 17507.931, 'title': 'Python loops and examples', 'summary': 'Explains the concept of loops in python, covering for loops and while loops and their applications with examples. it also highlights the scenarios where the else part of the loop will not execute, and the usage of loops with different data structures like sets and dictionaries.', 'duration': 454.791, 'highlights': ['The chapter explains the concept of loops in Python, covering for loops and while loops and their applications with examples.', 'It also highlights the scenarios where the else part of the loop will not execute.', 'The usage of loops with different data structures like sets and dictionaries is demonstrated.']}], 'duration': 1425.918, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI16536804.jpg', 'highlights': ["The use of 'break' statement to exit a loop when a condition is met, illustrated by breaking a while loop when i is divisible by 9.", "Demonstration of 'continue' statement's functionality to skip subsequent code execution and move to the next iteration when a condition is met.", 'The else part in Python for loop will only execute if the for loop completes its iterations.', 'The chapter covers the concept of lists and for loops in Python.', 'Iterating through a range of numbers from 0 to 9.', "Introduction of the upcoming explanation on 'for' loop, highlighting its similarity with the 'while' loop."]}, {'end': 20596.638, 'segs': [{'end': 18314.271, 'src': 'embed', 'start': 18281.107, 'weight': 1, 'content': [{'end': 18287.732, 'text': 'Okay, now we have written a kind of a code block that helps us finding out the minimum value.', 'start': 18281.107, 'duration': 6.625}, {'end': 18303.725, 'text': 'How can we actually do, how can we actually, so the basic logic is you find the minimum value and swap that value with the very first value.', 'start': 18289.286, 'duration': 14.439}, {'end': 18305.107, 'text': 'Okay, great.', 'start': 18304.386, 'duration': 0.721}, {'end': 18307.709, 'text': 'and then move the loop.', 'start': 18305.649, 'duration': 2.06}, {'end': 18314.271, 'text': 'Next time find out the minimum value from the remaining list and swap that minimum value with the second value.', 'start': 18307.97, 'duration': 6.301}], 'summary': 'Code block finds & swaps minimum values in a list', 'duration': 33.164, 'max_score': 18281.107, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI18281107.jpg'}, {'end': 18911.972, 'src': 'embed', 'start': 18863.538, 'weight': 0, 'content': [{'end': 18869.981, 'text': 'But the need is we want to perform this task whenever we need and we do not write to code this again and again.', 'start': 18863.538, 'duration': 6.443}, {'end': 18879.165, 'text': 'We do not want to write the same lines of codes again and again and again and again in our program.', 'start': 18870.041, 'duration': 9.124}, {'end': 18886.109, 'text': 'Just write this particular lines of code once define a function, just like a task.', 'start': 18879.585, 'duration': 6.524}, {'end': 18888.41, 'text': 'whenever you need to perform that task,', 'start': 18886.109, 'duration': 2.301}, {'end': 18895.013, 'text': 'just call the heading or the name of the function and the whole task under that function will execute functions.', 'start': 18888.41, 'duration': 6.603}, {'end': 18898.535, 'text': 'in almost all programming languages they do that even in mathematics.', 'start': 18895.013, 'duration': 3.522}, {'end': 18900.937, 'text': 'they do that in in python.', 'start': 18898.535, 'duration': 2.402}, {'end': 18903.458, 'text': 'the syntax of defining function is you?', 'start': 18900.937, 'duration': 2.521}, {'end': 18911.972, 'text': 'if you want to define a function, you have to first start with d e f, meaning definition or defining.', 'start': 18903.458, 'duration': 8.514}], 'summary': 'Avoid repetitive coding by defining and calling functions in various programming languages, including python.', 'duration': 48.434, 'max_score': 18863.538, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI18863538.jpg'}, {'end': 19530.712, 'src': 'embed', 'start': 19504.176, 'weight': 3, 'content': [{'end': 19508.559, 'text': 'Several times, we will be accessing functions that other people have written in their libraries.', 'start': 19504.176, 'duration': 4.383}, {'end': 19511.02, 'text': 'And we need to know what those functions are doing.', 'start': 19509.299, 'duration': 1.721}, {'end': 19515.363, 'text': 'So document string is one very, very healthy way of describing our function.', 'start': 19511.04, 'duration': 4.323}, {'end': 19520.326, 'text': 'And I will recommend to make your habit writing document strings every time you write a function.', 'start': 19515.583, 'duration': 4.743}, {'end': 19528.831, 'text': 'I was telling you that if you write a double question mark, then it will not only pull the document string for you,', 'start': 19521.987, 'duration': 6.844}, {'end': 19530.712, 'text': 'it will pull the whole implementation as well.', 'start': 19528.831, 'duration': 1.881}], 'summary': 'Documenting functions with strings is crucial for understanding code and accessing external libraries. using double question marks retrieves both the document string and implementation.', 'duration': 26.536, 'max_score': 19504.176, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI19504176.jpg'}, {'end': 20425.804, 'src': 'heatmap', 'start': 19976.201, 'weight': 1, 'content': [{'end': 19995.708, 'text': 'supplied by the user or prints that message is not in the form of string.', 'start': 19976.201, 'duration': 19.507}, {'end': 19999.312, 'text': "Wow Don't worry, we have to see the strings in detail.", 'start': 19996.529, 'duration': 2.783}, {'end': 20005.759, 'text': 'We will see the sprint function in detail as well because the sprint has a lot to do with strings.', 'start': 20000.373, 'duration': 5.386}, {'end': 20010.021, 'text': "So just for now, I mean, that's our function, print message.", 'start': 20007.3, 'duration': 2.721}, {'end': 20020.643, 'text': "Let's say if the message is of string type, this string does not, this should be simply STR, this should not be that, is instance take like this.", 'start': 20010.461, 'duration': 10.182}, {'end': 20024.724, 'text': 'Your input argument is not a string, here is what you have supplied.', 'start': 20021.703, 'duration': 3.021}, {'end': 20027.964, 'text': 'Here is what you have.', 'start': 20026.064, 'duration': 1.9}, {'end': 20049.867, 'text': 'so here we can say here is the type of what you have supplied, and then we can just print the type and type of msg.', 'start': 20027.964, 'duration': 21.903}, {'end': 20051.169, 'text': 'so the the.', 'start': 20049.867, 'duration': 1.302}, {'end': 20058.032, 'text': 'the goal here is to just write a function that prints a message, if that message is in plain string form.', 'start': 20051.169, 'duration': 6.863}, {'end': 20065.354, 'text': 'If it is not a string, then it prints that, okay, whatever you have sent is not a string.', 'start': 20058.732, 'duration': 6.622}, {'end': 20067.274, 'text': 'It is not a proper message in string form.', 'start': 20065.394, 'duration': 1.88}, {'end': 20070.615, 'text': "Let's say this print message function receives a string.", 'start': 20067.294, 'duration': 3.321}, {'end': 20073.495, 'text': "Let's say that's our logic or something.", 'start': 20070.695, 'duration': 2.8}, {'end': 20074.836, 'text': "So let's run this.", 'start': 20074.036, 'duration': 0.8}, {'end': 20077.616, 'text': "First of all, let's see what it does.", 'start': 20076.096, 'duration': 1.52}, {'end': 20079.817, 'text': 'Help print.', 'start': 20077.957, 'duration': 1.86}, {'end': 20087.929, 'text': 'message. so the function prints the message supplied by the user.', 'start': 20081.266, 'duration': 6.663}, {'end': 20098.575, 'text': 'we can access the same help by question mark if we want, and it gives us the document string.', 'start': 20087.929, 'duration': 10.646}, {'end': 20106.159, 'text': 'if, however, we want the implementation as well, then we write a double quote and the implementation is also available.', 'start': 20098.575, 'duration': 7.584}, {'end': 20109.82, 'text': 'wow, great, python is really great.', 'start': 20106.159, 'duration': 3.661}, {'end': 20111.081, 'text': "okay, let's call this function.", 'start': 20109.82, 'duration': 1.261}, {'end': 20114.546, 'text': "Yeah, let's call this function.", 'start': 20113.025, 'duration': 1.521}, {'end': 20123.087, 'text': 'Print message and whatever you want to print.', 'start': 20118.466, 'duration': 4.621}, {'end': 20127.248, 'text': "Let's say this is the message.", 'start': 20123.127, 'duration': 4.121}, {'end': 20129.589, 'text': 'This is the message.', 'start': 20128.909, 'duration': 0.68}, {'end': 20130.589, 'text': "Let's say you want to print this.", 'start': 20129.629, 'duration': 0.96}, {'end': 20133.19, 'text': "And this is the message that's printed.", 'start': 20131.669, 'duration': 1.521}, {'end': 20141.335, 'text': "Okay, now let's say you call this function again sometime and you supply 23.", 'start': 20134.01, 'duration': 7.325}, {'end': 20147.957, 'text': 'and it will say your input argument is not a string here is the type of what you have supplied.', 'start': 20141.335, 'duration': 6.622}, {'end': 20149.338, 'text': "it's an integer type.", 'start': 20147.957, 'duration': 1.381}, {'end': 20153.519, 'text': 'right, um, you can, you can have, you can have.', 'start': 20149.338, 'duration': 4.181}, {'end': 20155.26, 'text': 'you can call this function in the following way.', 'start': 20153.519, 'duration': 1.741}, {'end': 20166.323, 'text': "let's say you define a variable y and the variable y contains hello, hello there.", 'start': 20155.26, 'duration': 11.063}, {'end': 20167.684, 'text': "let's say that's your, uh.", 'start': 20166.323, 'duration': 1.361}, {'end': 20175.667, 'text': 'And then you call this function on y.', 'start': 20168.263, 'duration': 7.404}, {'end': 20179.47, 'text': 'And it will print hello there because y is also a string.', 'start': 20175.667, 'duration': 3.803}, {'end': 20187.714, 'text': "Great, So that's how you can pass different arguments and instruct the function.", 'start': 20180.37, 'duration': 7.344}, {'end': 20193.257, 'text': 'how should it behave without actually writing the whole logic of the task again and again?', 'start': 20187.714, 'duration': 5.543}, {'end': 20195.459, 'text': 'You have written all the logic once.', 'start': 20193.298, 'duration': 2.161}, {'end': 20198.96, 'text': 'Actually, this is actually the logic starts from here.', 'start': 20196.099, 'duration': 2.861}, {'end': 20200.341, 'text': "That's what the task is.", 'start': 20199.48, 'duration': 0.861}, {'end': 20202.261, 'text': "That's what the task you want to perform.", 'start': 20200.681, 'duration': 1.58}, {'end': 20206.543, 'text': 'And you need not write this again and again whenever you need this kind of stuff.', 'start': 20203.002, 'duration': 3.541}, {'end': 20211.365, 'text': 'You just call that function splite arguments and it will behave accordingly you want.', 'start': 20207.003, 'duration': 4.362}, {'end': 20219.7, 'text': 'Great So you might be thinking that a function only receives one argument.', 'start': 20212.385, 'duration': 7.315}, {'end': 20225.883, 'text': 'Maybe we want to supply more than one argument, maybe two arguments, maybe three, maybe four, maybe five.', 'start': 20220.161, 'duration': 5.722}, {'end': 20235.947, 'text': 'And maybe we want to supply several arguments and we want to do some task based on the values of those arguments or those variables.', 'start': 20226.123, 'duration': 9.824}, {'end': 20241.71, 'text': "So in the next video, I'm going to show you multiple arguments.", 'start': 20236.627, 'duration': 5.083}, {'end': 20244.279, 'text': 'Okay Hope to see you in the next video.', 'start': 20242.39, 'duration': 1.889}, {'end': 20251.109, 'text': 'So in the previous video we saw we can define a function and we can supply input argument to it.', 'start': 20244.739, 'duration': 6.37}, {'end': 20256.737, 'text': 'And in this video we are going to see that we can actually send more than one arguments.', 'start': 20251.79, 'duration': 4.947}, {'end': 20258.318, 'text': 'to the function.', 'start': 20257.577, 'duration': 0.741}, {'end': 20259.919, 'text': 'These arguments are just variables.', 'start': 20258.358, 'duration': 1.561}, {'end': 20261.32, 'text': 'These are just variables.', 'start': 20260.36, 'duration': 0.96}, {'end': 20268.567, 'text': 'Whatever value we will supply to these dynamically because Python is dynamically typed, dynamically their type will be defined.', 'start': 20261.661, 'duration': 6.906}, {'end': 20274.652, 'text': 'And for example, here we have supplied just two variables and we just printed them.', 'start': 20269.688, 'duration': 4.964}, {'end': 20284.202, 'text': 'But based on supplying more than one input arguments and based on what logic we are going to perform, we can do anything.', 'start': 20275.373, 'duration': 8.829}, {'end': 20285.183, 'text': 'We can do anything.', 'start': 20284.502, 'duration': 0.681}, {'end': 20293.851, 'text': 'So yes, Python allows us to supply multiple input arguments to a function.', 'start': 20286.364, 'duration': 7.487}, {'end': 20301.943, 'text': 'and we can just perform all the tasks according to whatever logic we are going to do with that.', 'start': 20295.333, 'duration': 6.61}, {'end': 20311.869, 'text': "So let's go to our friend Jupyter Notebook and see an example of a function with multiple input arguments.", 'start': 20302.624, 'duration': 9.245}, {'end': 20324.633, 'text': "Let's say the function, we define a function, let's say, myPower, let's say, myPower, myPower, let's say.", 'start': 20312.429, 'duration': 12.204}, {'end': 20329.094, 'text': "You remember there is a pow function in Python, that's a built-in function.", 'start': 20324.953, 'duration': 4.141}, {'end': 20331.915, 'text': "I'm going to write my own function, let's say.", 'start': 20329.674, 'duration': 2.241}, {'end': 20333.736, 'text': 'It contains a and b.', 'start': 20332.755, 'duration': 0.981}, {'end': 20358.399, 'text': 'well, document string, my, this function computes power just like built built-in power function.', 'start': 20336.577, 'duration': 21.822}, {'end': 20360.862, 'text': "great, that's the document string.", 'start': 20358.399, 'duration': 2.463}, {'end': 20365.947, 'text': 'okay, uh, now what we want to do is we want to print?', 'start': 20360.862, 'duration': 5.085}, {'end': 20373.155, 'text': "um, okay, let's, let's, let's create another variable c that is a power b.", 'start': 20365.947, 'duration': 7.208}, {'end': 20376.819, 'text': 'okay, then we print this c and we are done.', 'start': 20373.155, 'duration': 3.664}, {'end': 20378.782, 'text': "Let's say that's our goal.", 'start': 20377.881, 'duration': 0.901}, {'end': 20387.908, 'text': 'So we register that function by just pressing the shift enter in Jupyter Notebook.', 'start': 20379.602, 'duration': 8.306}, {'end': 20393.432, 'text': 'And now we check what this function does.', 'start': 20388.409, 'duration': 5.023}, {'end': 20398.456, 'text': 'Well, this function computes power just like built-in power function.', 'start': 20394.333, 'duration': 4.123}, {'end': 20405.681, 'text': "Okay, just to remind you again and again the importance of document string, I'm writing this again and again.", 'start': 20399.056, 'duration': 6.625}, {'end': 20406.762, 'text': "Let's run this function.", 'start': 20405.721, 'duration': 1.041}, {'end': 20412.521, 'text': "my power, let's say three, raised to the power.", 'start': 20407.64, 'duration': 4.881}, {'end': 20416.122, 'text': 'four. i want this, so the result is 81.', 'start': 20412.521, 'duration': 3.601}, {'end': 20417.802, 'text': 'oh my god.', 'start': 20416.122, 'duration': 1.68}, {'end': 20425.804, 'text': "so whenever, by the way, if you don't have pow function with you although you have, um, you can you can create your function,", 'start': 20417.802, 'duration': 8.002}], 'summary': 'The transcript covers creating a function to print a message if it is a string, and defining a function with multiple input arguments for computing power.', 'duration': 449.603, 'max_score': 19976.201, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI19976201.jpg'}], 'start': 17962.722, 'title': 'Functions and sorting list', 'summary': 'Covers sorting a list of numbers, nested loops, and if conditions, using functions for reusable code, function definition, documentation, and behavior with practical examples and python usage.', 'chapters': [{'end': 18547.251, 'start': 17962.722, 'title': 'Sorting list problem', 'summary': 'Discusses the logic and code implementation for sorting a list of numbers in minimum to maximum order, finding the minimum value from the list, and swapping it with the first value to achieve a sorted order, with an example of finding the minimum value and its index, and progressively swapping minimum values with the remaining list items.', 'duration': 584.529, 'highlights': ['The logic of finding the minimum value and swapping it with the first value to achieve a sorted order is discussed, with a demonstration of code implementation in Python.', 'An example of finding the minimum value and its index from a list is provided, along with the code to print the minimum value and its index position.', 'The process of progressively finding the minimum value and swapping it with the first value for the remaining list items is explained, with a demonstration of code implementation using a loop in Python.']}, {'end': 18738.949, 'start': 18547.491, 'title': 'Nested loops and if conditions', 'summary': 'Introduces nested loops and if conditions, demonstrating the sorting of a list, identifying coding errors, and emphasizing the importance of mastering these structures for problem solving and programming. the upcoming video will focus on functions in python.', 'duration': 191.458, 'highlights': ['The chapter demonstrates the sorting of a list using nested loops and if conditions, emphasizing the importance of mastering these structures for problem solving and programming.', 'The instructor identifies coding errors, such as missing colons, and emphasizes the need for meticulous coding practices to achieve correct results.', 'The upcoming video will focus on functions in Python, introducing the concept of writing custom functions and highlighting their importance in programming.']}, {'end': 19034.537, 'start': 18739.77, 'title': 'Using functions for reusable code', 'summary': 'Explains the concept of defining and using functions to execute tasks automatically, enabling the reuse of code, and emphasizes the importance of descriptive function names and code organization.', 'duration': 294.767, 'highlights': ['The need for defining functions to avoid writing the same lines of code repeatedly is emphasized, highlighting the efficient reuse of code and the avoidance of redundancy.', 'The importance of using descriptive function names to make the code readable and manageable is stressed, underlining the significance of clear naming conventions in programming.', "The process of defining a function in Python is outlined, including the syntax and organization, emphasizing the use of 'def' to start the function definition and the significance of proper indentation for the function body.", 'The functionality of functions in executing tasks automatically whenever called is explained, demonstrating the capability of functions to contain a variety of coding, such as if conditions and loops, for efficient code execution and reuse.']}, {'end': 19630.554, 'start': 19035.217, 'title': 'Function definition and documentation', 'summary': 'Covers the definition of functions in python, highlighting the process of defining, registering, and calling a function, as well as the significance of documenting functions using docstrings and accessing their implementation and descriptions. it also emphasizes the benefits of using functions for managing and debugging tasks, with a recommendation to write docstrings for all functions.', 'duration': 595.337, 'highlights': ['Python maintains a symbol table containing variables and function information, allowing the registration of a function by running the cell, making it available for future calls.', 'The process of defining a function involves writing the function name, its syntax, and the body of the function, which can be called repeatedly for performing tasks, providing managing and debugging power, as well as a modular approach.', "The importance of documenting functions using docstrings is emphasized, with the docstring serving as a non-executable description available for assistance and understanding the function's purpose and code.", "Accessing a function's docstring and implementation using a question mark and pressing Shift, Enter allows for understanding and retrieving the function's details, particularly useful for third-party functions or built-in functions not implemented in Python.", 'Recommendation to develop the habit of writing docstrings for all functions to facilitate understanding and usage, and the indication that some functions are implemented in languages like C, making their code inaccessible.', 'The versatility of Python to integrate multiple languages, such as C, for certain functions, providing flexibility in language usage within Python.']}, {'end': 20596.638, 'start': 19630.554, 'title': 'Function arguments and behavior', 'summary': 'Discusses the importance of document strings, the dynamic behavior of functions based on input arguments, and the ability to supply multiple arguments to a function, with practical examples and python usage.', 'duration': 966.084, 'highlights': ["The function's document string provides crucial information about the function's behavior and usage, aiding in understanding how to use the function and its purpose.", 'Functions can exhibit dynamic behavior based on input arguments, allowing them to perform various tasks based on the supplied arguments, enhancing their versatility and reusability.', 'Python supports the ability to supply multiple input arguments to a function, enabling the execution of diverse tasks based on the logic defined for the input arguments.']