title
Hash Table And HashMap In Python | Implementing Hash Tables Using Dictionary In Python | Edureka

description
** Python Certification Training: https://www.edureka.co/python ** This Edureka video on 'HashTables and HashMaps in Python' will help you learn how you to implement Hash Tables and HashMaps in Python using dictionaries. Below are the topics covered in this video: What is a Hash Table or a Hashmap in Python? Creating Dictionaries Nested Dictionaries Performing Operation oh Hash Tables Accessing Items Updating Values Deleting Entries Converting Dictionary into a Dataframe Python Tutorial Playlist: https://goo.gl/WsBpKe Blog Series: http://bit.ly/2sqmP4s #Edureka #PythonEdureka #HashTablesandHashmapsinPython#pythonProgramming #pythonTutorial #PythonTraining Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ----------------------------------------------------------------------------------------------------------- How it Works? 1. This is a 5 Week Instructor-led Online Course,40 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Python Online Certification Training will make you an expert in Python programming. It will also help you learn Python the Big data way with integration of Machine learning, Pig, Hive and Web Scraping through beautiful soup. During our Python Certification training, our instructors will help you: 1. Master the Basic and Advanced Concepts of Python 2. Understand Python Scripts on UNIX/Windows, Python Editors and IDEs 3. Master the Concepts of Sequences and File operations 4. Learn how to use and create functions, sorting different elements, Lambda function, error handling techniques and Regular expressions ans using modules in Python 5. Gain expertise in machine learning using Python and build a Real Life Machine Learning application 6. Understand the supervised and unsupervised learning and concepts of Scikit-Learn 7. Master the concepts of MapReduce in Hadoop 8. Learn to write Complex MapReduce programs 9. Understand what is PIG and HIVE, Streaming feature in Hadoop, MapReduce job running with Python 10. Implementing a PIG UDF in Python, Writing a HIVE UDF in Python, Pydoop and/Or MRjob Basics 11. Master the concepts of Web scraping in Python 12. Work on a Real Life Project on Big Data Analytics using Python and gain Hands on Project Experience - - - - - - - - - - - - - - - - - - - Why learn Python? Programmers love Python because of how fast and easy it is to use. Python cuts development time in half with its simple to read syntax and easy compilation feature. Debugging your programs is a breeze in Python with its built in debugger. Using Python makes Programmers more productive and their programs ultimately better. Python continues to be a favorite option for data scientists who use it for building and using Machine learning applications and other scientific computations. Python runs on Windows, Linux/Unix, Mac OS and has been ported to Java and .NET virtual machines. Python is free to use, even for the commercial products, because of its OSI-approved open source license. Python has evolved as the most preferred Language for Data Analytics and the increasing search trends on python also indicates that Python is the next "Big Thing" and a must for Professionals in the Data Analytics domain. Who should go for python? Edureka’s Data Science certification course in Python is a good fit for the below professionals: · Programmers, Developers, Technical Leads, Architects · Developers aspiring to be a ‘Machine Learning Engineer' · Analytics Managers who are leading a team of analysts · Business Analysts who want to understand Machine Learning (ML) Techniques · Information Architects who want to gain expertise in Predictive Analytics · 'Python' professionals who want to design automatic predictive models For more information, Please write back to us at sales@edureka.in or call us at IND: 9606058406 / US: 18338555775 (toll free)

detail