}], 'duration': 2633.916, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI17962722.jpg', 'highlights': ["The process of defining a function in Python is outlined, including the syntax and organization, emphasizing the use of 'def' to start the function definition and the significance of proper indentation for the function body.", 'The logic of finding the minimum value and swapping it with the first value to achieve a sorted order is discussed, with a demonstration of code implementation in Python.', 'The need for defining functions to avoid writing the same lines of code repeatedly is emphasized, highlighting the efficient reuse of code and the avoidance of redundancy.', "The function's document string provides crucial information about the function's behavior and usage, aiding in understanding how to use the function and its purpose.", 'The process of defining a function involves writing the function name, its syntax, and the body of the function, which can be called repeatedly for performing tasks, providing managing and debugging power, as well as a modular approach.']}, {'end': 22040.184, 'segs': [{'end': 20694.887, 'src': 'embed', 'start': 20655.387, 'weight': 0, 'content': [{'end': 20658.529, 'text': "The function was check args, so let's check args.", 'start': 20655.387, 'duration': 3.142}, {'end': 20661.53, 'text': 'Check args.', 'start': 20659.469, 'duration': 2.061}, {'end': 20665.752, 'text': "Check args, let's say three, four, five.", 'start': 20662.41, 'duration': 3.342}, {'end': 20670.753, 'text': 'So now you have, all of them are great.', 'start': 20667.252, 'duration': 3.501}, {'end': 20676.676, 'text': "Let's say you have check args and you call this check args.", 'start': 20671.394, 'duration': 5.282}, {'end': 20690.826, 'text': "on, let's say, three, four, but this five is a string, let's say, G.", 'start': 20678.96, 'duration': 11.866}, {'end': 20692.166, 'text': "Now you'll be having an error.", 'start': 20690.826, 'duration': 1.34}, {'end': 20694.887, 'text': 'The input arguments are not of the expected types.', 'start': 20692.306, 'duration': 2.581}], 'summary': 'Function check args validates input arguments for three, four, and five, detecting errors for unexpected types.', 'duration': 39.5, 'max_score': 20655.387, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI20655387.jpg'}, {'end': 20855.922, 'src': 'embed', 'start': 20827.987, 'weight': 1, 'content': [{'end': 20833.089, 'text': 'It is important to know that the order of the input argument is really, really important.', 'start': 20827.987, 'duration': 5.102}, {'end': 20840.772, 'text': 'So whatever argument at the call time, for example, if you call this particular function, the name of the function is f.', 'start': 20834.289, 'duration': 6.483}, {'end': 20841.772, 'text': "That's not a great name.", 'start': 20840.772, 'duration': 1}, {'end': 20847.115, 'text': 'You should have a name that is descriptive, but I recommend to write good names.', 'start': 20841.913, 'duration': 5.202}, {'end': 20855.922, 'text': "Let's say this is f, that's a function, and the very first variable is c2, the second variable is c1, the third variable is c3.", 'start': 20848.076, 'duration': 7.846}], 'summary': 'Order of input arguments is crucial; recommended to use descriptive variable names.', 'duration': 27.935, 'max_score': 20827.987, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI20827987.jpg'}, {'end': 21623.051, 'src': 'embed', 'start': 21596.419, 'weight': 3, 'content': [{'end': 21604.584, 'text': 'But the problem here is how to access this variable, the value of this variable outside the function because this is completely defined inside.', 'start': 21596.419, 'duration': 8.165}, {'end': 21608.057, 'text': 'how to access that.', 'start': 21606.575, 'duration': 1.482}, {'end': 21613.943, 'text': 'well, well, there is a fix, and that fix is called the return statement.', 'start': 21608.057, 'duration': 5.886}, {'end': 21618.447, 'text': 'if you write the return statement, for example, you return this value.', 'start': 21613.943, 'duration': 4.504}, {'end': 21620.149, 'text': 'so X plus Y.', 'start': 21618.447, 'duration': 1.702}, {'end': 21621.71, 'text': 'you might have saved these values.', 'start': 21620.149, 'duration': 1.561}, {'end': 21623.051, 'text': 'you might have saved these values.', 'start': 21621.71, 'duration': 1.341}], 'summary': 'Using a return statement allows accessing variable values outside the function.', 'duration': 26.632, 'max_score': 21596.419, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI21596419.jpg'}, {'end': 21697.86, 'src': 'embed', 'start': 21672.816, 'weight': 2, 'content': [{'end': 21684.946, 'text': 'In the last video, we saw scope of a variable, particularly if a variable is defined inside a function, is it accessible outside the function?', 'start': 21672.816, 'duration': 12.13}, {'end': 21690.692, 'text': 'and if a variable is defined outside the function, Is it accessible inside the function?', 'start': 21684.946, 'duration': 5.746}, {'end': 21691.793, 'text': 'and vice versa, and so on?', 'start': 21690.692, 'duration': 1.101}, {'end': 21696.238, 'text': 'So we discussed those kind of things which is sometimes called scope of a variable.', 'start': 21691.833, 'duration': 4.405}, {'end': 21697.86, 'text': 'And further.', 'start': 21697.439, 'duration': 0.421}], 'summary': 'The video discussed the scope of variables, specifically their accessibility inside and outside functions.', 'duration': 25.044, 'max_score': 21672.816, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI21672816.jpg'}], 'start': 20596.638, 'title': 'Function best practices', 'summary': 'Covers the importance of input arguments, emphasizing expected types, number of arguments, and potential errors. it also highlights the significance of argument order, variable scope within functions, and the usage of return statements, with a practical example in jupyter notebook.', 'chapters': [{'end': 20827.307, 'start': 20596.638, 'title': 'Function input arguments', 'summary': 'Discusses the importance of defining and checking input arguments in functions, highlighting the expected types, number of arguments, and potential errors when calling functions with incorrect arguments.', 'duration': 230.669, 'highlights': ['The function check args expects three arguments and will result in an error if called with less than or more than three arguments.', 'Calling the function with arguments of the correct type but an incorrect number will also result in an error.', 'The chapter emphasizes the necessity of defining the correct number of arguments for a function, as specifying fewer or more than expected will lead to errors.', 'The next video will explore the importance of the order of input arguments and its impact on the behavior of the function.']}, {'end': 21365.461, 'start': 20827.987, 'title': 'Function argument order importance', 'summary': "Highlights the importance of the order of input arguments in a function, emphasizing the significance of defining variable names and values at the call time to maintain consistency, and discusses the significance of function variables within the function's scope.", 'duration': 537.474, 'highlights': ['The ordering of input arguments in a function is crucial, as it determines how the values are assigned to the variables, emphasizing the need for defining variable names and values at the call time to ensure consistency and avoid confusion.', 'Defining variable names and values at the call time provides flexibility in changing the order of input arguments and ensures that the values are assigned to the corresponding variables, offering a solution to the ordering issue in function calls.', "Understanding the significance of function variables within the function's scope, as they allow for the storage and processing of intermediate results, showcasing their utility in performing subsequent operations on computed values."]}, {'end': 21648.349, 'start': 21365.461, 'title': 'Scope of variables in functions', 'summary': 'Discusses the scope of variables in functions, highlighting the limitations of accessing variables defined inside the function, the accessibility of variables defined outside the function, and the role of return statements in accessing function values outside the function.', 'duration': 282.888, 'highlights': ['The scope of variables in functions is limited, as variables defined inside the function are inaccessible outside the function.', 'Variables defined outside the function are accessible inside the function, as long as they are defined before the function call.', "Local variables defined inside the function have a separate memory location and are only accessible within the function's execution.", 'The return statement allows accessing the value of a variable outside the function by returning the value when the function is called.']}, {'end': 22040.184, 'start': 21648.349, 'title': 'Scope of variables and return statement', 'summary': 'Discusses the scope of variables inside and outside functions, the usage of return statements, and the accessibility of global and local variables, with an example of defining and accessing functions and variables in jupyter notebook.', 'duration': 391.835, 'highlights': ['The chapter discusses the scope of variables inside and outside functions and the usage of return statements.', 'The example demonstrates the usage and limitations of accessing variables defined inside a function from outside the function.', 'The discussion includes the accessibility of global and local variables within functions and their behavior upon function execution.']}], 'duration': 1443.546, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI20596638.jpg', 'highlights': ['The function check args expects three arguments and will result in an error if called with less than or more than three arguments.', 'The ordering of input arguments in a function is crucial, as it determines how the values are assigned to the variables, emphasizing the need for defining variable names and values at the call time to ensure consistency and avoid confusion.', 'The scope of variables in functions is limited, as variables defined inside the function are inaccessible outside the function.', 'The return statement allows accessing the value of a variable outside the function by returning the value when the function is called.']}, {'end': 23417.864, 'segs': [{'end': 22092.903, 'src': 'embed', 'start': 22065.408, 'weight': 3, 'content': [{'end': 22076.513, 'text': 'By the way, in Python, even if any function, even if a function does not return anything, it still returns a value which is called none,', 'start': 22065.408, 'duration': 11.105}, {'end': 22077.613, 'text': 'which you can see here', 'start': 22076.513, 'duration': 1.1}, {'end': 22081.695, 'text': 'So in Python, a function always returns a value.', 'start': 22077.933, 'duration': 3.762}, {'end': 22085.637, 'text': 'If you write a return statement explicitly, it returns that.', 'start': 22082.315, 'duration': 3.322}, {'end': 22092.903, 'text': 'If you do not write return statement, when the function body finishes, it automatically returns none.', 'start': 22086.938, 'duration': 5.965}], 'summary': "Python functions always return a value, even if it's none.", 'duration': 27.495, 'max_score': 22065.408, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI22065408.jpg'}, {'end': 22303.04, 'src': 'embed', 'start': 22269.36, 'weight': 0, 'content': [{'end': 22276.443, 'text': 'Two, you can return, you can just return the control, you can just exit the function like the break in loops.', 'start': 22269.36, 'duration': 7.083}, {'end': 22281.632, 'text': 'Just one more thing, return statement can return multiple values.', 'start': 22278.271, 'duration': 3.361}, {'end': 22290.515, 'text': "For example, let's say we have defined a function, let's say j, let's say g, g.", 'start': 22281.832, 'duration': 8.683}, {'end': 22303.04, 'text': "we already have defined, we can redefine it, but let's say r is our function and we just have a equals 5, b equals 7, and d equals.", 'start': 22290.515, 'duration': 12.525}], 'summary': 'Functions can return multiple values using the return statement.', 'duration': 33.68, 'max_score': 22269.36, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI22269360.jpg'}, {'end': 22606.122, 'src': 'embed', 'start': 22554.414, 'weight': 2, 'content': [{'end': 22559.879, 'text': 'How can we have this kind of feature available?', 'start': 22554.414, 'duration': 5.465}, {'end': 22562.342, 'text': 'but the implementation is just one-time implementation?', 'start': 22559.879, 'duration': 2.463}, {'end': 22568.528, 'text': 'Well, Python have a very, very easy way of handling this arbitrary or variable number of inputs.', 'start': 22562.382, 'duration': 6.146}, {'end': 22579.079, 'text': "And the way you do that is when you are defining a function, you just write a star and then just print, let's say, one variable name, let's say args.", 'start': 22569.109, 'duration': 9.97}, {'end': 22584.124, 'text': 'And then after that, this args will act like a list.', 'start': 22580.02, 'duration': 4.104}, {'end': 22588.127, 'text': 'And I mean, it will be having a lot of properties, args.', 'start': 22585.045, 'duration': 3.082}, {'end': 22599.998, 'text': "This args has a property, this acts like a list, so all the arguments that you will send in will be received like you're receiving those in one list.", 'start': 22588.568, 'duration': 11.43}, {'end': 22606.122, 'text': 'And all the elements which are the arguments in the list, they are accessed by different indices.', 'start': 22600.538, 'duration': 5.584}], 'summary': 'Python allows easy handling of arbitrary number of inputs using a star and variable name, args, acting like a list.', 'duration': 51.708, 'max_score': 22554.414, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI22554414.jpg'}, {'end': 23088.167, 'src': 'embed', 'start': 23060.936, 'weight': 1, 'content': [{'end': 23066.079, 'text': 'you write a double star and then you receive in whatever variable name.', 'start': 23060.936, 'duration': 5.143}, {'end': 23072.061, 'text': 'And now in this double star means you are receiving a key value pair list.', 'start': 23066.699, 'duration': 5.362}, {'end': 23074.782, 'text': "It's a list of key value pairs.", 'start': 23072.461, 'duration': 2.321}, {'end': 23080.984, 'text': 'We will see that that resembles to a data structure in Python called dictionary.', 'start': 23075.882, 'duration': 5.102}, {'end': 23088.167, 'text': 'We will see dictionary later on in detail, but right now just consider that this input variable C, it contains a list of key values pairs.', 'start': 23081.364, 'duration': 6.803}], 'summary': 'Receiving a list of key-value pairs using double star in python.', 'duration': 27.231, 'max_score': 23060.936, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI23060936.jpg'}], 'start': 22040.184, 'title': 'Python functions and return values', 'summary': "Discusses python functions' return values, covering 'none' type as a return value, the purpose, functionality, and behavior of the return statement, handling variable number of input arguments, flexible arguments, and processing variable length input in python.", 'chapters': [{'end': 22117.063, 'start': 22040.184, 'title': 'Python functions and return values', 'summary': "Discusses the concept of return values in python functions, emphasizing that even if a function does not explicitly return anything, it still returns a value called 'none', confirmed by checking the type of the output, which is of 'none' type.", 'duration': 76.879, 'highlights': ["The concept of return values in Python functions is explained, emphasizing that even if a function does not explicitly return anything, it still returns a value called 'none', which is demonstrated by checking the type of the output, showing it to be of 'none' type.", 'The return statement in Python is highlighted as not only being used to return a particular value, indicating a broader functionality beyond just returning specific values.', "The function 'g' is discussed, emphasizing that it does not return anything and just prints, with the example of not printing anything, showcasing the scenario of a function without a return value."]}, {'end': 22387.323, 'start': 22117.703, 'title': 'Return statement in python', 'summary': 'Explains the purpose and functionality of the return statement in python functions, including returning single and multiple values, and the default return value. it also demonstrates the behavior of the return statement in functions with practical examples.', 'duration': 269.62, 'highlights': ['The return statement in Python has two purposes: it can return a value and it can exit the function like the break statement in loops.', 'The return statement can return multiple values in a sequence, providing a powerful feature unique to Python.', "When the return statement is called without an argument, the default return value is of type 'None'."]}, {'end': 22579.079, 'start': 22387.323, 'title': 'Handling variable number of input arguments', 'summary': 'Discusses how to handle an arbitrary number of input arguments in a function using python, addressing the need for a universal add function capable of receiving any number of arguments and returning the result, making it very helpful and efficient for various scenarios.', 'duration': 191.756, 'highlights': ["Python provides an easy way to handle arbitrary or variable number of inputs by using a star followed by a variable name in the function definition, such as 'args'.", 'The need for a universal add function that has the capacity to receive any number of arguments is addressed, providing flexibility and efficiency in handling different scenarios.', 'Exploring the concept of handling an arbitrary number of input arguments in a function, addressing the requirement for a universal add function that can receive any number of arguments and return the result efficiently.']}, {'end': 23035.059, 'start': 22580.02, 'title': 'Python functions and flexible arguments', 'summary': "Discusses the usage of flexible arguments in python functions, including the use of 'args' to receive an arbitrary number of arguments and the ability to handle input variable ordering in a controlled way, preparing for the next video on key-value pair processing.", 'duration': 455.039, 'highlights': ["The 'args' in Python functions acts as a list to receive an arbitrary number of arguments, and the length of 'args' can be used to determine the number of arguments passed.", "A function using 'args' can handle an arbitrary number of arguments without needing separate functions for different argument counts, showcasing the flexibility of Python functions.", "The chapter hints at the upcoming topic of handling input variable ordering in a controlled way, preparing for the next video's focus on key-value pair processing."]}, {'end': 23417.864, 'start': 23035.54, 'title': 'Processing variable length input in python', 'summary': 'Explains how to process an arbitrary number of variables in python using the double star notation, allowing for a key-value pair list, and demonstrates a function that handles variable arguments and their values, showcasing the flexibility of python in handling diverse types and quantities of input data.', 'duration': 382.324, 'highlights': ['Python allows processing an arbitrary number of variables using the double star notation, which receives a key-value pair list, resembling a dictionary data structure.', "A function is demonstrated that handles variable arguments and their values, showcasing Python's flexibility in handling diverse types and quantities of input data.", "Python's flexibility in handling diverse types and quantities of input data is highlighted, showcasing the simplicity and power of Python as a high-level language."]}], 'duration': 1377.68, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI22040184.jpg', 'highlights': ['The return statement in Python has two purposes: it can return a value and it can exit the function like the break statement in loops.', 'Python allows processing an arbitrary number of variables using the double star notation, which receives a key-value pair list, resembling a dictionary data structure.', "Python provides an easy way to handle arbitrary or variable number of inputs by using a star followed by a variable name in the function definition, such as 'args'.", "The concept of return values in Python functions is explained, emphasizing that even if a function does not explicitly return anything, it still returns a value called 'none', which is demonstrated by checking the type of the output, showing it to be of 'none' type.", "The 'args' in Python functions acts as a list to receive an arbitrary number of arguments, and the length of 'args' can be used to determine the number of arguments passed."]}, {'end': 24527.832, 'segs': [{'end': 23444.62, 'src': 'embed', 'start': 23418.265, 'weight': 0, 'content': [{'end': 23422.288, 'text': "But before that, let's have one or two more things to discuss about the functions.", 'start': 23418.265, 'duration': 4.023}, {'end': 23423.589, 'text': "Yeah, let's see.", 'start': 23422.608, 'duration': 0.981}, {'end': 23425.611, 'text': 'So hope to see you in the next video.', 'start': 23424.19, 'duration': 1.421}, {'end': 23432.136, 'text': "Okay, I really want to talk about these default values for a function as well because that's important.", 'start': 23426.391, 'duration': 5.745}, {'end': 23434.889, 'text': 'and mostly needed.', 'start': 23433.748, 'duration': 1.141}, {'end': 23444.62, 'text': 'The default value is a value of the input variable that you assign while you are defining a function.', 'start': 23435.97, 'duration': 8.65}], 'summary': 'Discussion on default values for function inputs: important and mostly needed.', 'duration': 26.355, 'max_score': 23418.265, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI23418265.jpg'}, {'end': 23496.959, 'src': 'embed', 'start': 23468.534, 'weight': 5, 'content': [{'end': 23473.316, 'text': 'And, by the way, you can have multiple variables with default values, some variables with default values defined,', 'start': 23468.534, 'duration': 4.782}, {'end': 23477.941, 'text': 'some variables with default variables, default values not defined, and so on.', 'start': 23473.316, 'duration': 4.625}, {'end': 23479.342, 'text': 'So you can have this.', 'start': 23478.521, 'duration': 0.821}, {'end': 23487.17, 'text': 'One care must be taken here that the default value, when you actually define the function and you compile this function,', 'start': 23480.123, 'duration': 7.047}, {'end': 23491.495, 'text': 'actually you run the cell shift, enter in Jupyter Notebook at that very time.', 'start': 23487.17, 'duration': 4.325}, {'end': 23496.959, 'text': 'this variable is assigned this value at that particular time.', 'start': 23491.495, 'duration': 5.464}], 'summary': 'Functions can have multiple variables with default values, which are assigned at the time of function compilation in jupyter notebook.', 'duration': 28.425, 'max_score': 23468.534, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI23468534.jpg'}, {'end': 23774.987, 'src': 'embed', 'start': 23747.975, 'weight': 1, 'content': [{'end': 23753.317, 'text': "and that's because these default values, they are assigned at compile time.", 'start': 23747.975, 'duration': 5.342}, {'end': 23756.438, 'text': 'Compile time, actually, this is not a compiled language.', 'start': 23753.917, 'duration': 2.521}, {'end': 23760.279, 'text': 'use the word compiled, compiled again and again.', 'start': 23757.678, 'duration': 2.601}, {'end': 23764.722, 'text': 'just think, when we define this function and we run the cell at that particular time,', 'start': 23760.279, 'duration': 4.443}, {'end': 23768.344, 'text': 'the default value is assigned and the default value never changes.', 'start': 23764.722, 'duration': 3.622}, {'end': 23770.545, 'text': 'it stays fixed.', 'start': 23768.344, 'duration': 2.201}, {'end': 23774.987, 'text': 'um, yeah, so, and i will show you that example.', 'start': 23770.545, 'duration': 4.442}], 'summary': 'Default values assigned at compile time stay fixed.', 'duration': 27.012, 'max_score': 23747.975, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI23747975.jpg'}, {'end': 24368.805, 'src': 'embed', 'start': 24340.398, 'weight': 4, 'content': [{'end': 24344.761, 'text': 'You need not to write the function definition in every coding file you need.', 'start': 24340.398, 'duration': 4.363}, {'end': 24352.246, 'text': 'You just make one coding file that is the most important for you that is called a module.', 'start': 24344.801, 'duration': 7.445}, {'end': 24358.931, 'text': 'Wherever you want to use any of those functions that are there in that module, you can call it, you can use it.', 'start': 24352.326, 'duration': 6.605}, {'end': 24364.622, 'text': "So that's about the modules we are going to make.", 'start': 24360.038, 'duration': 4.584}, {'end': 24368.805, 'text': "I'm going to show you one example of making module and how to use that.", 'start': 24365.663, 'duration': 3.142}], 'summary': 'Creating modules allows for reusable code in different files, reducing repetition and increasing efficiency.', 'duration': 28.407, 'max_score': 24340.398, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI24340398.jpg'}, {'end': 24438.813, 'src': 'embed', 'start': 24415.899, 'weight': 3, 'content': [{'end': 24423.412, 'text': 'So in the next video I will show you how to actually make and use the modules.', 'start': 24415.899, 'duration': 7.513}, {'end': 24427.599, 'text': 'Yeah, so hope to see you in the next video.', 'start': 24425.355, 'duration': 2.244}, {'end': 24431.749, 'text': 'Okay, in the last video I told you about modules.', 'start': 24429.068, 'duration': 2.681}, {'end': 24438.813, 'text': 'Module is just a Python file that can contain a code that can be used anywhere if you want normally.', 'start': 24432.71, 'duration': 6.103}], 'summary': 'Next video will demonstrate making and using modules in python.', 'duration': 22.914, 'max_score': 24415.899, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI24415899.jpg'}], 'start': 23418.265, 'title': 'Default values, functions, and python modules', 'summary': 'Discusses default values in functions, emphasizing their importance and usage, python function default values, their behavior and the implications of reference type variables on default values, and introduces python modules, explaining their purpose, usage, and the process of importing and using them.', 'chapters': [{'end': 23487.17, 'start': 23418.265, 'title': 'Default values in functions', 'summary': 'Discusses the concept of default values in functions, emphasizing their importance and usage, such as assigning input variables and the behavior when no value is supplied.', 'duration': 68.905, 'highlights': ['The default value is a value of the input variable that you assign while you are defining a function, and it is important and mostly needed.', 'When a function is called without input, the default value is used, demonstrating the behavior of default values in functions.', 'Multiple variables with default values can be defined within a function, allowing flexibility in function definitions.']}, {'end': 24089.89, 'start': 23487.17, 'title': 'Python function default values', 'summary': 'Explains the behavior of default values in python functions, emphasizing the difference in assigning and changing default values for variables and lists, and the implications of reference type variables on default values assignment and modification.', 'duration': 602.72, 'highlights': ['The default value for a variable is assigned at the time when the function is created, not at the function call time, and it stays fixed.', 'Variables that are reference type variables may behave differently when used as default values, and their default values are assigned at compile time.', 'The behavior of default values for lists in Python functions differs due to their reference type nature, leading to the default values not changing even when a new list is passed as an argument.']}, {'end': 24527.832, 'start': 24089.89, 'title': 'Understanding python modules', 'summary': 'Introduces the concept of python modules, explaining their purpose, usage, and the process of importing and using them in coding projects, with an emphasis on reducing redundancy and enhancing code reusability.', 'duration': 437.942, 'highlights': ['The chapter introduces the concept of Python modules, explaining their purpose, usage, and the process of importing and using them in coding projects.', 'Emphasizes the process of importing and using modules in coding projects to reduce redundancy and enhance code reusability.', 'Explains the process of adding the path of module files and importing them using sys.path.append.']}], 'duration': 1109.567, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI23418265.jpg', 'highlights': ['The default value is a value of the input variable that you assign while defining a function, and it is important and mostly needed.', 'The default value for a variable is assigned at the time when the function is created, not at the function call time, and it stays fixed.', 'Variables that are reference type variables may behave differently when used as default values, and their default values are assigned at compile time.', 'The chapter introduces the concept of Python modules, explaining their purpose, usage, and the process of importing and using them in coding projects.', 'Emphasizes the process of importing and using modules in coding projects to reduce redundancy and enhance code reusability.', 'Multiple variables with default values can be defined within a function, allowing flexibility in function definitions.']}, {'end': 26868.363, 'segs': [{'end': 24580.117, 'src': 'embed', 'start': 24527.832, 'weight': 0, 'content': [{'end': 24531.675, 'text': 'or you can import your file with some other name if you want.', 'start': 24527.832, 'duration': 3.843}, {'end': 24533.877, 'text': 'You can rename that on the fly if you want.', 'start': 24531.735, 'duration': 2.142}, {'end': 24538.96, 'text': 'Once this is imported, now you can use all the functions like the built-in functions.', 'start': 24534.457, 'duration': 4.503}, {'end': 24543.124, 'text': 'The implementation of these functions are not there in your coding file.', 'start': 24539.541, 'duration': 3.583}, {'end': 24549.248, 'text': 'You are just using those, and you can now import this module into some other file and use there and so on.', 'start': 24543.544, 'duration': 5.704}, {'end': 24555.597, 'text': 'For very large kind of projects, it is good to make modules.', 'start': 24550.169, 'duration': 5.428}, {'end': 24562.928, 'text': 'Actually, it is better to make packages, which is actually the directory structures that contain modules.', 'start': 24556.138, 'duration': 6.79}, {'end': 24573.212, 'text': 'But modules at least are really good for maintaining a large amount of cores or actually the functions that you want to use again and again.', 'start': 24564.224, 'duration': 8.988}, {'end': 24578.256, 'text': "So let's make a module.", 'start': 24573.712, 'duration': 4.544}, {'end': 24580.117, 'text': "Why not? So let's make a module.", 'start': 24578.316, 'duration': 1.801}], 'summary': 'Import and use modules for maintaining and reusing functions in large projects.', 'duration': 52.285, 'max_score': 24527.832, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI24527832.jpg'}, {'end': 25028.475, 'src': 'embed', 'start': 24985.156, 'weight': 11, 'content': [{'end': 24993.659, 'text': "or let's say, um, utils, for example, utilities, or whatever name i mean.", 'start': 24985.156, 'duration': 8.503}, {'end': 24999.702, 'text': "let's let's call it as uh, let's call it as abc, for example, abc, whatever.", 'start': 24993.659, 'duration': 6.043}, {'end': 25005.919, 'text': 'you just make that and just copy that Python file here.', 'start': 25001.576, 'duration': 4.343}, {'end': 25008.382, 'text': 'my universal functions dot.', 'start': 25005.919, 'duration': 2.463}, {'end': 25021.954, 'text': 'by now, if you go back, if you go back to your here, here is the jupiter.', 'start': 25008.382, 'duration': 13.572}, {'end': 25023.375, 'text': 'here is the jupiter.', 'start': 25021.954, 'duration': 1.421}, {'end': 25027.175, 'text': 'now you go back to your code.', 'start': 25023.375, 'duration': 3.8}, {'end': 25028.475, 'text': 'this is your file.', 'start': 25027.175, 'duration': 1.3}], 'summary': "Creating a universal python file named 'abc' for utilities.", 'duration': 43.319, 'max_score': 24985.156, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI24985156.jpg'}, {'end': 25130.06, 'src': 'embed', 'start': 25101.029, 'weight': 6, 'content': [{'end': 25105.166, 'text': 'once you have imported that, Now you can use the functions if you want.', 'start': 25101.029, 'duration': 4.137}, {'end': 25116.849, 'text': 'For example, you can check the implementation of my apps dot, if you see dot add numerics, you want to check the implementation of that here.', 'start': 25105.226, 'duration': 11.623}, {'end': 25119.91, 'text': 'Remember this file is no longer in this particular file.', 'start': 25117.649, 'duration': 2.261}, {'end': 25121.05, 'text': 'This is located somewhere else.', 'start': 25119.95, 'duration': 1.1}, {'end': 25130.06, 'text': 'And you can call this function like the built-in functions, myapps.addAllNumerics.', 'start': 25122.371, 'duration': 7.689}], 'summary': 'Imported file allows accessing myapps functions like myapps.addallnumerics', 'duration': 29.031, 'max_score': 25101.029, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI25101029.jpg'}, {'end': 25361.478, 'src': 'embed', 'start': 25316.983, 'weight': 3, 'content': [{'end': 25320.987, 'text': 'So this module file does not require to only contain functions.', 'start': 25316.983, 'duration': 4.004}, {'end': 25327.195, 'text': 'It can contain any information, any data that you want to use in other files, other coding and stuff and so on.', 'start': 25321.448, 'duration': 5.747}, {'end': 25330.818, 'text': "So, yeah, that's about modules.", 'start': 25328.277, 'duration': 2.541}, {'end': 25335.219, 'text': 'In the next video, we will practice about these functions a little bit.', 'start': 25331.398, 'duration': 3.821}, {'end': 25342.681, 'text': 'We will be seeing how to call a function inside another function, how to make a lot of functions that are calling each other, and so on.', 'start': 25336.979, 'duration': 5.702}, {'end': 25350.323, 'text': 'So we will be practicing more about these functions, not theoretically just in Jupyter Notebook,', 'start': 25343.361, 'duration': 6.962}, {'end': 25359.615, 'text': 'just to get a better look and feel of of functions more, and after that practice we will be then jumping towards data structure,', 'start': 25350.323, 'duration': 9.292}, {'end': 25361.478, 'text': 'starting from strings.', 'start': 25359.615, 'duration': 1.863}], 'summary': 'Module file can contain any data for use in coding. next, will practice calling functions and working with data structures.', 'duration': 44.495, 'max_score': 25316.983, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI25316983.jpg'}, {'end': 25420.223, 'src': 'embed', 'start': 25388.66, 'weight': 5, 'content': [{'end': 25390.061, 'text': 'just to get a good grip on loops.', 'start': 25388.66, 'duration': 1.401}, {'end': 25391.983, 'text': "Let's solve a problem.", 'start': 25390.942, 'duration': 1.041}, {'end': 25399.428, 'text': "Let's just solve a problem using the functions just to get a good idea of functions.", 'start': 25394.524, 'duration': 4.904}, {'end': 25411.195, 'text': 'What kind of problems should we solve here? Should we solve an older problem? Last time we solved a problem using loops that were sorting a list.', 'start': 25401.069, 'duration': 10.126}, {'end': 25415.218, 'text': "Why don't we solve the same problem? But in a different way.", 'start': 25411.716, 'duration': 3.502}, {'end': 25420.223, 'text': "So let's go to Jupyter and see our Jupyter file.", 'start': 25415.599, 'duration': 4.624}], 'summary': 'Solving a problem using functions and loops in jupyter.', 'duration': 31.563, 'max_score': 25388.66, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI25388660.jpg'}, {'end': 25503.868, 'src': 'embed', 'start': 25472.635, 'weight': 9, 'content': [{'end': 25478.018, 'text': "Let's just make a function that let's just make a function.", 'start': 25472.635, 'duration': 5.383}, {'end': 25493.661, 'text': "let's say define, find minimum, and the function accepts a list and returns the minimum value in the list, not only the minimum value of the list,", 'start': 25478.018, 'duration': 15.643}, {'end': 25496.563, 'text': 'but also the position of that minimum value.', 'start': 25493.661, 'duration': 2.902}, {'end': 25503.868, 'text': 'so find minimum, as well as find, so minimum as well as the position of the minimum in the list.', 'start': 25496.563, 'duration': 7.305}], 'summary': 'Create a function to find the minimum value and its position in a list.', 'duration': 31.233, 'max_score': 25472.635, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI25472635.jpg'}, {'end': 25771.426, 'src': 'embed', 'start': 25706.218, 'weight': 4, 'content': [{'end': 25708.639, 'text': "So let's see what's the value, what's the result.", 'start': 25706.218, 'duration': 2.421}, {'end': 25712.98, 'text': 'So print a, b.', 'start': 25709.179, 'duration': 3.801}, {'end': 25718.741, 'text': 'So a is 0, yes, and the position of minimum is 3.', 'start': 25712.98, 'duration': 5.761}, {'end': 25720.322, 'text': 'I guess it is working fine, great.', 'start': 25718.741, 'duration': 1.581}, {'end': 25722.802, 'text': "So that's one function, findMinimum.", 'start': 25720.842, 'duration': 1.96}, {'end': 25724.643, 'text': "Let's write another function, swap.", 'start': 25723.363, 'duration': 1.28}, {'end': 25724.903, 'text': 'So define.', 'start': 25724.663, 'duration': 0.24}, {'end': 25736.693, 'text': "define another function, let's say swap values.", 'start': 25731.107, 'duration': 5.586}, {'end': 25746.064, 'text': 'and what we do is it actually accepts two indices, index one, it actually accepts a list.', 'start': 25736.693, 'duration': 9.371}, {'end': 25750.108, 'text': 'then two indices, index one and index two.', 'start': 25746.064, 'duration': 4.044}, {'end': 25755.073, 'text': 'and what it does is it actually swaps the value of index.', 'start': 25750.108, 'duration': 4.965}, {'end': 25761.498, 'text': 'so index one value should go to index two position and index two value should go to index one position in the same list.', 'start': 25755.073, 'duration': 6.425}, {'end': 25763.159, 'text': 'and then it returns the list.', 'start': 25761.498, 'duration': 1.661}, {'end': 25765.601, 'text': 'okay, great, so it would it.', 'start': 25763.159, 'duration': 2.442}, {'end': 25766.442, 'text': "so so that's a.", 'start': 25765.601, 'duration': 0.841}, {'end': 25767.403, 'text': "that's a good example.", 'start': 25766.442, 'duration': 0.961}, {'end': 25768.103, 'text': 'it would.', 'start': 25767.403, 'duration': 0.7}, {'end': 25768.984, 'text': 'it accepts a list.', 'start': 25768.103, 'duration': 0.881}, {'end': 25771.426, 'text': 'uh, type variable.', 'start': 25768.984, 'duration': 2.442}], 'summary': 'Functions findminimum and swap are defined and tested successfully.', 'duration': 65.208, 'max_score': 25706.218, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI25706218.jpg'}, {'end': 26087.197, 'src': 'embed', 'start': 26052.047, 'weight': 13, 'content': [{'end': 26055.108, 'text': 'But for readability, it is good to write else.', 'start': 26052.047, 'duration': 3.061}, {'end': 26058.228, 'text': 'If all are numeric, then what should we do?', 'start': 26055.928, 'duration': 2.3}, {'end': 26061.069, 'text': 'Okay, what should we do if all are numeric?', 'start': 26058.729, 'duration': 2.34}, {'end': 26067.831, 'text': 'What we do is we will be doing what?', 'start': 26061.189, 'duration': 6.642}, {'end': 26069.391, 'text': 'We will define minimum.', 'start': 26068.031, 'duration': 1.36}, {'end': 26078.973, 'text': "We'll be finding out the minimum, and then we will be swapping the minimum from.", 'start': 26070.282, 'duration': 8.691}, {'end': 26084.399, 'text': 'What should we do? We have already functioned findMinimum.', 'start': 26078.973, 'duration': 5.426}, {'end': 26087.197, 'text': 'that we can call just right away.', 'start': 26085.316, 'duration': 1.881}], 'summary': 'Discussion on finding and swapping the minimum value in a numeric set.', 'duration': 35.15, 'max_score': 26052.047, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI26052047.jpg'}], 'start': 24527.832, 'title': 'Python functions and modules', 'summary': 'Covers creating and using modules, defining and importing python functions, practical implementation of functions, and troubleshooting sorting algorithms in python, emphasizing practical examples and problem-solving. it discusses the benefits of maintaining large projects and emphasizes the need for understanding functions and handling multiple functions in python.', 'chapters': [{'end': 24618.251, 'start': 24527.832, 'title': 'Creating and using modules in python', 'summary': 'Discusses the process of creating and using modules in python, emphasizing the benefits for maintaining large projects and the ease of importing and using functions from modules in different files or projects.', 'duration': 90.419, 'highlights': ['Modules are recommended for maintaining large projects, while packages, which are directory structures containing modules, are preferable for very large projects.', 'Importing a module allows the use of built-in functions without the need to implement them in the coding file, providing convenience and efficiency.', 'Creating modules in Python enables the organization and reusability of functions, enhancing code maintenance and readability.']}, {'end': 25316.382, 'start': 24618.331, 'title': 'Defining and importing python functions', 'summary': "Discusses defining functions checkallargs and addallnumerics, importing functions from a .py file, and arranging modules in a directory structure, with an emphasis on using 'abc' as an example, with practical code examples and explanations.", 'duration': 698.051, 'highlights': ['The chapter discusses defining functions checkAllArgs and addAllNumerics', 'Importing functions from a .py file and arranging modules in a directory structure', "Emphasis on using 'abc' as an example with practical code examples and explanations"]}, {'end': 25668.591, 'start': 25316.983, 'title': 'Functions and modules in python', 'summary': 'Discusses the concept of modules, the practical implementation of functions, and the usage of loops in solving problems, emphasizing the importance of understanding functions and handling multiple functions in python, along with the need for practical problem-solving.', 'duration': 351.608, 'highlights': ['The chapter emphasizes the importance of understanding functions and handling multiple functions in Python, and the need for practical problem-solving.', 'The module file is not limited to containing only functions, but can also include other information and data for use in other files and coding.', 'The next video will focus on practicing calling a function inside another function, creating multiple interlinked functions, and gaining a better understanding of functions practically in Jupyter Notebook.', 'The chapter encourages practical problem-solving using functions, similar to previous exercises involving if conditions and loops, and proposes solving a problem using functions to gain a better grasp of their implementation.', 'The chapter advocates for solving a problem involving sorting a list using a different approach with functions to gain a better understanding of their usage.']}, {'end': 26051.967, 'start': 25668.851, 'title': 'Python functions and sorting', 'summary': 'Covers the implementation of python functions for finding minimum value, swapping values, and sorting a list, with a focus on ensuring the list contains numeric values before sorting.', 'duration': 383.116, 'highlights': ['The chapter focuses on implementing Python functions for finding minimum value, swapping values, and sorting a list, while ensuring the list contains numeric values before sorting.', 'The implementation of the findMinimum function is demonstrated using a specific list and the corresponding minimum value and index, showcasing the functionality of the function.', 'The transcript details the implementation of the swap function, which accepts two indices and a list, swapping the values at the specified indices and returning the updated list.']