{'title': 'Hash Table And HashMap In Python | Implementing Hash Tables Using Dictionary In Python | Edureka', 'heatmap': [{'end': 965.374, 'start': 942.528, 'weight': 1}], 'summary': 'Covers python hash tables and maps, discussing hash table implementation using dictionaries and nested dictionaries, along with operations like accessing, updating, and deleting elements, and concludes with converting a python dictionary into a pandas data frame.', 'chapters': [{'end': 94.041, 'segs': [{'end': 39.299, 'src': 'embed', 'start': 11.448, 'weight': 1, 'content': [{'end': 15.49, 'text': 'Data requires a number of ways in which it can be stored and accessed,', 'start': 11.448, 'duration': 4.042}, {'end': 19.792, 'text': 'and one of its most important implementations includes hash tables and hash maps.', 'start': 15.49, 'duration': 4.302}, {'end': 23.073, 'text': 'Hey guys, welcome back to a new session from edureka.', 'start': 20.352, 'duration': 2.721}, {'end': 30.297, 'text': "My name is Vajija and in this session, you'll be learning all about hash tables and hash maps in Python along with the implementations.", 'start': 23.574, 'duration': 6.723}, {'end': 37.24, 'text': 'So before we begin just make sure you subscribe to our channel and hit the bell icon to stay updated with all the latest edureka videos.', 'start': 30.917, 'duration': 6.323}, {'end': 39.299, 'text': 'Coming back towards the session.', 'start': 37.998, 'duration': 1.301}], 'summary': 'Learning about hash tables and hash maps in python with implementations.', 'duration': 27.851, 'max_score': 11.448, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI11448.jpg'}, {'end': 85.257, 'src': 'embed', 'start': 51.448, 'weight': 0, 'content': [{'end': 54.67, 'text': 'such as accessing, updating and deleting items from them.', 'start': 51.448, 'duration': 3.222}, {'end': 59.934, 'text': "Finally, I'll be showing you guys how to convert a python dictionary into a pandas data frame.", 'start': 55.451, 'duration': 4.483}, {'end': 62.536, 'text': "So without any further delays, let's get started.", 'start': 60.535, 'duration': 2.001}, {'end': 66.279, 'text': 'So what exactly is a hash table or hash map in python?', 'start': 63.397, 'duration': 2.882}, {'end': 73.631, 'text': 'In the field of computer science, a hash table or a hash map is a type of data structure that Maps keys to its value pairs.', 'start': 67.248, 'duration': 6.383}, {'end': 76.593, 'text': 'It implements the abstract array data type.', 'start': 74.331, 'duration': 2.262}, {'end': 85.257, 'text': 'So this basically makes use of a function that computes an index value that in turn holds the elements to be searched inserted removed Etc.', 'start': 77.293, 'duration': 7.964}], 'summary': 'Python tutorial covering hash tables and converting dictionary to pandas data frame.', 'duration': 33.809, 'max_score': 51.448, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI51448.jpg'}], 'start': 11.448, 'title': 'Python hash tables and maps', 'summary': 'Discusses hash tables and hash maps in python, including the implementation of dictionaries and nested dictionaries, along with operations on hash tables, and concludes with the conversion of a python dictionary into a pandas data frame.', 'chapters': [{'end': 94.041, 'start': 11.448, 'title': 'Python hash tables and maps', 'summary': 'Discusses hash tables and hash maps in python, covering the implementation of dictionaries, nested dictionaries, and operations on hash tables, and concludes with converting a python dictionary into a pandas data frame.', 'duration': 82.593, 'highlights': ['A hash table or a hash map is a type of data structure that Maps keys to its value pairs. Explains the concept of a hash table or hash map as a data structure that maps keys to value pairs.', 'The chapter discusses hash tables and hash maps in Python, covering the implementation of dictionaries, nested dictionaries, and operations on hash tables, and concludes with converting a Python dictionary into a pandas data frame. Covers the comprehensive discussion on hash tables and hash maps in Python, including implementation of dictionaries, nested dictionaries, operations on hash tables, and conversion to pandas data frame.', 'A hash table or a hash map is a type of data structure that Maps keys to its value pairs. Explains the concept of a hash table or hash map as a data structure that maps keys to value pairs.']