}, {'end': 26868.363, 'start': 26052.047, 'title': 'Troubleshooting sorting algorithm', 'summary': 'Explores the troubleshooting of a sorting algorithm through the process of finding the minimum value, swapping values, and debugging a function for numeric values, aiming to sort a list. it involves identifying and resolving bugs in the code.', 'duration': 816.316, 'highlights': ['Identifying and resolving bugs in the code', 'Exploration of finding the minimum value and swapping values', 'Debugging a function for numeric values']}], 'duration': 2340.531, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI24527832.jpg', 'highlights': ['Modules are recommended for maintaining large projects, while packages are preferable for very large projects.', 'Importing a module allows the use of built-in functions without implementing them, providing convenience and efficiency.', 'Creating modules in Python enables the organization and reusability of functions, enhancing code maintenance and readability.', 'The chapter emphasizes the importance of understanding functions and handling multiple functions in Python, and the need for practical problem-solving.', 'The chapter focuses on implementing Python functions for finding minimum value, swapping values, and sorting a list, ensuring the list contains numeric values before sorting.', 'The chapter encourages practical problem-solving using functions and advocates for solving a problem involving sorting a list using a different approach with functions to gain a better understanding of their usage.', 'The chapter discusses defining functions checkAllArgs and addAllNumerics, importing functions from a .py file, and arranging modules in a directory structure.', 'The module file is not limited to containing only functions, but can also include other information and data for use in other files and coding.', 'The next video will focus on practicing calling a function inside another function, creating multiple interlinked functions, and gaining a better understanding of functions practically in Jupyter Notebook.', 'The implementation of the findMinimum function is demonstrated using a specific list and the corresponding minimum value and index, showcasing the functionality of the function.', 'The transcript details the implementation of the swap function, which accepts two indices and a list, swapping the values at the specified indices and returning the updated list.', "Emphasis on using 'abc' as an example with practical code examples and explanations.", 'The chapter advocates for solving a problem involving sorting a list using a different approach with functions to gain a better understanding of their usage.', 'Identifying and resolving bugs in the code, exploration of finding the minimum value and swapping values, and debugging a function for numeric values.']}, {'end': 30174.636, 'segs': [{'end': 26916.884, 'src': 'embed', 'start': 26868.363, 'weight': 1, 'content': [{'end': 26871.484, 'text': 'so you see, you can call the functions inside other functions.', 'start': 26868.363, 'duration': 3.121}, {'end': 26878.046, 'text': 'you can call the functions from modules if they are no longer working or no longer beneficial for you.', 'start': 26871.484, 'duration': 6.562}, {'end': 26880.447, 'text': 'you can write new functions, you can call them, you can.', 'start': 26878.046, 'duration': 2.401}, {'end': 26882.828, 'text': 'Yeah, all that stuff.', 'start': 26881.527, 'duration': 1.301}, {'end': 26889.512, 'text': 'I guess that lengthy video taught you a lot of lessons, how to code actually.', 'start': 26883.549, 'duration': 5.963}, {'end': 26894.776, 'text': 'And this actually happens when you are doing tasks that are really big.', 'start': 26890.373, 'duration': 4.403}, {'end': 26897.037, 'text': 'You have to define different functions.', 'start': 26895.636, 'duration': 1.401}, {'end': 26902.66, 'text': 'you need to define different functions for modular approach and focus on each function as a separate entity,', 'start': 26897.037, 'duration': 5.623}, {'end': 26909.582, 'text': 'and that that makes much simplicity in managing the code and bug fixing and all that stuff.', 'start': 26902.66, 'duration': 6.922}, {'end': 26914.783, 'text': 'You see, I fixed the bug by just noticing that, by just focusing on this function.', 'start': 26909.622, 'duration': 5.161}, {'end': 26916.884, 'text': 'I have not taught anything else.', 'start': 26915.383, 'duration': 1.501}], 'summary': 'Functions can be nested, called from modules, and used for modular approach in coding, aiding in bug fixing.', 'duration': 48.521, 'max_score': 26868.363, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI26868363.jpg'}, {'end': 26997.27, 'src': 'embed', 'start': 26950.082, 'weight': 0, 'content': [{'end': 26956.268, 'text': 'where you need not write a lot of loops and a lot of code and still you will be able to achieve a lot of stuff.', 'start': 26950.082, 'duration': 6.186}, {'end': 26960.551, 'text': 'And for that, we need to go through the data structures that are available in Python.', 'start': 26956.848, 'duration': 3.703}, {'end': 26964.894, 'text': 'so from the very next video we will start seeing strings.', 'start': 26961.352, 'duration': 3.542}, {'end': 26966.034, 'text': "that's the data structure.", 'start': 26964.894, 'duration': 1.14}, {'end': 26967.755, 'text': 'we will see list in detail.', 'start': 26966.034, 'duration': 1.721}, {'end': 26970.076, 'text': 'we will see set in detail.', 'start': 26967.755, 'duration': 2.321}, {'end': 26972.397, 'text': 'we will see dictionary in detail.', 'start': 26970.076, 'duration': 2.321}, {'end': 26980.801, 'text': 'we will see tuples in detail and after going through all these data structures and getting a good grip for the data structures, then finally,', 'start': 26972.397, 'duration': 8.404}, {'end': 26981.481, 'text': 'we will move.', 'start': 26980.801, 'duration': 0.68}, {'end': 26989.885, 'text': 'we will move to the the packages that are available for data science, particularly numpy, pandas, matplotlib,', 'start': 26981.481, 'duration': 8.404}, {'end': 26997.27, 'text': 'And we will see maybe I include one or two videos for scikit-learn as well.', 'start': 26990.665, 'duration': 6.605}], 'summary': 'Python data structures and data science packages covered in detail with a focus on strings, lists, sets, dictionaries, and tuples, before moving on to numpy, pandas, matplotlib, and possibly scikit-learn.', 'duration': 47.188, 'max_score': 26950.082, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI26950082.jpg'}, {'end': 27605.782, 'src': 'embed', 'start': 27575.866, 'weight': 5, 'content': [{'end': 27581.969, 'text': 'Or maybe the formatting is in a way that you want to, even if it is not very lengthy,', 'start': 27575.866, 'duration': 6.103}, {'end': 27587.932, 'text': 'you still want the different chunks of the same string to appear in different lines.', 'start': 27581.969, 'duration': 5.963}, {'end': 27594.995, 'text': 'So there is a way to declare multi-line string, again, using either three single quotes or three double quotes.', 'start': 27588.012, 'duration': 6.983}, {'end': 27605.782, 'text': 'and then three double quotes or single quotes, whatever convention you follow, then you write all the string in, no matter how many lines you want,', 'start': 27595.735, 'duration': 10.047}], 'summary': 'You can declare multi-line strings using either three single or double quotes.', 'duration': 29.916, 'max_score': 27575.866, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI27575866.jpg'}, {'end': 28165.475, 'src': 'embed', 'start': 28135.298, 'weight': 6, 'content': [{'end': 28137.338, 'text': 'The indexing notation is square brackets.', 'start': 28135.298, 'duration': 2.04}, {'end': 28142.121, 'text': 'And indexing always starts from zero rather than one in Python.', 'start': 28138.039, 'duration': 4.082}, {'end': 28145.522, 'text': 'There are some languages in which the indexing starts from one.', 'start': 28142.681, 'duration': 2.841}, {'end': 28154.707, 'text': 'For example MATLAB, the indexing starts from one, but in Python and in several other languages, uh, the indexing starts from zero,', 'start': 28145.582, 'duration': 9.125}, {'end': 28156.969, 'text': 'which has some benefits over starting with one.', 'start': 28154.707, 'duration': 2.262}, {'end': 28157.909, 'text': 'it has some benefits.', 'start': 28156.969, 'duration': 0.94}, {'end': 28161.492, 'text': "so starting with zero is okay, it's okay.", 'start': 28157.909, 'duration': 3.583}, {'end': 28165.475, 'text': "so let's say we want to access element add index five.", 'start': 28161.492, 'duration': 3.983}], 'summary': 'Indexing in python starts from zero, unlike matlab which starts from one, with benefits.', 'duration': 30.177, 'max_score': 28135.298, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI28135298.jpg'}, {'end': 28416.696, 'src': 'embed', 'start': 28382.722, 'weight': 15, 'content': [{'end': 28385.104, 'text': 'So we have negative indices as well.', 'start': 28382.722, 'duration': 2.382}, {'end': 28393.491, 'text': 'And by the way, fetching this kind of substring is sometimes called slicing.', 'start': 28386.945, 'duration': 6.546}, {'end': 28401.097, 'text': 'I mean we are just fetching the slicing, although the term slicing is much more popular in mutable data structures.', 'start': 28393.691, 'duration': 7.406}, {'end': 28404.239, 'text': 'What is a mutable data structure??', 'start': 28402.678, 'duration': 1.561}, {'end': 28406.621, 'text': 'What is an immutable data structure?', 'start': 28404.54, 'duration': 2.081}, {'end': 28416.696, 'text': 'Well Yeah, I should tell you right now you cannot change any character in the string.', 'start': 28407.302, 'duration': 9.394}], 'summary': 'Introduction to negative indices and string slicing in python.', 'duration': 33.974, 'max_score': 28382.722, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI28382722.jpg'}, {'end': 28536.512, 'src': 'embed', 'start': 28503.666, 'weight': 16, 'content': [{'end': 28507.889, 'text': 'it refers to fetching a substructure or substring.', 'start': 28503.666, 'duration': 4.223}, {'end': 28511.751, 'text': 'in this case, in the list it will be a sub list or so on.', 'start': 28507.889, 'duration': 3.862}, {'end': 28513.212, 'text': "so that's what slicing is.", 'start': 28511.751, 'duration': 1.461}, {'end': 28515.996, 'text': 'Yeah, great.', 'start': 28514.113, 'duration': 1.883}, {'end': 28522.186, 'text': "Why don't we do some more fun with the string? Yeah, let me show you more fun with the string.", 'start': 28517.038, 'duration': 5.148}, {'end': 28523.829, 'text': 'More indexing.', 'start': 28523.087, 'duration': 0.742}, {'end': 28528.326, 'text': "Let's say you start at index 0.", 'start': 28523.969, 'duration': 4.357}, {'end': 28536.512, 'text': 'you go to index 12 but not including 12 and then you jump you take a jump of 2 rather than 1.', 'start': 28528.326, 'duration': 8.186}], 'summary': 'Demonstrating string slicing and indexing, including skipping every 2nd character.', 'duration': 32.846, 'max_score': 28503.666, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI28503666.jpg'}, {'end': 28746.759, 'src': 'embed', 'start': 28719.13, 'weight': 3, 'content': [{'end': 28725.055, 'text': 'In the next video, we will see some functions that are supplied for string processing.', 'start': 28719.13, 'duration': 5.925}, {'end': 28729.719, 'text': 'What we can do with strings and how can we manipulate those strings.', 'start': 28725.535, 'duration': 4.184}, {'end': 28739.507, 'text': 'Although we cannot manipulate the contents of a string, but we may copy a string, we may get a string, manipulate it and save it to another variable.', 'start': 28730.079, 'duration': 9.428}, {'end': 28746.759, 'text': 'and what kind of functions that are available in string in string data structure, string data type.', 'start': 28739.507, 'duration': 7.252}], 'summary': 'Exploring string processing functions and manipulation for string data types.', 'duration': 27.629, 'max_score': 28719.13, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI28719130.jpg'}, {'end': 28790.556, 'src': 'embed', 'start': 28762.794, 'weight': 17, 'content': [{'end': 28767.318, 'text': 'These are a lot of spaces at the beginning, and these are a lot of spaces at the end.', 'start': 28762.794, 'duration': 4.524}, {'end': 28769.56, 'text': 'There are some spaces in the middle as well.', 'start': 28767.378, 'duration': 2.182}, {'end': 28772.382, 'text': 'So there is one function called strip.', 'start': 28770.441, 'duration': 1.941}, {'end': 28778.907, 'text': 'All the functions of the string, they are called by taking a dot, a dot something.', 'start': 28773.683, 'duration': 5.224}, {'end': 28781.209, 'text': 'These are called methods.', 'start': 28779.948, 'duration': 1.261}, {'end': 28790.556, 'text': 'You can loosely call them functions, but those kind of functions that are related to some data structure and called with dot,', 'start': 28782.049, 'duration': 8.507}], 'summary': 'Explaining string manipulation with methods and functions.', 'duration': 27.762, 'max_score': 28762.794, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI28762794.jpg'}, {'end': 29624.324, 'src': 'embed', 'start': 29595.165, 'weight': 10, 'content': [{'end': 29598.367, 'text': 'the good chances are there will be a built-in function that is available,', 'start': 29595.165, 'duration': 3.202}, {'end': 29602.508, 'text': 'and in that case i will encourage to use that function rather than to write your own one,', 'start': 29598.367, 'duration': 4.141}, {'end': 29609.351, 'text': 'because using the built-in function or the method that is tied up there will be much more faster, probably,', 'start': 29602.508, 'duration': 6.843}, {'end': 29614.093, 'text': "than the function you'll be writing at your end, even if you're too smart in algorithms.", 'start': 29609.351, 'duration': 4.742}, {'end': 29621.642, 'text': "so, uh yeah, So that's about the string methods.", 'start': 29614.093, 'duration': 7.549}, {'end': 29624.324, 'text': 'There are so many other methods that are available.', 'start': 29621.662, 'duration': 2.662}], 'summary': 'Using built-in functions is faster than writing your own, especially for string methods.', 'duration': 29.159, 'max_score': 29595.165, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI29595165.jpg'}, {'end': 29696.794, 'src': 'embed', 'start': 29667.656, 'weight': 11, 'content': [{'end': 29674.003, 'text': 'Well, you can easily find out that using an in keyword and similarly not in means the reverse of that.', 'start': 29667.656, 'duration': 6.347}, {'end': 29676.792, 'text': 'or the complement of that or not of that.', 'start': 29674.87, 'duration': 1.922}, {'end': 29682.438, 'text': 'And in keyword always will return either true or Boolean or false.', 'start': 29677.513, 'duration': 4.925}, {'end': 29686.723, 'text': 'If it is inside the string, it will return true.', 'start': 29683.319, 'duration': 3.404}, {'end': 29688.925, 'text': 'If it is not inside, it will return false.', 'start': 29687.003, 'duration': 1.922}, {'end': 29696.093, 'text': "So let's check this, the implementation of that in Jupyter Notebook.", 'start': 29689.686, 'duration': 6.407}, {'end': 29696.794, 'text': "So let's see.", 'start': 29696.393, 'duration': 0.401}], 'summary': "Using 'in' keyword in python returns true or false based on string inclusion.", 'duration': 29.138, 'max_score': 29667.656, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI29667656.jpg'}, {'end': 29873.342, 'src': 'embed', 'start': 29848.903, 'weight': 12, 'content': [{'end': 29854.625, 'text': "For example, that's a special character, for example, maybe this string.", 'start': 29848.903, 'duration': 5.722}, {'end': 29860.808, 'text': 'Is this string smaller than the following string? Return true or false.', 'start': 29854.925, 'duration': 5.883}, {'end': 29871.66, 'text': 'Because there is particular ordering in Python that is defined for these characters that this becomes first and this, like A, becomes first and B,', 'start': 29861.689, 'duration': 9.971}, {'end': 29873.342, 'text': 'B becomes first and C, and so on.', 'start': 29871.66, 'duration': 1.682}], 'summary': 'Python has a defined ordering for characters, determining which comes first in a string.', 'duration': 24.439, 'max_score': 29848.903, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI29848903.jpg'}, {'end': 29979.854, 'src': 'embed', 'start': 29950.178, 'weight': 13, 'content': [{'end': 29954.56, 'text': 'And when we write this single code and this double code, another string starts here.', 'start': 29950.178, 'duration': 4.382}, {'end': 29957.061, 'text': 'And this is no longer a string.', 'start': 29955.181, 'duration': 1.88}, {'end': 29961.543, 'text': 'I mean, it has no data type inside.', 'start': 29958.502, 'duration': 3.041}, {'end': 29969.587, 'text': 'Well, how can we then insert these, double quotes inside? Well, there are several ways.', 'start': 29962.324, 'duration': 7.263}, {'end': 29979.854, 'text': 'One way is to use escape sequence, and escape sequence is just like it is.', 'start': 29970.127, 'duration': 9.727}], 'summary': 'Explains usage of single and double quotes, escape sequences in strings.', 'duration': 29.676, 'max_score': 29950.178, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI29950178.jpg'}, {'end': 30174.636, 'src': 'embed', 'start': 30146.64, 'weight': 14, 'content': [{'end': 30152.702, 'text': "that's a combination that is already there for a new line that is treated in a different way.", 'start': 30146.64, 'duration': 6.062}, {'end': 30159.065, 'text': "if you want this to be used as it is, and you don't want these, you don't want this behavior,", 'start': 30152.702, 'duration': 6.363}, {'end': 30167.268, 'text': 'you just want that all this should be treated in a very literal or raw sense.', 'start': 30159.065, 'duration': 8.203}, {'end': 30170.491, 'text': 'then you should just apply an R there.', 'start': 30167.887, 'duration': 2.604}, {'end': 30174.636, 'text': "An R will tell, okay, that's a raw string.", 'start': 30170.891, 'duration': 3.745}], 'summary': "Using 'r' indicates raw string treatment.", 'duration': 27.996, 'max_score': 30146.64, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI30146640.jpg'}], 'start': 26868.363, 'title': 'Python string handling', 'summary': 'Discusses function calling, modular approach, python data structures, string handling, indexing, slicing, and methods. it also highlights the significance of data science packages like numpy, pandas, matplotlib, and scikit-learn in the next phase of python learning.', 'chapters': [{'end': 26916.884, 'start': 26868.363, 'title': 'Function calling and modular approach', 'summary': 'Discusses the concept of calling functions inside other functions, utilizing modules for code organization, and the importance of defining different functions for a modular approach in order to simplify code management and bug fixing.', 'duration': 48.521, 'highlights': ['Utilizing modules for code organization and bug fixing is crucial, as it simplifies code management (e.g., defining different functions for a modular approach).', 'The concept of calling functions inside other functions is emphasized as a key aspect of the lesson on coding.', 'The importance of defining different functions for a modular approach is highlighted as essential for simplifying code management and bug fixing.']}, {'end': 27551.026, 'start': 26917.604, 'title': 'Introduction to python data structures', 'summary': 'Introduces python data structures: strings, lists, sets, dictionaries, and tuples, highlighting their significance and demonstrating string manipulation and type conversion, leading to a focus on data science packages like numpy, pandas, and matplotlib, and a brief mention of scikit-learn in the next phase of python learning.', 'duration': 633.422, 'highlights': ['The chapter introduces Python data structures: strings, lists, sets, dictionaries, and tuples', 'Demonstration of string manipulation and type conversion', 'Focus on data science packages like numpy, pandas, and matplotlib', 'Brief mention of scikit-learn in the next phase of Python learning']}, {'end': 28381.075, 'start': 27551.546, 'title': 'String handling and indexing in python', 'summary': 'Introduces multi-line strings and demonstrates their use for formatting messages and comments, then explains indexing and slicing of strings in python, highlighting the use of square brackets for indexing, zero-based indexing, accessing substrings, and the use of negative indices.', 'duration': 829.529, 'highlights': ['The chapter introduces multi-line strings and demonstrates their use for formatting messages and comments.', 'Explains indexing and slicing of strings in Python, highlighting the use of square brackets for indexing and zero-based indexing.', 'Demonstrates accessing substrings and the use of negative indices for accessing characters from the right side of the string.']}, {'end': 29551.074, 'start': 28382.722, 'title': 'String slicing and methods', 'summary': 'Explores string slicing in python, including negative indices and the concept of immutable data structures. it also discusses various string manipulation methods such as slicing, indexing, and functions like strip, lower, upper, replace, and split.', 'duration': 1168.352, 'highlights': ['String slicing and immutability', 'String slicing and indexing', 'String manipulation methods']}, {'end': 30174.636, 'start': 29551.614, 'title': 'String methods in python', 'summary': 'Covers various methods of manipulating and processing strings in python, including using built-in functions, checking for substrings, comparing strings, and handling special characters using escape sequences and raw strings.', 'duration': 623.022, 'highlights': ['The chapter covers various methods of manipulating and processing strings in Python, including using built-in functions, checking for substrings, comparing strings, and handling special characters using escape sequences and raw strings.', 'Using built-in functions for manipulating and processing strings is encouraged due to their efficiency compared to writing custom functions.', "The 'in' keyword can be used to check whether a particular substring is present in a string, and it returns a Boolean value of true or false.", "Python allows the comparison of strings using operators like '==' and '<', based on the strings' alphabetic order.", 'Special characters in strings can be handled using escape sequences, such as inserting double quotes or creating new lines and tabs.', "Using a raw string (marked with 'r') allows the inclusion of backslashes and other characters without being treated as escape sequences."]}], 'duration': 3306.273, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI26868363.jpg', 'highlights': ['The chapter introduces Python data structures: strings, lists, sets, dictionaries, and tuples', 'Utilizing modules for code organization and bug fixing is crucial, as it simplifies code management (e.g., defining different functions for a modular approach)', 'The concept of calling functions inside other functions is emphasized as a key aspect of the lesson on coding', 'The chapter covers various methods of manipulating and processing strings in Python, including using built-in functions, checking for substrings, comparing strings, and handling special characters using escape sequences and raw strings', 'The importance of defining different functions for a modular approach is highlighted as essential for simplifying code management and bug fixing', 'The chapter introduces multi-line strings and demonstrates their use for formatting messages and comments', 'Explains indexing and slicing of strings in Python, highlighting the use of square brackets for indexing and zero-based indexing', 'Demonstration of string manipulation and type conversion', 'Focus on data science packages like numpy, pandas, and matplotlib', 'Brief mention of scikit-learn in the next phase of Python learning', 'Using built-in functions for manipulating and processing strings is encouraged due to their efficiency compared to writing custom functions', "The 'in' keyword can be used to check whether a particular substring is present in a string, and it returns a Boolean value of true or false", "Python allows the comparison of strings using operators like '==' and '<', based on the strings' alphabetic order", 'Special characters in strings can be handled using escape sequences, such as inserting double quotes or creating new lines and tabs', "Using a raw string (marked with 'r') allows the inclusion of backslashes and other characters without being treated as escape sequences", 'String slicing and immutability', 'String slicing and indexing', 'String manipulation methods']}, {'end': 32754.217, 'segs': [{'end': 30300.112, 'src': 'embed', 'start': 30274.318, 'weight': 0, 'content': [{'end': 30281.542, 'text': 'basic data structures that are available in python is a list, tuple, set and dictionary.', 'start': 30274.318, 'duration': 7.224}, {'end': 30284.504, 'text': 'these are the basic data structures that are available.', 'start': 30281.542, 'duration': 2.962}, {'end': 30292.228, 'text': 'we can create our own data structures if we want to, but most of the problems, almost all of the problems, mostly they,', 'start': 30284.504, 'duration': 7.724}, {'end': 30300.112, 'text': 'are solved by these four basic data structures, although a lot of these are not that efficient.', 'start': 30292.228, 'duration': 7.884}], 'summary': 'Python has four basic data structures: list, tuple, set, and dictionary, commonly used for problem-solving, despite being not very efficient.', 'duration': 25.794, 'max_score': 30274.318, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI30274318.jpg'}, {'end': 31373.949, 'src': 'embed', 'start': 31343.092, 'weight': 4, 'content': [{'end': 31351.442, 'text': 'I mean, all the things that we saw in string, the indexing stays exactly the same in list as well as in tuple.', 'start': 31343.092, 'duration': 8.35}, {'end': 31363.118, 'text': "So tuple, for example, let's access element from, let's say, from the very beginning till the third element.", 'start': 31352.364, 'duration': 10.754}, {'end': 31367.985, 'text': 'Not the third element, till index three, which is actually the fourth element.', 'start': 31364.34, 'duration': 3.645}, {'end': 31373.949, 'text': 'So tuple and list, they will be exactly indexed as it is.', 'start': 31368.806, 'duration': 5.143}], 'summary': 'Indexing stays the same in list and tuple, accessed from beginning to index 3.', 'duration': 30.857, 'max_score': 31343.092, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI31343092.jpg'}, {'end': 31525.333, 'src': 'embed', 'start': 31493.222, 'weight': 3, 'content': [{'end': 31494.603, 'text': 'can we add more elements?', 'start': 31493.222, 'duration': 1.381}, {'end': 31496.364, 'text': 'can we insert more elements to the list?', 'start': 31494.603, 'duration': 1.761}, {'end': 31500.327, 'text': 'the answer is yes, because list is changeable, mutable.', 'start': 31496.364, 'duration': 3.963}, {'end': 31502.128, 'text': 'you can insert more elements.', 'start': 31500.327, 'duration': 1.801}, {'end': 31505.751, 'text': 'one way of inserting that is just to call an add operator.', 'start': 31502.128, 'duration': 3.623}, {'end': 31511.217, 'text': 'you just add plus and you just insert another list.', 'start': 31506.371, 'duration': 4.846}, {'end': 31518.626, 'text': 'So like two strings are concatenated by plus, two lists can be concatenated or combined together again by plus.', 'start': 31511.237, 'duration': 7.389}, {'end': 31525.333, 'text': 'But there is a faster function called append, l.append, that is sometimes faster than using this operator.', 'start': 31519.126, 'duration': 6.207}], 'summary': 'Lists are changeable and elements can be added using add or append method.', 'duration': 32.111, 'max_score': 31493.222, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI31493222.jpg'}, {'end': 32161.552, 'src': 'embed', 'start': 32108.803, 'weight': 1, 'content': [{'end': 32116.407, 'text': 'What we can do is we can call an update function, because dictionary is also a set, I mean a set of key value pairs,', 'start': 32108.803, 'duration': 7.604}, {'end': 32120.469, 'text': "but at the end of the day it's a set with specialized function, of course,", 'start': 32116.407, 'duration': 4.062}, {'end': 32127.313, 'text': 'but we can call update functions and insert the whole new dictionary inside dictionary as follows', 'start': 32120.469, 'duration': 6.844}, {'end': 32134.078, 'text': 'Yeah, so the answer is using plus operator, no, but there is a way using update method, great.', 'start': 32128.354, 'duration': 5.724}, {'end': 32139.204, 'text': 'So next we focus on the copy function.', 'start': 32135.123, 'duration': 4.081}, {'end': 32141.745, 'text': 'The copy function is available for list.', 'start': 32139.725, 'duration': 2.02}, {'end': 32143.726, 'text': 'The copy function is available for set.', 'start': 32141.865, 'duration': 1.861}, {'end': 32146.267, 'text': 'The copy function is available for dictionary.', 'start': 32144.286, 'duration': 1.981}, {'end': 32150.628, 'text': "So let's see the need of this copy function.", 'start': 32148.027, 'duration': 2.601}, {'end': 32156.39, 'text': "Here I want you to be very careful because that's really important.", 'start': 32150.988, 'duration': 5.402}, {'end': 32159.331, 'text': "Let's say we have a list.", 'start': 32158.271, 'duration': 1.06}, {'end': 32161.552, 'text': "Let's say that's list.", 'start': 32159.971, 'duration': 1.581}], 'summary': 'Using the update method, we can insert a new dictionary inside a dictionary. the copy function is available for list, set, and dictionary.', 'duration': 52.749, 'max_score': 32108.803, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI32108803.jpg'}], 'start': 30175.097, 'title': 'Python data structures and string handling', 'summary': 'Covers the basics of string handling, data structures (lists, tuples, sets, dictionaries) in python, their properties, applications, insertion/deletion methods, and concatenation. it also emphasizes the absence of escape sequences in string handling and the importance of copying to avoid referencing.', 'chapters': [{'end': 30221.736, 'start': 30175.097, 'title': 'String handling basics', 'summary': 'Covers the basics of string handling, emphasizing the absence of escape sequences, and encourages further exploration of string functions and manipulation.', 'duration': 46.639, 'highlights': ['The chapter emphasizes the absence of escape sequences in string handling, providing a foundational understanding of string manipulation.', 'The speaker encourages further exploration of string functions and manipulation, highlighting the importance of understanding additional ways to work with strings.', 'The speaker suggests seeking information on string functions and manipulation based on specific requirements, promoting independent research and learning.']}, {'end': 30763.822, 'start': 30222.237, 'title': 'Data structures in python', 'summary': 'Discusses the basic data structures in python including lists, tuples, sets, and dictionaries, highlighting their properties and applications, and emphasizing their use in solving various problems. the chapter also sets the stage for exploring these data structures in the upcoming videos.', 'duration': 541.585, 'highlights': ['The chapter discusses the basic data structures in Python including lists, tuples, sets, and dictionaries, highlighting their properties and applications, and emphasizing their use in solving various problems.', 'The chapter also sets the stage for exploring these data structures in the upcoming videos.', 'Lists, tuples, sets, and dictionaries are the basic data structures in Python and are applicable to almost all the problems.']}, {'end': 31493.222, 'start': 30763.822, 'title': 'Python data structures basics', 'summary': 'Covers the basics of python data structures, including lists, tuples, sets, and dictionaries, and their indexing methods, with a focus on accessing elements and their corresponding types, preparing for further exploration in data science packages.', 'duration': 729.4, 'highlights': ['The chapter covers the basics of Python data structures, including lists, tuples, sets, and dictionaries.', 'The indexing methods of lists and tuples are explained, emphasizing their similarity to string indexing.', 'The types of elements within the data structures are demonstrated through printing and accessing them.']}, {'end': 32063.565, 'start': 31493.222, 'title': 'Inserting and deleting elements in python data structures', 'summary': 'Explores the process of inserting and deleting elements in different python data structures, including lists, tuples, sets, and dictionaries, detailing the methods and functions available for each, and hinting at the possibility of concatenating dictionaries using the plus operator.', 'duration': 570.343, 'highlights': ['You can insert elements to a list using the add operator or the append function, with the latter being faster in some cases.', 'Tuples are immutable, and while you cannot insert or delete elements from a tuple, you can concatenate two tuples together using the plus operator to create a new tuple.', 'Sets allow element insertion using the add function for single elements and the update function for multiple elements, and it is possible to remove elements using the remove function.', 'Dictionaries support the insertion of a new key-value pair using the assignment operator, and elements can be removed using the del command or specific methods like remove for sets and dictionaries.', 'The possibility of concatenating dictionaries using the plus operator is hinted at, challenging the viewer to explore this in the next video.']}, {'end': 32754.217, 'start': 32064.395, 'title': 'Dictionary concatenation and copy function', 'summary': 'Discusses concatenating dictionaries, using the update method, and the copy function for lists, sets, and dictionaries, emphasizing the importance of copying to avoid referencing and the difference between slicing in python and numpy arrays.', 'duration': 689.822, 'highlights': ['The chapter discusses concatenating dictionaries and the update method, emphasizing the importance of using the update method instead of the plus operator, and highlights that the plus operator is not defined for dictionaries.', 'The chapter explains the copy function for lists, sets, and dictionaries, emphasizing the importance of using the copy function to avoid referencing and memory consumption.', 'The chapter discusses slicing in Python and the importance of understanding that slicing creates a copy by default, and emphasizes the difference between slicing in Python and NumPy arrays.']}], 'duration': 2579.12, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI30175097.jpg', 'highlights': ['The chapter covers the basics of Python data structures, including lists, tuples, sets, and dictionaries.', 'The chapter discusses concatenating dictionaries and the update method, emphasizing the importance of using the update method instead of the plus operator.', 'The chapter explains the copy function for lists, sets, and dictionaries, emphasizing the importance of using the copy function to avoid referencing and memory consumption.', 'You can insert elements to a list using the add operator or the append function, with the latter being faster in some cases.', 'The indexing methods of lists and tuples are explained, emphasizing their similarity to string indexing.']}, {'end': 34494.613, 'segs': [{'end': 32778.648, 'src': 'embed', 'start': 32755.237, 'weight': 2, 'content': [{'end': 32762.442, 'text': 'Or, if you give an index, it will remove that value at that index and it will, after removing it, will return you that,', 'start': 32755.237, 'duration': 7.205}, {'end': 32764.203, 'text': 'so you can use it wherever you want.', 'start': 32762.442, 'duration': 1.761}, {'end': 32767.201, 'text': 'So there are many more functions.', 'start': 32765.2, 'duration': 2.001}, {'end': 32769.423, 'text': 'For example, you can see all of them one by one.', 'start': 32767.241, 'duration': 2.182}, {'end': 32771.284, 'text': 'Remove function, for example, reverse.', 'start': 32769.463, 'duration': 1.821}, {'end': 32774.586, 'text': 'Reverse like the name suggests.', 'start': 32771.343, 'duration': 3.243}, {'end': 32778.648, 'text': 'If you call the reverse function, the list will be reversed.', 'start': 32775.226, 'duration': 3.422}], 'summary': 'Python list functions include remove, reverse, and more.', 'duration': 23.411, 'max_score': 32755.237, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI32755237.jpg'}, {'end': 32943.006, 'src': 'embed', 'start': 32893.623, 'weight': 1, 'content': [{'end': 32901.61, 'text': 'The purpose here is to tell you what kind of data structure has what kind of properties and what are the similarities and differences in between.', 'start': 32893.623, 'duration': 7.987}, {'end': 32910.797, 'text': 'So if you remember this one slide for list, tuple set and dictionary and some text that is written out above,', 'start': 32902.29, 'duration': 8.507}, {'end': 32918.343, 'text': "you'll be having very good knowledge of where to pick what kind of data structure in practice.", 'start': 32910.797, 'duration': 7.546}, {'end': 32932.843, 'text': "So in the next video I'll be actually going to Jupyter Notebook as our style and I will be coding or solving some problem for you.", 'start': 32919.978, 'duration': 12.865}, {'end': 32938.184, 'text': 'that will involve list, tuple set or dictionary, or one of them, or we will be choosing, based on problem,', 'start': 32932.843, 'duration': 5.341}, {'end': 32941.586, 'text': 'what kind of data structure is well and what.', 'start': 32938.184, 'duration': 3.402}, {'end': 32943.006, 'text': "So we'll be doing that.", 'start': 32942.146, 'duration': 0.86}], 'summary': 'Learn about data structures and their applications in practice for problem solving.', 'duration': 49.383, 'max_score': 32893.623, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI32893623.jpg'}, {'end': 33273.973, 'src': 'embed', 'start': 33244.25, 'weight': 10, 'content': [{'end': 33257.082, 'text': 'for example, list of all the squares till till starting from zero, list of all the squares till till 10, for example, 0 square, 1 square, 2 square.', 'start': 33244.25, 'duration': 12.832}, {'end': 33258.963, 'text': "let's say we want a list of that.", 'start': 33257.082, 'duration': 1.881}, {'end': 33262.886, 'text': 'so one way of doing that is a quick shortcut, is to just use loops.', 'start': 33258.963, 'duration': 3.923}, {'end': 33273.973, 'text': 'so in loops, for example, we write okay x square for x in range 10, for example.', 'start': 33262.886, 'duration': 11.087}], 'summary': 'Demonstrating the use of loops for generating a list of squares up to 10.', 'duration': 29.723, 'max_score': 33244.25, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI33244250.jpg'}, {'end': 33406.148, 'src': 'embed', 'start': 33300.138, 'weight': 0, 'content': [{'end': 33318.017, 'text': "for example, let's say you want to make a set of all the squares for X in range, let's say, starting from starting from 2, ending at 20,", 'start': 33300.138, 'duration': 17.879}, {'end': 33321.538, 'text': "and you want to take a step of, let's say, three.", 'start': 33318.017, 'duration': 3.521}, {'end': 33332.285, 'text': 'so start from index to go till 20, do not include 20, but take the step of three and you can now have a set, which is which is this?', 'start': 33321.538, 'duration': 10.747}, {'end': 33336.667, 'text': 'i mean, uh, there are, there are a lot of ways of working these, working with these.', 'start': 33332.285, 'duration': 4.382}, {'end': 33341.473, 'text': 'uh, One can explore more and more about these things.', 'start': 33336.667, 'duration': 4.806}, {'end': 33345.614, 'text': 'but what the basic thing about these data structures are?', 'start': 33341.473, 'duration': 4.141}, {'end': 33347.136, 'text': 'they are very, very abstract.', 'start': 33345.614, 'duration': 1.522}, {'end': 33354.961, 'text': 'They can I mean a list can contain a dictionary and that dictionary can contain a tuple and that tuple can have an element, which is another list,', 'start': 33347.697, 'duration': 7.264}, {'end': 33355.421, 'text': 'and so on.', 'start': 33354.961, 'duration': 0.46}, {'end': 33358.103, 'text': 'It is that abstract.', 'start': 33356.942, 'duration': 1.161}, {'end': 33360.905, 'text': 'It allows you to do each and everything in that way.', 'start': 33358.163, 'duration': 2.742}, {'end': 33363.718, 'text': 'Okay, so I end this video here.', 'start': 33361.936, 'duration': 1.782}, {'end': 33371.064, 'text': 'In the next video, we will actually solve a problem using one of these data structures, or we will try to choose one of those.', 'start': 33363.799, 'duration': 7.265}, {'end': 33380.93, 'text': 'And that video may be lengthy, may be small, because we may have bugs inside, and we will play around with these data structures in the next video.', 'start': 33371.663, 'duration': 9.267}, {'end': 33389.974, 'text': "So do attend the next video, because It's really the practice and you will get your hands.", 'start': 33381.591, 'duration': 8.383}, {'end': 33398.425, 'text': 'you will get a very good grip on the data structures in solving the next problem that we are launching for you.', 'start': 33389.974, 'duration': 8.451}, {'end': 33400.487, 'text': 'Okay, hope to see you in the next video.', 'start': 33398.845, 'duration': 1.642}, {'end': 33406.148, 'text': "Okay, let's see a problem just to get comfortable with these data structures.", 'start': 33400.928, 'duration': 5.22}], 'summary': 'Introduction to abstract data structures and upcoming problem-solving exercises.', 'duration': 106.01, 'max_score': 33300.138, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI33300138.jpg'}, {'end': 33597.539, 'src': 'embed', 'start': 33567.83, 'weight': 4, 'content': [{'end': 33575.134, 'text': 'For example, if a student have taken five subjects, then the marks for all the five subjects are available.', 'start': 33567.83, 'duration': 7.304}, {'end': 33579.775, 'text': "You just add all the marks and divide by five, and that's, let's say, the average marks.", 'start': 33575.194, 'duration': 4.581}, {'end': 33591.638, 'text': "So first of all, let's write a way to compute, for example, to just collect the data, how to collect the data.", 'start': 33581.315, 'duration': 10.323}, {'end': 33594.138, 'text': "So let's write a function for that.", 'start': 33592.278, 'duration': 1.86}, {'end': 33597.539, 'text': "So let's say define a function.", 'start': 33594.659, 'duration': 2.88}], 'summary': 'Demonstrates computation of average marks for five subjects.', 'duration': 29.709, 'max_score': 33567.83, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI33567830.jpg'}], 'start': 32755.237, 'title': 'Python data structures', 'summary': 'Discusses functions and properties of data structures like list, tuple, set, and dictionary, preparing for problem-solving. it also covers the use of these structures in python, including creating/accessing elements and computing student averages with examples yielding averages of 38 and 49.2.', 'chapters': [{'end': 33024.563, 'start': 32755.237, 'title': 'Data structure functions and properties', 'summary': 'Highlights the various functions of different data structures, such as list, tuple, set, and dictionary, and emphasizes their abstract nature, preparing for problem-solving in upcoming videos.', 'duration': 269.326, 'highlights': ['The chapter emphasizes the abstract nature of data structures, illustrating their ability to contain various types of items and nested structures.', 'The chapter discusses the functions of different data structures, including list, tuple, set, and dictionary, highlighting their properties and similarities.', 'The chapter provides a glimpse into the upcoming problem-solving sessions in Jupyter Notebook, focusing on utilizing different data structures for efficient solutions.', 'The chapter explains specific functions of data structures, such as remove, reverse, add, clear, copy, and items, providing insights into their practical usage.']}, {'end': 33332.285, 'start': 33026.065, 'title': 'Python data structures', 'summary': 'Discusses the use of various data structures such as lists, tuples, sets, and dictionaries in python, including examples of creating and accessing elements, as well as shortcuts for list and set creation using loops.', 'duration': 306.22, 'highlights': ['Accessing and manipulating elements in lists, tuples, sets, and dictionaries, including examples of creating a dictionary with different data types as values and accessing nested elements within the data structures.', 'Creating a list of squares using a shortcut with loops, demonstrating the use of list comprehensions for quick list creation.', 'Demonstrating the creation of a set of squares with specified range and step using a set comprehension.']}, {'end': 33872.847, 'start': 33332.285, 'title': 'Understanding abstract data structures', 'summary': 'Highlights the abstract nature of data structures, the upcoming problem-solving session using these structures, and the process of collecting and computing student data for average marks.', 'duration': 540.562, 'highlights': ['The abstract nature of data structures allows for complex nesting, such as a list containing a dictionary, and so on, enabling versatile usage for solving various problems.', 'The upcoming problem-solving session using these data structures will provide practical experience and a strong grasp on solving problems, presenting a valuable opportunity for learners.', 'The process of collecting and computing student data for average marks involves creating a function to gather data, validating student IDs, and organizing marks into a dictionary for further computations.']}, {'end': 34494.613, 'start': 33872.847, 'title': 'Computing student marks and averages', 'summary': 'Illustrates a python program to collect student data, compute average marks for each student, and handle errors, resulting in average marks of 38 for student 12 and 49.2 for student 45.', 'duration': 621.766, 'highlights': ['The chapter demonstrates a Python program to collect student data from the user, process it to compute average marks for individual students, and handle errors, resulting in average marks of 38 for student 12 and 49.2 for student 45.', 'The program allows the user to input student IDs and their respective marks, iterates through the data, and calculates the average marks for each student, with student 45 achieving an average of 49.2.']}], 'duration': 1739.376, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI32755237.jpg', 'highlights': ['The chapter emphasizes the abstract nature of data structures, illustrating their ability to contain various types of items and nested structures.', 'The chapter discusses the functions of different data structures, including list, tuple, set, and dictionary, highlighting their properties and similarities.', 'The chapter explains specific functions of data structures, such as remove, reverse, add, clear, copy, and items, providing insights into their practical usage.', 'Accessing and manipulating elements in lists, tuples, sets, and dictionaries, including examples of creating a dictionary with different data types as values and accessing nested elements within the data structures.', 'The process of collecting and computing student data for average marks involves creating a function to gather data, validating student IDs, and organizing marks into a dictionary for further computations.', 'The chapter provides a glimpse into the upcoming problem-solving sessions in Jupyter Notebook, focusing on utilizing different data structures for efficient solutions.', 'The abstract nature of data structures allows for complex nesting, such as a list containing a dictionary, and so on, enabling versatile usage for solving various problems.', 'The upcoming problem-solving session using these data structures will provide practical experience and a strong grasp on solving problems, presenting a valuable opportunity for learners.', 'The program allows the user to input student IDs and their respective marks, iterates through the data, and calculates the average marks for each student, with student 45 achieving an average of 49.2.', 'The chapter demonstrates a Python program to collect student data from the user, process it to compute average marks for individual students, and handle errors, resulting in average marks of 38 for student 12 and 49.2 for student 45.', 'Creating a list of squares using a shortcut with loops, demonstrating the use of list comprehensions for quick list creation.', 'Demonstrating the creation of a set of squares with specified range and step using a set comprehension.']}, {'end': 36582.377, 'segs': [{'end': 34680.966, 'src': 'embed', 'start': 34657.922, 'weight': 0, 'content': [{'end': 34666.327, 'text': 'I mean it is efficient with respect to memory, because if the type is same, we need not to save information about each element,', 'start': 34657.922, 'duration': 8.405}, {'end': 34671.514, 'text': 'because we need just to save the information about the type, because the type is same for all elements.', 'start': 34666.327, 'duration': 5.187}, {'end': 34677.982, 'text': 'Further, when the type is same, we can write functions that are much more faster than a list.', 'start': 34672.094, 'duration': 5.888}, {'end': 34680.966, 'text': 'So NumPy is very, very popular.', 'start': 34678.523, 'duration': 2.443}], 'summary': 'Numpy is efficient with memory and allows for faster functions due to same type, making it very popular.', 'duration': 23.044, 'max_score': 34657.922, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI34657922.jpg'}, {'end': 34742.75, 'src': 'embed', 'start': 34709.586, 'weight': 3, 'content': [{'end': 34712.287, 'text': 'Although you can have a NumPy array with.', 'start': 34709.586, 'duration': 2.701}, {'end': 34717.812, 'text': 'with string data types, I mean all the strings or all general objects as well,', 'start': 34713.388, 'duration': 4.424}, {'end': 34726.979, 'text': 'but the power of NumPy array will become much more evident when we will be working on numeric type data.', 'start': 34717.812, 'duration': 9.167}, {'end': 34736.526, 'text': 'So in this particular course, we will focus more on numeric data than other kind of data.', 'start': 34727.419, 'duration': 9.107}, {'end': 34741.229, 'text': "That's how you write import.", 'start': 34739.448, 'duration': 1.781}, {'end': 34742.75, 'text': 'NumPy is installed.', 'start': 34741.709, 'duration': 1.041}], 'summary': 'Numpy array is powerful for numeric data. course focuses on numeric data.', 'duration': 33.164, 'max_score': 34709.586, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI34709586.jpg'}, {'end': 34861.459, 'src': 'embed', 'start': 34828.573, 'weight': 2, 'content': [{'end': 34831.876, 'text': 'We can also define the array using a tuple rather than a list.', 'start': 34828.573, 'duration': 3.303}, {'end': 34837.541, 'text': "It's our choice which way we define the array.", 'start': 34832.456, 'duration': 5.085}, {'end': 34841.802, 'text': 'Either way, 2, 3, 5.', 'start': 34837.841, 'duration': 3.961}, {'end': 34844.587, 'text': "Let's say that's another array, for example.", 'start': 34841.804, 'duration': 2.783}, {'end': 34855.975, 'text': 'So if we print, for example, a, it will give us a, but if we just see the type of a, it will no longer be a list.', 'start': 34845.007, 'duration': 10.968}, {'end': 34860.138, 'text': "It will be an nd array, numpy.nd array, that's an n-dimensional array.", 'start': 34856.135, 'duration': 4.003}, {'end': 34861.459, 'text': 'Okay, great.', 'start': 34860.918, 'duration': 0.541}], 'summary': 'Arrays can be defined using tuple or list. numpy creates n-dimensional arrays.', 'duration': 32.886, 'max_score': 34828.573, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI34828573.jpg'}, {'end': 35030.464, 'src': 'embed', 'start': 35000.138, 'weight': 4, 'content': [{'end': 35008.382, 'text': 'And that store actually, that actually stores the information of the data type of the elements of the array of NP array.', 'start': 35000.138, 'duration': 8.244}, {'end': 35013.184, 'text': 'Remember NP array, all the elements of NP array, they must have same data type.', 'start': 35008.882, 'duration': 4.302}, {'end': 35017.066, 'text': 'It cannot store heterogeneous arrays as it is.', 'start': 35014.365, 'duration': 2.701}, {'end': 35024.681, 'text': "Okay, now there's another property sometimes called the dimensions or ndim.", 'start': 35018.638, 'duration': 6.043}, {'end': 35030.464, 'text': 'That tells actually what are the dimensions of the array.', 'start': 35025.822, 'duration': 4.642}], 'summary': 'Np array stores data type and dimensions, ensuring homogeneous arrays.', 'duration': 30.326, 'max_score': 35000.138, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI35000138.jpg'}, {'end': 35518.393, 'src': 'embed', 'start': 35493.255, 'weight': 5, 'content': [{'end': 35502.88, 'text': 'The problem is when you are going to define multi-dimensional arrays, the number of elements for each dimension, they should stay consistent.', 'start': 35493.255, 'duration': 9.625}, {'end': 35509.304, 'text': 'For example, if the first array has three elements, the second array must have three elements.', 'start': 35502.9, 'duration': 6.404}, {'end': 35513.168, 'text': 'or If the second array has four elements, then the first must have four elements.', 'start': 35509.304, 'duration': 3.864}, {'end': 35518.393, 'text': 'If that is not the case, the array will not be defined like a multidimensional array.', 'start': 35513.628, 'duration': 4.765}], 'summary': 'In defining multi-dimensional arrays, each dimension must have consistent number of elements.', 'duration': 25.138, 'max_score': 35493.255, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI35493255.jpg'}, {'end': 35767.055, 'src': 'embed', 'start': 35738.04, 'weight': 6, 'content': [{'end': 35744.864, 'text': 'Wow So that is basically, And by the way, you can make a four-dimensional array.', 'start': 35738.04, 'duration': 6.824}, {'end': 35749.787, 'text': 'A four-dimensional array will be an array of three-dimensional arrays and so on.', 'start': 35745.225, 'duration': 4.562}, {'end': 35761.412, 'text': "You can make, for example, n-dimensional arrays, and that's one reason why we call this as ndArray, n-dimensional array.", 'start': 35750.907, 'duration': 10.505}, {'end': 35764.174, 'text': 'The type of C is ndArray, n-dimensional array.', 'start': 35761.993, 'duration': 2.181}, {'end': 35767.055, 'text': 'You can add as many dimensions as you want.', 'start': 35765.014, 'duration': 2.041}], 'summary': 'Ndarray allows creation of n-dimensional arrays with unlimited dimensions.', 'duration': 29.015, 'max_score': 35738.04, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI35738040.jpg'}, {'end': 35822.774, 'src': 'embed', 'start': 35796.204, 'weight': 7, 'content': [{'end': 35803.527, 'text': 'Okay, in the last video we discussed this number of dimensions or ndim property of any NumPy array,', 'start': 35796.204, 'duration': 7.323}, {'end': 35808.268, 'text': 'and we also saw an example of defining a three-dimensional array in Jupyter Notebook.', 'start': 35803.527, 'duration': 4.741}, {'end': 35814.15, 'text': "Let's discuss another property which is the shape property.", 'start': 35810.269, 'duration': 3.881}, {'end': 35818.192, 'text': "Let's see what this shape actually represents.", 'start': 35814.591, 'duration': 3.601}, {'end': 35822.774, 'text': "So, let's go to Jupyter Notebook and see what actually this shape represents.", 'start': 35818.892, 'duration': 3.882}], 'summary': 'Numpy array properties discussed, including ndim and shape.', 'duration': 26.57, 'max_score': 35796.204, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI35796204.jpg'}, {'end': 36110.469, 'src': 'embed', 'start': 36082.623, 'weight': 9, 'content': [{'end': 36090.15, 'text': 'For example, what if you want to create an array containing all zeros? So there is a function in NumPy, np.zeros.', 'start': 36082.623, 'duration': 7.527}, {'end': 36092.673, 'text': 'that tells you how to do that.', 'start': 36090.771, 'duration': 1.902}, {'end': 36102.221, 'text': 'Similarly, if you want to generate an array containing a lot of ones or all ones, there is a function to do that and stuff like so.', 'start': 36092.733, 'duration': 9.488}, {'end': 36107.506, 'text': 'There are some functions that are actually used a lot and I want to discuss those.', 'start': 36103.302, 'duration': 4.204}, {'end': 36110.469, 'text': 'One function is np.arrange.', 'start': 36108.587, 'duration': 1.882}], 'summary': 'Numpy provides functions like np.zeros and np.arrange for creating arrays with specific values.', 'duration': 27.846, 'max_score': 36082.623, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI36082623.jpg'}, {'end': 36170.074, 'src': 'embed', 'start': 36140.681, 'weight': 1, 'content': [{'end': 36148.426, 'text': "So that's an array, that's a quick way to create an array with all the numbers till 100.", 'start': 36140.681, 'duration': 7.745}, {'end': 36158.651, 'text': "Yeah, so let's see a running example of this np.arrange method in Jupyter Notebook just to get a better look and feel of how it works.", 'start': 36148.426, 'duration': 10.225}, {'end': 36159.952, 'text': "So let's see.", 'start': 36159.271, 'duration': 0.681}, {'end': 36165.054, 'text': "So let's say we have a equals np.arrange.", 'start': 36161.773, 'duration': 3.281}, {'end': 36169.533, 'text': "And let's say 100.", 'start': 36167.85, 'duration': 1.683}, {'end': 36170.074, 'text': "So that's it.", 'start': 36169.533, 'duration': 0.541}], 'summary': 'Demonstrating np.arrange method to create array with numbers till 100 in jupyter notebook.', 'duration': 29.393, 'max_score': 36140.681, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI36140681.jpg'}, {'end': 36492.369, 'src': 'embed', 'start': 36463.286, 'weight': 8, 'content': [{'end': 36464.546, 'text': 'that are just random arrays.', 'start': 36463.286, 'duration': 1.26}, {'end': 36469.149, 'text': 'Just to test your code, just to test how it works on any kind of array.', 'start': 36464.947, 'duration': 4.202}, {'end': 36478.015, 'text': 'In that case, one way of getting a shuffled kind of array, one quick way is to just use np.random.permutation function.', 'start': 36469.529, 'duration': 8.486}, {'end': 36482.279, 'text': 'The np.random package does not only have this permutation.', 'start': 36479.276, 'duration': 3.003}, {'end': 36483.6, 'text': 'There are a lot of other functions.', 'start': 36482.319, 'duration': 1.281}, {'end': 36485.042, 'text': 'np.random for example.', 'start': 36483.76, 'duration': 1.282}, {'end': 36492.369, 'text': 'np.random.randint for example.', 'start': 36485.542, 'duration': 6.827}], 'summary': 'Testing code with np.random package for array shuffling and other functions.', 'duration': 29.083, 'max_score': 36463.286, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI36463286.jpg'}], 'start': 34494.613, 'title': 'Numpy for data science', 'summary': 'Introduces the numpy package for data science, highlighting its efficiency in handling numerical data, properties and dimensions of numpy arrays, accessing and understanding multidimensional arrays, ndarray and shape property, and introduction to numpy functions for creating arrays.', 'chapters': [{'end': 34951.248, 'start': 34494.613, 'title': 'Introduction to numpy for data science', 'summary': 'Introduces the numpy package for data science, highlighting its efficiency in handling numerical data, the process of defining arrays using numpy, and the automatic data type inference, with a focus on numeric data.', 'duration': 456.635, 'highlights': ['NumPy is much faster than List due to its efficiency in handling homogeneous data types, making it very popular for numerical Python, with a focus on numeric data.', 'The process of defining arrays using NumPy, either through lists or tuples, and viewing the type of the defined arrays as nd array, showcasing its flexibility for data manipulation.', 'Automatically inferring the data type of arrays in NumPy, with the option to specify the data type, showcasing the dynamic typing feature of NumPy.']}, {'end': 35340.745, 'start': 34951.408, 'title': 'Numpy array properties and dimensions', 'summary': 'Introduces the properties of numpy arrays including the data type and dimensions, with examples of one, two, and three-dimensional arrays, and explains how to access elements using indices.', 'duration': 389.337, 'highlights': ['Numpy array properties include D type for data type and ndim for dimensions, with all elements requiring the same data type.', 'One-dimensional arrays require one index to access elements, while two-dimensional arrays require two indices and three-dimensional arrays require three indices.', 'The example demonstrates a two-dimensional array and its ndim property is validated as two, indicating two dimensions.']}, {'end': 35675.696, 'start': 35340.745, 'title': 'Accessing multidimensional arrays', 'summary': 'Explains how to access elements in multidimensional arrays, the consistency required for defining multidimensional arrays, and provides examples of two and three-dimensional arrays in python using np.array.', 'duration': 334.951, 'highlights': ['Multidimensional arrays are accessed by specifying the indices corresponding to each dimension, with consistency required in the number of elements for each dimension.', 'Consistency in the number of elements for each dimension is crucial for defining multidimensional arrays, ensuring that arrays are accessed correctly.', 'Examples of two and three-dimensional arrays in Python using np.array are provided, demonstrating the structure and consistency required for multidimensional arrays.']}, {'end': 36035.129, 'start': 35675.696, 'title': 'Understanding ndarray and shape property', 'summary': 'Covers the concept of ndarray and shape property in numpy, including examples of accessing elements in a multidimensional array, defining dimensions, and exploring properties like size and n bytes.', 'duration': 359.433, 'highlights': ['NumPy arrays can have multiple dimensions, such as 2D, 3D, and even nD arrays, allowing for flexible data representation.', 'The shape property of a NumPy array returns a tuple representing the dimensions of the array, e.g., for a 3D array with 2 arrays of 2D, each containing 3 1D arrays with 3 elements, the shape would be (2, 3, 3).', 'NumPy allows the creation of 0D arrays with a single element, which can be concatenated to form higher-dimensional arrays.', 'Properties like size and n bytes provide valuable information about the array, such as the total number of elements and the memory consumption.']}, {'end': 36582.377, 'start': 36035.129, 'title': 'Introduction to numpy functions', 'summary': 'Introduces numpy functions for creating arrays, including np.zeros to create an array of zeros, np.arrange for creating arrays with specified ranges and steps, and np.random.permutation to shuffle array elements, showcasing the efficiency and practicality of numpy functions.', 'duration': 547.248, 'highlights': ["The np.arrange function quickly creates an array with specified ranges and steps, such as creating a 1D array starting from 0 up to 99, showcasing NumPy's efficiency in array generation.", 'The np.random.permutation function shuffles array elements in a random order, providing a quick way to create randomized arrays for testing code, adding practicality to array manipulation in NumPy.', 'Introduction to np.zeros for creating arrays filled with zeros, demonstrating the diversity of array creation functions in NumPy.']}], 'duration': 2087.764, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI34494613.jpg', 'highlights': ['NumPy is much faster than List due to its efficiency in handling homogeneous data types, making it very popular for numerical Python, with a focus on numeric data.', "The np.arrange function quickly creates an array with specified ranges and steps, such as creating a 1D array starting from 0 up to 99, showcasing NumPy's efficiency in array generation.", 'The process of defining arrays using NumPy, either through lists or tuples, and viewing the type of the defined arrays as nd array, showcasing its flexibility for data manipulation.', 'Automatically inferring the data type of arrays in NumPy, with the option to specify the data type, showcasing the dynamic typing feature of NumPy.', 'Numpy array properties include D type for data type and ndim for dimensions, with all elements requiring the same data type.', 'Multidimensional arrays are accessed by specifying the indices corresponding to each dimension, with consistency required in the number of elements for each dimension.', 'NumPy arrays can have multiple dimensions, such as 2D, 3D, and even nD arrays, allowing for flexible data representation.', 'The shape property of a NumPy array returns a tuple representing the dimensions of the array, e.g., for a 3D array with 2 arrays of 2D, each containing 3 1D arrays with 3 elements, the shape would be (2, 3, 3).', 'The np.random.permutation function shuffles array elements in a random order, providing a quick way to create randomized arrays for testing code, adding practicality to array manipulation in NumPy.', 'Introduction to np.zeros for creating arrays filled with zeros, demonstrating the diversity of array creation functions in NumPy.']}, {'end': 38031.726, 'segs': [{'end': 36635.279, 'src': 'embed', 'start': 36603.472, 'weight': 2, 'content': [{'end': 36617.281, 'text': "that's a very useful function to just create a testing array and just see output of a particular operation or algorithm just on different kind of arrays.", 'start': 36603.472, 'duration': 13.809}, {'end': 36621.344, 'text': 'Further, we saw permutation function in np.random package.', 'start': 36617.842, 'duration': 3.502}, {'end': 36635.279, 'text': 'And we saw that this permutation function actually it reshuffles, it shuffles different kind of.', 'start': 36624.767, 'duration': 10.512}], 'summary': 'Demonstrated the usefulness of testing arrays and the np.random permutation function.', 'duration': 31.807, 'max_score': 36603.472, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI36603472.jpg'}, {'end': 36688.235, 'src': 'embed', 'start': 36657.32, 'weight': 1, 'content': [{'end': 36667.167, 'text': "for example, if you have an array, let's say array is, let's say, we have an array with, let's say, 10 elements,", 'start': 36657.32, 'duration': 9.847}, {'end': 36681.329, 'text': "and if we call a.reshape and we give, let's say, two by five, so it will make a two-dimensional array out of a, which is b, and that will be a,", 'start': 36667.167, 'duration': 14.162}, {'end': 36688.235, 'text': 'two by five matrix, or that will be an array or a matrix with two rows and five columns.', 'start': 36681.329, 'duration': 6.906}], 'summary': 'Using the reshape function, an array with 10 elements can be transformed into a 2x5 matrix.', 'duration': 30.915, 'max_score': 36657.32, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI36657320.jpg'}, {'end': 36919.872, 'src': 'embed', 'start': 36892.838, 'weight': 0, 'content': [{'end': 36898.522, 'text': 'It can create different kind of random numbers following from different distributions.', 'start': 36892.838, 'duration': 5.684}, {'end': 36902.023, 'text': 'and doing in machine learning or in statistics.', 'start': 36899.382, 'duration': 2.641}, {'end': 36905.705, 'text': 'sometimes we need to generate these kind of random numbers.', 'start': 36902.023, 'duration': 3.682}, {'end': 36911.868, 'text': 'uh, for sometimes for testing purposes, sometimes for adding noise of a particular type to test our model and stuff like.', 'start': 36905.705, 'duration': 6.163}, {'end': 36916.97, 'text': 'so. so it is good to have a good grip on np dot random package.', 'start': 36911.868, 'duration': 5.102}, {'end': 36919.872, 'text': 'okay, um, next we see reshape function.', 'start': 36916.97, 'duration': 2.902}], 'summary': 'Np.random generates random numbers for testing and noise in ml/statistics.', 'duration': 27.034, 'max_score': 36892.838, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI36892838.jpg'}, {'end': 37073.249, 'src': 'embed', 'start': 37046.39, 'weight': 10, 'content': [{'end': 37053.673, 'text': 'Yeah, So sometimes we want to work on matrices and we just we can just plug in these, arrange,', 'start': 37046.39, 'duration': 7.283}, {'end': 37062.298, 'text': 'function to generate a bunch of numbers and then we can reshape those and build a matrix quickly and then just test the performance of our algorithm or our stuff like so.', 'start': 37053.673, 'duration': 8.625}, {'end': 37073.249, 'text': 'uh. so not only the reshape not only returns the uh, the i mean you can.', 'start': 37063.298, 'duration': 9.951}], 'summary': 'Matrix manipulation for quick algorithm testing.', 'duration': 26.859, 'max_score': 37046.39, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI37046390.jpg'}, {'end': 37287.452, 'src': 'embed', 'start': 37256.59, 'weight': 4, 'content': [{'end': 37262.693, 'text': 'If you slice that thing from NumPy, then B is not a copy.', 'start': 37256.59, 'duration': 6.103}, {'end': 37267.536, 'text': 'It is actually accessing the same memory view as in A.', 'start': 37263.034, 'duration': 4.502}, {'end': 37275.522, 'text': 'Now if you change any element in B, the corresponding element in A will change as long as A is a NumPy array.', 'start': 37268.076, 'duration': 7.446}, {'end': 37287.452, 'text': 'However, if A is a list or any other data structure, ordinary data structure, then the slicing, this kind of slice, gives a copy rather than a view.', 'start': 37275.943, 'duration': 11.509}], 'summary': 'Slicing a numpy array gives a view, not a copy, allowing changes to propagate to the original array.', 'duration': 30.862, 'max_score': 37256.59, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI37256590.jpg'}, {'end': 37495.67, 'src': 'embed', 'start': 37473.258, 'weight': 5, 'content': [{'end': 37481.642, 'text': 'One thing, if you are not going to change elements, the numpy supplies you very fast implementation of slicing by not changing the memory view.', 'start': 37473.258, 'duration': 8.384}, {'end': 37485.904, 'text': 'If you are aware, your algorithm is not going to change the elements.', 'start': 37481.862, 'duration': 4.042}, {'end': 37487.405, 'text': 'slicing will give you much,', 'start': 37485.904, 'duration': 1.501}, {'end': 37495.67, 'text': 'much efficient access to the elements or the sub-blocks or sub-arrays without actually making the copies inside the memory,', 'start': 37487.405, 'duration': 8.265}], 'summary': 'Numpy provides efficient slicing for fast access to elements without memory changes.', 'duration': 22.412, 'max_score': 37473.258, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI37473258.jpg'}, {'end': 37734.847, 'src': 'embed', 'start': 37667.894, 'weight': 6, 'content': [{'end': 37672.619, 'text': 'Let me see, np.indices returns an array representing the indices of a grid.', 'start': 37667.894, 'duration': 4.725}, {'end': 37680.807, 'text': 'Okay, so I have to give a grid, and then it returns, for example, the indices of all that grid.', 'start': 37673.32, 'duration': 7.487}, {'end': 37686.544, 'text': 'How can I use that? Well, it becomes difficult.', 'start': 37681.621, 'duration': 4.923}, {'end': 37701.213, 'text': 'There may be a find function or how can you locate the index where the minus 200 is located? How can I do that? Yeah, very difficult.', 'start': 37687.124, 'duration': 14.089}, {'end': 37702.514, 'text': 'Seems like very difficult.', 'start': 37701.293, 'duration': 1.221}, {'end': 37718.72, 'text': "Oh, why don't I, rather than finding out a function, Why don't I just play with numpy? Why not? So let's say a equal equals minus 1200.", 'start': 37702.694, 'duration': 16.026}, {'end': 37725.343, 'text': 'That gives me a Boolean array comparing each and every element with minus 1200.', 'start': 37718.72, 'duration': 6.623}, {'end': 37734.847, 'text': "So the returning array, let me call the index array or the Boolean array, let's say b, that array is true or false array or zero or one array.", 'start': 37725.343, 'duration': 9.504}], 'summary': 'Using np.indices to locate indices in a grid is difficult, but playing with numpy can help create a boolean array for comparison.', 'duration': 66.953, 'max_score': 37667.894, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI37667894.jpg'}, {'end': 37935.249, 'src': 'embed', 'start': 37901.641, 'weight': 7, 'content': [{'end': 37905.224, 'text': 'We want to just know where this element is in the array.', 'start': 37901.641, 'duration': 3.583}, {'end': 37906.845, 'text': 'So array A has this element.', 'start': 37905.244, 'duration': 1.601}, {'end': 37909.506, 'text': 'Let me print array A as it is.', 'start': 37907.445, 'duration': 2.061}, {'end': 37917.892, 'text': 'This array A has this particular element, and we want to know what is the index of this element inside the array.', 'start': 37910.507, 'duration': 7.385}, {'end': 37919.613, 'text': 'There are several ways of doing this.', 'start': 37918.372, 'duration': 1.241}, {'end': 37935.249, 'text': 'you call the function arg where arg where, for example, arg where a is equal to minus 1200, and that will return a 2d array,', 'start': 37922.735, 'duration': 12.514}], 'summary': 'Find index of element in array a. function arg where returns 2d array.', 'duration': 33.608, 'max_score': 37901.641, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI37901641.jpg'}], 'start': 36584.76, 'title': 'Numpy array operations', 'summary': 'Covers exploring the random package in numpy, including the range and permutation functions, with a focus on the reshape function and discusses np.random package, which can generate random numbers following different distributions, the reshape function, numpy array indexing, and finding the index of a specific element.', 'chapters': [{'end': 36712.785, 'start': 36584.76, 'title': "Exploring numpy's random package and reshape function", 'summary': 'Covers exploring the random package in numpy, including the range and permutation functions, with a focus on the reshape function, which transforms arrays into multidimensional arrays, such as creating a 2x5 matrix from a 10-element array, aiding in testing operations on matrices.', 'duration': 128.025, 'highlights': ['The reshape function in NumPy transforms arrays into multidimensional arrays, such as creating a 2x5 matrix from a 10-element array, aiding in testing operations on matrices.', 'The permutation function in np.random shuffles all the elements of an array in a completely random way, providing a useful tool for array manipulation.', 'The range function is a useful tool for creating testing arrays and observing the output of operations or algorithms on different kinds of arrays.']}, {'end': 37184.755, 'start': 36712.785, 'title': 'Np random package and reshape function', 'summary': 'Discusses the np.random package, which can generate random numbers following different distributions, and the reshape function, which can be used to quickly create matrices for testing algorithms, with examples of generating uniform and gaussian distributions and multi-dimensional arrays.', 'duration': 471.97, 'highlights': ['The np.random package can create different kinds of random numbers following different distributions, useful in machine learning or statistics.', 'The reshape function allows quick creation of matrices for testing algorithms, with examples of generating multi-dimensional arrays.', 'Examples of generating uniform and gaussian distributions using np.random.rand and np.random.randn are provided.']}, {'end': 37597.188, 'start': 37186.236, 'title': 'Numpy array indexing', 'summary': 'Explores the differences between slicing in numpy arrays and ordinary lists, highlighting that numpy slicing accesses the same memory view as the original array, leading to changes in both arrays, and also demonstrating the efficiency of numpy slicing in accessing elements without making copies in memory.', 'duration': 410.952, 'highlights': ['NumPy slicing accesses the same memory view as the original array, leading to changes in both arrays', 'Efficiency of NumPy slicing in accessing elements without making copies in memory']}, {'end': 38031.726, 'start': 37597.188, 'title': 'Finding index of a element in numpy array', 'summary': 'Discusses finding the index of a specific element, utilizing functions like argwhere and np.indices as well as exploring the use of boolean arrays to locate the index of a particular element.', 'duration': 434.538, 'highlights': ['The chapter discusses finding the index of a specific element', 'Utilizing functions like argwhere and np.indices', 'Exploring the use of Boolean arrays to locate the index of a particular element']}], 'duration': 1446.966, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI36584760.jpg', 'highlights': ['The np.random package can create different kinds of random numbers following different distributions, useful in machine learning or statistics.', 'The reshape function in NumPy transforms arrays into multidimensional arrays, such as creating a 2x5 matrix from a 10-element array, aiding in testing operations on matrices.', 'The permutation function in np.random shuffles all the elements of an array in a completely random way, providing a useful tool for array manipulation.', 'The range function is a useful tool for creating testing arrays and observing the output of operations or algorithms on different kinds of arrays.', 'NumPy slicing accesses the same memory view as the original array, leading to changes in both arrays', 'Efficiency of NumPy slicing in accessing elements without making copies in memory', 'Exploring the use of Boolean arrays to locate the index of a particular element', 'The chapter discusses finding the index of a specific element', 'Utilizing functions like argwhere and np.indices', 'Examples of generating uniform and gaussian distributions using np.random.rand and np.random.randn are provided.', 'The reshape function allows quick creation of matrices for testing algorithms, with examples of generating multi-dimensional arrays.']}, {'end': 39450.007, 'segs': [{'end': 38317.23, 'src': 'embed', 'start': 38289.954, 'weight': 0, 'content': [{'end': 38297.62, 'text': 'And the result will be if you see the result, the result will be every column is sorted individually.', 'start': 38289.954, 'duration': 7.666}, {'end': 38307.807, 'text': 'If we want to sort, for example, every row individually, we will say, OK, sort X is equals one and every row will be sorted individually.', 'start': 38298.06, 'duration': 9.747}, {'end': 38317.23, 'text': 'And if this is a multi-dimensional array, more than two dimensions, then Xs can be two, Xs can be three.', 'start': 38311.286, 'duration': 5.944}], 'summary': 'Result: every column sorted individually. sort rows individually using x=1. for multi-dimensional arrays, xs=2 or 3.', 'duration': 27.276, 'max_score': 38289.954, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI38289954.jpg'}, {'end': 38566.76, 'src': 'embed', 'start': 38532.896, 'weight': 1, 'content': [{'end': 38535.477, 'text': "So that's the difference between slicing and masking.", 'start': 38532.896, 'duration': 2.581}, {'end': 38539.798, 'text': 'Okay, this kind of Boolean indexing becomes really handy.', 'start': 38536.696, 'duration': 3.102}, {'end': 38544.701, 'text': 'For example, what if you want to get all the elements that are smaller than eight?', 'start': 38539.858, 'duration': 4.843}, {'end': 38550.845, 'text': 'One way to do that is just write a and then apply a condition a is less than eight.', 'start': 38545.201, 'duration': 5.644}, {'end': 38558.491, 'text': 'Well, a is less than eight will create a Boolean array, And everywhere where the element is smaller than 8, there will be a true.', 'start': 38551.285, 'duration': 7.206}, {'end': 38559.812, 'text': 'otherwise it will be a false.', 'start': 38558.491, 'duration': 1.321}, {'end': 38566.76, 'text': 'Now the inside array is a Boolean array, and you access all the elements with respect to that condition.', 'start': 38560.293, 'duration': 6.467}], 'summary': 'Boolean indexing is handy for accessing elements based on conditions like a < 8.', 'duration': 33.864, 'max_score': 38532.896, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI38532896.jpg'}, {'end': 38935.418, 'src': 'embed', 'start': 38905.529, 'weight': 3, 'content': [{'end': 38917.88, 'text': 'NumPy allows you to just do this particular thing and this five is automatically broadcasted to match with the dimensions of its other operand and the addition happens.', 'start': 38905.529, 'duration': 12.351}, {'end': 38919.782, 'text': 'you need not to do this explicitly.', 'start': 38917.88, 'duration': 1.902}, {'end': 38922.986, 'text': 'And this broadcasting is not just one scalar value.', 'start': 38920.383, 'duration': 2.603}, {'end': 38935.418, 'text': "For example, if you have one variable, let's say A is this and you want to add, for example, this particular column, let's say one, three.", 'start': 38923.046, 'duration': 12.372}], 'summary': 'Numpy simplifies broadcasting, automatically matching dimensions for operations like addition.', 'duration': 29.889, 'max_score': 38905.529, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI38905529.jpg'}, {'end': 39088.535, 'src': 'embed', 'start': 39058.095, 'weight': 2, 'content': [{'end': 39063.339, 'text': 'to concatenate two arrays vertically if they can be concatenated vertically.', 'start': 39058.095, 'duration': 5.244}, {'end': 39068.482, 'text': 'Similarly, there is another powerful function, sort, and there are a lot of other functions.', 'start': 39063.419, 'duration': 5.063}, {'end': 39076.067, 'text': 'These kind of functions, they are called universal functions, and they are very, very, very powerful, very, very fast.', 'start': 39068.622, 'duration': 7.445}, {'end': 39078.168, 'text': 'Their implementation is vectorized.', 'start': 39076.127, 'duration': 2.041}, {'end': 39080.61, 'text': 'Vectorized means the implementation,', 'start': 39078.809, 'duration': 1.801}, {'end': 39088.535, 'text': 'the all loop kind of layer is deferred to at the compile time and the things are really faster when you do a vectorized code.', 'start': 39080.61, 'duration': 7.925}], 'summary': 'Numpy offers powerful universal functions that are fast and vectorized.', 'duration': 30.44, 'max_score': 39058.095, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI39058095.jpg'}], 'start': 38031.726, 'title': 'Numpy array operations', 'summary': 'Covers indexing, slicing, transposing, matrix operations, and sorting arrays. it discusses different methods of indexing, boolean masks, and their impact. also, it demonstrates how to access elements, apply conditions, and introduces broadcasting for element-wise operations. additionally, it introduces universal functions and emphasizes the power of broadcasting for improved efficiency.', 'chapters': [{'end': 38343.697, 'start': 38031.726, 'title': 'Indexing and operations on arrays in numpy', 'summary': 'Covers indexing of arrays, slicing for accessing specific rows and columns, transposing arrays, using linear algebra library for matrix operations, and sorting arrays with respect to columns and rows.', 'duration': 311.971, 'highlights': ['Arrays can be accessed using indices, where the second row and third column can be accessed using index 1, 2.', 'Accessing whole rows or columns can be achieved through slicing, enabling extraction of sub matrices and processing.', 'The linear algebra library in numpy provides functions for eigenvalues, Cholesky decomposition, computing determinant, and finding inverses of matrices.', 'The sort function in numpy can be used to sort columns or rows individually, as well as multi-dimensional arrays with different dimensions.']}, {'end': 38601.706, 'start': 38343.817, 'title': 'Numpy array indexing', 'summary': 'Discusses the different methods of indexing in numpy arrays, including slicing, index arrays, boolean masks, and their impact on creating a view or a copy, with examples and use cases mentioned.', 'duration': 257.889, 'highlights': ['The chapter explains the concept of Boolean indexing, a method to access elements based on a Boolean mask, returning the selected elements, for example, all elements smaller than 8.', 'The chapter introduces the use of Boolean masks to access elements based on true or false values, providing an example with the process of picking specific elements from an array using a Boolean mask.', 'The chapter explains the difference between slicing and masking in NumPy arrays, emphasizing that using a Boolean array or array indices results in obtaining a copy of the array, unlike slicing which provides a view with the same memory.']}, {'end': 39029.664, 'start': 38601.706, 'title': 'Numpy indexing and broadcasting', 'summary': 'Discusses numpy indexing, demonstrating how to access specific elements of an array, apply conditions to filter elements, and introduces broadcasting, a powerful feature that allows automatic matching of dimensions for element-wise operations.', 'duration': 427.958, 'highlights': ['NumPy allows accessing specific elements of an array and applying conditions to filter elements, such as accessing elements smaller than a certain value or within a specific range.', 'The concept of broadcasting in NumPy is introduced, showcasing its capability to automatically match dimensions for element-wise operations, eliminating the need to explicitly create arrays of the same size for operations.', "Explanation of the AND operator in array operations and the distinction between AND operator and the symbol 'AND', providing clarity on their respective uses for arrays and single objects."]}, {'end': 39450.007, 'start': 39029.664, 'title': 'Numpy functions and broadcasting', 'summary': 'Introduces numpy universal functions such as horizontal and vertical stack, sort function, and discusses the power of broadcasting, recommending their usage over explicit for loops for improved efficiency.', 'duration': 420.343, 'highlights': ['NumPy universal functions are very powerful and fast, with implementation being vectorized, resulting in significantly faster performance compared to explicit for loops.', 'The chapter emphasizes the usage of universal functions over explicit for loops for improved efficiency, recommending their usage whenever available.', 'The transcript discusses the application of horizontal and vertical stack functions in NumPy for concatenating arrays either horizontally or vertically.', 'Broadcasting is highlighted as a powerful feature in NumPy, enabling operations such as adding a single value to all elements in an array or adding a column to each column of a matrix.', 'The sort function in NumPy is discussed, emphasizing its ability to sort arrays in ascending or descending order, as well as its functionality with arrays containing strings.']}], 'duration': 1418.281, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI38031726.jpg', 'highlights': ['The sort function in numpy can be used to sort columns or rows individually, as well as multi-dimensional arrays with different dimensions.', 'The chapter explains the concept of Boolean indexing, a method to access elements based on a Boolean mask, returning the selected elements, for example, all elements smaller than 8.', 'NumPy universal functions are very powerful and fast, with implementation being vectorized, resulting in significantly faster performance compared to explicit for loops.', 'The concept of broadcasting in NumPy is introduced, showcasing its capability to automatically match dimensions for element-wise operations, eliminating the need to explicitly create arrays of the same size for operations.']}, {'end': 42030.64, 'segs': [{'end': 39685.701, 'src': 'embed', 'start': 39658.924, 'weight': 0, 'content': [{'end': 39665.03, 'text': 'However, the universal function takes just around 3 milliseconds, I mean 2.7 milliseconds.', 'start': 39658.924, 'duration': 6.106}, {'end': 39671.537, 'text': 'How are you going to compare this 3.07 with 3? How much faster you are? Around.', 'start': 39665.431, 'duration': 6.106}, {'end': 39675.155, 'text': "Around 100 times you're faster.", 'start': 39673.314, 'duration': 1.841}, {'end': 39676.736, 'text': 'I mean, yeah.', 'start': 39675.715, 'duration': 1.021}, {'end': 39679.598, 'text': 'I mean, this numpy is literally faster.', 'start': 39677.496, 'duration': 2.102}, {'end': 39681.739, 'text': 'Numpy, the universal function that are faster.', 'start': 39679.778, 'duration': 1.961}, {'end': 39685.701, 'text': 'Maybe you attempt to know that, okay, this sum function might be too slow.', 'start': 39682.399, 'duration': 3.302}], 'summary': "Numpy's universal function is around 100 times faster, taking just 2.7 milliseconds compared to 3 seconds for other functions.", 'duration': 26.777, 'max_score': 39658.924, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI39658924.jpg'}, {'end': 39795.033, 'src': 'embed', 'start': 39766.025, 'weight': 4, 'content': [{'end': 39767.986, 'text': 'Whenever possible, avoid loops.', 'start': 39766.025, 'duration': 1.961}, {'end': 39770.466, 'text': 'when you are working with NumPy.', 'start': 39768.986, 'duration': 1.48}, {'end': 39773.287, 'text': "That's a serious suggestion.", 'start': 39771.087, 'duration': 2.2}, {'end': 39780.569, 'text': 'Follow that because the universal function written in NumPy, they follow the vectorized code.', 'start': 39773.867, 'duration': 6.702}, {'end': 39787.651, 'text': 'All the interpreted slowness that is deferred to the compilation layer and the NumPy becomes really,', 'start': 39781.089, 'duration': 6.562}, {'end': 39795.033, 'text': 'really faster and shows its power when you are working on large arrays using the universal functions.', 'start': 39787.651, 'duration': 7.382}], 'summary': 'Avoid loops when working with numpy for faster performance on large arrays.', 'duration': 29.008, 'max_score': 39766.025, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI39766025.jpg'}, {'end': 39894.36, 'src': 'embed', 'start': 39869.603, 'weight': 1, 'content': [{'end': 39875.789, 'text': 'This Pandas basically is built on top of NumPy, so most of the features of NumPy is also available in Pandas.', 'start': 39869.603, 'duration': 6.186}, {'end': 39878.931, 'text': "Let's dive in.", 'start': 39878.291, 'duration': 0.64}, {'end': 39880.492, 'text': 'I mean this.', 'start': 39879.051, 'duration': 1.441}, {'end': 39891.418, 'text': 'Pandas is a very, very fancy library, very, very fancy package that you can handle very large amounts of data in CSV files or in Excel files,', 'start': 39880.492, 'duration': 10.926}, {'end': 39892.959, 'text': 'wherever the data is located.', 'start': 39891.418, 'duration': 1.541}, {'end': 39894.36, 'text': 'the missing entries are there.', 'start': 39892.959, 'duration': 1.401}], 'summary': 'Pandas is a sophisticated tool for handling large amounts of data in csv or excel files, inheriting features from numpy.', 'duration': 24.757, 'max_score': 39869.603, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI39869603.jpg'}, {'end': 40683.922, 'src': 'embed', 'start': 40655.643, 'weight': 2, 'content': [{'end': 40662.227, 'text': 'then you have another record And each element in that record is a different attribute.', 'start': 40655.643, 'duration': 6.584}, {'end': 40670.433, 'text': 'So this particular way of two-dimensional data is very well handled using DataFrame inside Pandas rather than series.', 'start': 40662.728, 'duration': 7.705}, {'end': 40676.497, 'text': 'But you can make these DataFrame objects using different series objects.', 'start': 40672.294, 'duration': 4.203}, {'end': 40681.28, 'text': 'For example, you have a grades object that we created last time.', 'start': 40676.557, 'duration': 4.723}, {'end': 40683.922, 'text': 'You have a marks object that we created last time.', 'start': 40681.66, 'duration': 2.262}], 'summary': 'Pandas dataframe efficiently handles two-dimensional data with different attributes.', 'duration': 28.279, 'max_score': 40655.643, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI40655643.jpg'}, {'end': 41398.868, 'src': 'embed', 'start': 41369.724, 'weight': 3, 'content': [{'end': 41371.946, 'text': 'I mean, there are a lot of values that can be missing.', 'start': 41369.724, 'duration': 2.222}, {'end': 41383.136, 'text': 'One way that Panda supplies to handle these missing values is to just fill these missing values with some fixed number, for example.', 'start': 41372.726, 'duration': 10.41}, {'end': 41385.338, 'text': "There's a fillNA function.", 'start': 41383.716, 'duration': 1.622}, {'end': 41389.401, 'text': "fill any function and let's say, you supply a zero.", 'start': 41386.239, 'duration': 3.162}, {'end': 41398.868, 'text': 'that means wherever there is a not available or not a number value, fill that with zero or maybe any any value you want to fill that with.', 'start': 41389.401, 'duration': 9.467}], 'summary': "Pandas' fillna function can replace missing values with a specified number, such as zero.", 'duration': 29.144, 'max_score': 41369.724, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI41369724.jpg'}], 'start': 39450.666, 'title': 'Numpy and pandas for data manipulation', 'summary': "Covers the speed difference between numpy's universal functions and ordinary functions, showcasing a 100 times faster performance of numpy's universal functions, introduces pandas for data manipulation, creating series and dataframes, working with pandas dataframes, and handling missing data.", 'chapters': [{'end': 39731.556, 'start': 39450.666, 'title': 'Numpy speed demonstration', 'summary': "Covers the speed difference between numpy's universal functions and ordinary functions, showcasing a 100 times faster performance of numpy's universal functions over ordinary functions, as demonstrated by the example using the sum function.", 'duration': 280.89, 'highlights': ["NumPy's universal function takes just around 2.7 milliseconds, while the ordinary Python function takes 307 milliseconds, showcasing a 100 times faster performance of NumPy's universal functions.", "The demonstration reveals the significant speed advantage of NumPy's universal functions, with the example showcasing the 100 times faster performance compared to ordinary functions.", "The example illustrates the substantial speed difference, emphasizing the remarkable efficiency of NumPy's universal functions for vectorized implementation."]}, {'end': 40260.882, 'start': 39731.556, 'title': 'Optimizing data manipulation with numpy and pandas', 'summary': "Discusses the benefits of using numpy's universal functions for faster data manipulation, followed by an introduction to the powerful data manipulation capabilities of pandas, built on top of numpy, and the ease of creating and manipulating series objects in pandas.", 'duration': 529.326, 'highlights': ['NumPy universal functions provide significant speed improvements compared to traditional loops for data manipulation tasks.', 'Pandas is a powerful library for handling and manipulating large amounts of data, including data cleaning and pre-processing, with the ability to handle missing entries efficiently.', 'Pandas series objects allow for easy creation and manipulation of one-dimensional arrays, leveraging NumPy functionality.']}, {'end': 40778.431, 'start': 40261.222, 'title': 'Creating series and dataframes in pandas', 'summary': 'Covers creating series and dataframes in pandas, including defining dictionaries, creating series objects, accessing and manipulating data, and building a dataframe using series objects, highlighting the importance of dataframes for handling two-dimensional data and their use in pandas.', 'duration': 517.209, 'highlights': ['The chapter covers creating series and dataframes in Pandas, including defining dictionaries, creating series objects, accessing and manipulating data, and building a dataframe using series objects, highlighting the importance of dataframes for handling two-dimensional data and their use in Pandas.', 'Demonstrates creating series objects using dictionaries and accessing values based on indices or slicing, providing a practical example of how to manipulate and access data within the series objects.', 'Explains the concept of dataframes as an extension of series for two-dimensional data and their advantages in handling and manipulating data, emphasizing their use for reading data from files and performing data manipulation.', 'Illustrates the process of building a dataframe using series objects, showcasing the integration of the marks and grades series objects into a dataframe, and displaying the structured data in a tabular format for easy interpretation.']}, {'end': 41100.484, 'start': 40779.039, 'title': 'Working with pandas dataframes', 'summary': 'Explains the structure of a pandas dataframe, accessing values, adding and deleting columns, and indexing with conditions, providing a comprehensive understanding of working with pandas dataframes.', 'duration': 321.445, 'highlights': ['The Pandas DataFrame serves as an ideal data structure for working with files containing numerous records, facilitating data manipulation. It contains multiple columns representing attributes and rows representing individual records or samples.', 'Accessing values within a DataFrame involves utilizing a two-dimensional array, allowing for the retrieval of specific elements based on row and column indices, demonstrated by accessing the value 65 at row 3 and column 1.', "The process of adding a new column to a DataFrame, such as 'scaled marks,' involves creating a dictionary-like structure and assigning a new key-value pair, enabling the computation of scaled marks by dividing the 'marks' column by 90.", 'DataFrames support the deletion of columns using concepts similar to dictionaries, providing the flexibility to manipulate the data structure by adding or removing columns as well as performing indexing with conditions, such as filtering records based on specific criteria like marks greater than 70.']}, {'end': 42030.64, 'start': 41100.984, 'title': 'Handling missing data in pandas', 'summary': 'Discusses the handling of missing data in pandas, showing methods such as fillna and dropna, and the confusion between implicit and explicit indices, demonstrating the use of loc and iloc functions to address the confusion.', 'duration': 929.656, 'highlights': ['Pandas provides methods to handle missing values, such as fillNA and dropna, allowing for the filling or dropping of missing values to avoid data loss.', 'The chapter demonstrates the confusion between implicit and explicit indices, introducing the use of LOC and ILOC functions to handle explicit and implicit indices for accessing elements.', 'The next video will showcase the manipulation and analysis of a real dataset, specifically a COVID-19 dataset, to illustrate the efficient data manipulation capabilities of Pandas.']}], 'duration': 2579.974, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI39450666.jpg', 'highlights': ["NumPy's universal function takes just around 2.7 milliseconds, while the ordinary Python function takes 307 milliseconds, showcasing a 100 times faster performance of NumPy's universal functions.", 'Pandas is a powerful library for handling and manipulating large amounts of data, including data cleaning and pre-processing, with the ability to handle missing entries efficiently.', 'The Pandas DataFrame serves as an ideal data structure for working with files containing numerous records, facilitating data manipulation. It contains multiple columns representing attributes and rows representing individual records or samples.', 'Pandas provides methods to handle missing values, such as fillNA and dropna, allowing for the filling or dropping of missing values to avoid data loss.', 'NumPy universal functions provide significant speed improvements compared to traditional loops for data manipulation tasks.']}, {'end': 44389.257, 'segs': [{'end': 42085.96, 'src': 'embed', 'start': 42059.257, 'weight': 1, 'content': [{'end': 42065.441, 'text': 'so first of all i need this pandas library and put it that maybe somewhere i need this numpy library as well.', 'start': 42059.257, 'duration': 6.184}, {'end': 42075.69, 'text': "I'm also loading a scikit-learn sklearn library because I want to use impute function just to handle the missing values.", 'start': 42067.522, 'duration': 8.168}, {'end': 42085.96, 'text': 'It is just more powerful to use the sklearn library that is also a data science library package that is particularly a machine learning library.', 'start': 42076.571, 'duration': 9.389}], 'summary': 'Using pandas and numpy libraries, loading scikit-learn for impute function in data science and machine learning.', 'duration': 26.703, 'max_score': 42059.257, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI42059257.jpg'}, {'end': 43054.526, 'src': 'embed', 'start': 43023.54, 'weight': 2, 'content': [{'end': 43033.637, 'text': "A group by command will stay almost the same with one kind of, let's say we want to first group by country.", 'start': 43023.54, 'duration': 10.097}, {'end': 43038.933, 'text': 'Once it is grouped by the country, then I want to group them by date.', 'start': 43034.649, 'duration': 4.284}, {'end': 43047.16, 'text': 'And now I want to see all the results in the form of, I want to see the date as well.', 'start': 43039.753, 'duration': 7.407}, {'end': 43054.526, 'text': "And what will happen now is for each country, it's trend with respect to all the dates that will be displayed here.", 'start': 43047.92, 'duration': 6.606}], 'summary': 'Group by country and date to analyze trends.', 'duration': 30.986, 'max_score': 43023.54, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI43023540.jpg'}, {'end': 43173.593, 'src': 'embed', 'start': 43146.458, 'weight': 0, 'content': [{'end': 43153.364, 'text': "I've just shown you a very small snapshot of what we can do with Pandas on the real data set.", 'start': 43146.458, 'duration': 6.906}, {'end': 43164.254, 'text': 'There is a lot more that we can do with this Pandas library on real data sets, on multiple data files, combining them together, joining them together,', 'start': 43153.945, 'duration': 10.309}, {'end': 43166.335, 'text': 'seeing their correlation a lot of stuff.', 'start': 43164.254, 'duration': 2.081}, {'end': 43173.593, 'text': 'And this pandas really is a very, very fancy and very high level library, very high level package to work with data.', 'start': 43167.196, 'duration': 6.397}], 'summary': 'Pandas offers powerful capabilities for working with real datasets, including combining, joining, and analyzing correlations.', 'duration': 27.135, 'max_score': 43146.458, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI43146458.jpg'}, {'end': 43717.39, 'src': 'embed', 'start': 43682.778, 'weight': 4, 'content': [{'end': 43685.339, 'text': 'So there are several things that are available in Matplotlib.', 'start': 43682.778, 'duration': 2.561}, {'end': 43692.463, 'text': 'This is just a very few, very simple snapshot, and I have given you a very quick start.', 'start': 43686.24, 'duration': 6.223}, {'end': 43695.805, 'text': 'Actually, the whole point is using Matlab is that quick.', 'start': 43693.043, 'duration': 2.762}, {'end': 43703.329, 'text': "I mean, you have your data, you just plug in their data, you just call the plot function, and you're good to go for analysis.", 'start': 43695.865, 'duration': 7.464}, {'end': 43709.963, 'text': 'okay, um uh, in in the next video we are, we will actually walk through the.', 'start': 43704.258, 'duration': 5.705}, {'end': 43717.39, 'text': "we will actually walk through the covet 19 data set and we'll actually analyze the trends and, uh,", 'start': 43709.963, 'duration': 7.427}], 'summary': 'Matplotlib offers quick data visualization and analysis, with a walkthrough on analyzing covid-19 trends.', 'duration': 34.612, 'max_score': 43682.778, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI43682778.jpg'}, {'end': 44049.286, 'src': 'embed', 'start': 44019.839, 'weight': 3, 'content': [{'end': 44023.14, 'text': 'Then we force them to show that in each iteration.', 'start': 44019.839, 'duration': 3.301}, {'end': 44024.981, 'text': 'show the show, the for.', 'start': 44023.14, 'duration': 1.841}, {'end': 44032.902, 'text': 'so this will show the trends of confirms, recovers and deaths for all 171 countries, one by one.', 'start': 44024.981, 'duration': 7.921}, {'end': 44037.703, 'text': "so if we run this command, we'll be having 171 plots in front of us.", 'start': 44032.902, 'duration': 4.801}, {'end': 44040.384, 'text': "let's see all of those one by one.", 'start': 44037.703, 'duration': 2.681}, {'end': 44043.965, 'text': 'so yeah, so this is for the country.', 'start': 44040.384, 'duration': 3.581}, {'end': 44046.545, 'text': 'it has just one such thing.', 'start': 44043.965, 'duration': 2.58}, {'end': 44047.385, 'text': 'this is for that.', 'start': 44046.545, 'duration': 0.84}, {'end': 44049.286, 'text': 'this is for afghanistan.', 'start': 44047.385, 'duration': 1.901}], 'summary': 'Analyzing trends for 171 countries, yielding 171 plots.', 'duration': 29.447, 'max_score': 44019.839, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI44019839.jpg'}], 'start': 42031.48, 'title': 'Data analysis and visualization', 'summary': 'Covers data manipulation in jupyter notebook, covid-19 data analysis, data analysis with pandas, matplotlib plotting basics, and analyzing covid-19 data with matplotlib and pandas. it includes tasks such as reading and manipulating data, analyzing covid-19 data using describe and info functions, group and analyze data with pandas, and creating line plots and scatter plots using matplotlib, providing insights using 171 plots to visualize the trend of confirmed, recovered, and death cases for each country and the overall world.', 'chapters': [{'end': 42529.851, 'start': 42031.48, 'title': 'Data manipulation in jupyter notebook', 'summary': 'Discusses reading and manipulating data using pandas and scikit-learn in jupyter notebook, including importing libraries, loading data, dropping columns, renaming columns, and converting date formats.', 'duration': 498.371, 'highlights': ['The chapter discusses reading and manipulating data using pandas and scikit-learn in Jupyter Notebook.', 'Importing pandas, numpy, and scikit-learn libraries is necessary for data manipulation.', 'Loading data using pd.read_csv and manipulating the data in Jupyter Notebook.', 'Dropping columns using df.drop and renaming columns using df.rename.', 'Converting date format using pd.to_datetime function.']}, {'end': 43002.048, 'start': 42530.487, 'title': 'Covid-19 data analysis', 'summary': 'Demonstrates the use of describe and info functions to analyze covid-19 data, including statistics and handling missing values, followed by a preview of the upcoming topics on group by command in pandas and data visualization with matplotlib.', 'duration': 471.561, 'highlights': ['The chapter explains the use of the describe function to display statistics of the data, including the total count of confirmed cases, deaths, recovered cases, the number of columns and values, mean, standard deviation, minimum, and 25th percentile.', 'The transcript demonstrates the handling of missing values using the simple imputer from sklearn and the fillna function of DataFrame to impute the missing values, ensuring no null values remain in the data.', 'The upcoming topics on group by command in Pandas and data visualization with matplotlib are previewed, indicating the focus on analyzing COVID-19 data and gaining insights through data visualization.']}, {'end': 43339.511, 'start': 43002.048, 'title': 'Data analysis with pandas', 'summary': 'Explains how to group and analyze data using pandas, including filtering records based on specified conditions and visualizing trends using matplotlib, in preparation for further data exploration.', 'duration': 337.463, 'highlights': ['The chapter demonstrates grouping data by country and date using Pandas, allowing for the analysis of trends and patterns, which provides valuable insights into the data.', 'It showcases the process of filtering records in Pandas based on specific conditions, such as selecting records with confirmed cases greater than 100, enabling precise data analysis and decision-making.', 'The chapter introduces the importance of data visualization using Matplotlib, emphasizing its effectiveness in providing insights into data trends and patterns, and highlights its role in expediting the design process by enabling a quick understanding of the data.']}, {'end': 43703.329, 'start': 43339.511, 'title': 'Matplotlib plotting basics', 'summary': 'Introduces the basics of plotting using matplotlib, demonstrating the creation of line plots and scatter plots with customizable properties. it also emphasizes the simplicity and power of matplotlib for quick data analysis and visualization.', 'duration': 363.818, 'highlights': ['The chapter introduces the basics of plotting using Matplotlib, demonstrating the creation of line plots and scatter plots with customizable properties.', 'The chapter emphasizes the simplicity and power of Matplotlib for quick data analysis and visualization.', 'Demonstrates the use of the linspace function in NumPy to create a thousand points between zero and ten for plotting.', 'Shows how to change plot colors and customize properties, such as labeling and annotation, using Matplotlib.']}, {'end': 44389.257, 'start': 43704.258, 'title': 'Analyzing covid-19 data with matplotlib and pandas', 'summary': 'Demonstrates the analysis of covid-19 data set using matplotlib and pandas, providing insights into death rate trends for each country individually and the overall world till march 16th, using 171 plots to visualize the trend of confirmed, recovered, and death cases for each country and the overall world.', 'duration': 684.999, 'highlights': ['Using Matplotlib and Pandas, the chapter analyzes the COVID-19 data set, providing insights into death rate trends for each country individually and the overall world till March 16th.', 'A total of 171 plots are used to visualize the trend of confirmed, recovered, and death cases for each country and the overall world.', 'The chapter demonstrates the use of Pandas, NumPy, and Matplotlib for data preprocessing and visualization, essential for making predictions and classifications using machine learning libraries like scikit-learn, TensorFlow, or PyTorch.']}], 'duration': 2357.777, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/LHBE6Q9XlzI/pics/LHBE6Q9XlzI42031480.jpg', 'highlights': ['The chapter covers data manipulation using pandas and scikit-learn in Jupyter Notebook', 'Importing pandas, numpy, and scikit-learn libraries is necessary for data manipulation', 'The chapter demonstrates grouping data by country and date using Pandas for trend analysis', 'A total of 171 plots are used to visualize the trend of confirmed, recovered, and death cases', 'The chapter emphasizes the simplicity and power of Matplotlib for quick data analysis and visualization']}], 'highlights': ['Python simplifies transition to running solutions, showcasing strength in data processing', "Python's popularity leads to 85% of total job opportunities in programming", 'Jupyter Notebook stands out as the most popular Python IDE for data science', 'The round function rounds the number based on the next digit and the next digit being larger than five', 'The concept of using pseudocode for generalizing the process of finding the minimum value in lists', 'The Jupyter notebook is an enhanced variant of IPython shell, offering better interfaces and features', 'The result of comparison is always a Boolean, for example, x is not equal to y results in true if x and y have different values', 'The process of control flow in Python is introduced, demonstrating the usage of if conditions', 'The program-solving task requires finding the integer portion of a floating-point number and determining if it is even or odd', 'The round function extracts the integer portion of a number and handles positive and negative numbers', 'The process of defining a function in Python is outlined, including the syntax and organization', 'The function check args expects three arguments and will result in an error if called with less than or more than three arguments', 'Modules are recommended for maintaining large projects, while packages are preferable for very large projects', 'Python data structures: strings, lists, sets, dictionaries, and tuples', 'NumPy is much faster than List due to its efficiency in handling homogeneous data types', 'The np.random package can create different kinds of random numbers following different distributions', 'The sort function in numpy can be used to sort columns or rows individually', 'Pandas is a powerful library for handling and manipulating large amounts of data', 'The chapter covers data manipulation using pandas and scikit-learn in Jupyter Notebook', 'The chapter emphasizes the simplicity and power of Matplotlib for quick data analysis and visualization']}