}], 'duration': 82.593, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI11448.jpg', 'highlights': ['Covers the comprehensive discussion on hash tables and hash maps in Python, including implementation of dictionaries, nested dictionaries, operations on hash tables, and conversion to pandas data frame.', 'Explains the concept of a hash table or hash map as a data structure that maps keys to value pairs.']}, {'end': 647.928, 'segs': [{'end': 137.288, 'src': 'embed', 'start': 94.983, 'weight': 0, 'content': [{'end': 100.285, 'text': 'hash tables or hash maps in python are implemented through the built-in dictionary data type.', 'start': 94.983, 'duration': 5.302}, {'end': 103.926, 'text': 'the keys of a dictionary in python are generated by a hashing function.', 'start': 100.285, 'duration': 3.641}, {'end': 107.928, 'text': 'The elements of a dictionary are not ordered and they can be changed.', 'start': 104.627, 'duration': 3.301}, {'end': 116.231, 'text': 'So for example a dictionary can be a mapping of employee names and their employee IDs or the names of students along with your student IDs.', 'start': 108.688, 'duration': 7.543}, {'end': 118.452, 'text': 'Okay, so moving ahead.', 'start': 117.271, 'duration': 1.181}, {'end': 121.413, 'text': "Let's go on and see how to create dictionaries in python.", 'start': 118.732, 'duration': 2.681}, {'end': 129.781, 'text': 'Dictionaries in python can be created in two ways one is by using the curly braces and the second is to use the dict function.', 'start': 122.415, 'duration': 7.366}, {'end': 133.925, 'text': "So now I'll jump on to my Jupiter notebook and over here.", 'start': 130.582, 'duration': 3.343}, {'end': 137.288, 'text': "I'll be showing you guys how to create dictionaries in both these methods.", 'start': 134.185, 'duration': 3.103}], 'summary': 'Python dictionaries use hashing for key generation and can be created using curly braces or the dict function.', 'duration': 42.305, 'max_score': 94.983, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI94983.jpg'}, {'end': 220.894, 'src': 'embed', 'start': 193.109, 'weight': 2, 'content': [{'end': 196.17, 'text': 'Okay So now to show you guys how to make use of the dict function.', 'start': 193.109, 'duration': 3.061}, {'end': 198.45, 'text': 'All you can do is just specify some name.', 'start': 196.59, 'duration': 1.86}, {'end': 202.192, 'text': "I'll say new dictionary and make use of the dict function.", 'start': 198.53, 'duration': 3.662}, {'end': 204.793, 'text': "I'm not giving any parameters at first.", 'start': 203.012, 'duration': 1.781}, {'end': 207.693, 'text': "I'll just print out new dict.", 'start': 205.973, 'duration': 1.72}, {'end': 212.155, 'text': 'And the type of it as well.', 'start': 211.175, 'duration': 0.98}, {'end': 220.894, 'text': 'Okay, so, as you can see over here, an empty dictionary is created,', 'start': 217.293, 'duration': 3.601}], 'summary': 'Demonstrating the dict function to create an empty dictionary.', 'duration': 27.785, 'max_score': 193.109, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI193109.jpg'}, {'end': 312.101, 'src': 'embed', 'start': 286.503, 'weight': 3, 'content': [{'end': 291.427, 'text': 'this project dictionary itself can be a part of the organization that has a number of projects.', 'start': 286.503, 'duration': 4.924}, {'end': 295.791, 'text': 'So I hope that gives you a clear idea about what exactly is a nested dictionary.', 'start': 292.148, 'duration': 3.643}, {'end': 299.774, 'text': "So now I'll jump on to my Jupiter notebook to show you guys how to create them.", 'start': 296.391, 'duration': 3.383}, {'end': 305.498, 'text': "So all I'm going to do over here is create a dictionary which contains the employee details.", 'start': 300.655, 'duration': 4.843}, {'end': 312.101, 'text': 'a single team can have a number of employees, and these employees have different salaries, IDs and designations.', 'start': 305.498, 'duration': 6.603}], 'summary': 'Nested dictionary organizes project and employee details. a team can have multiple employees with varied salaries, ids, and designations.', 'duration': 25.598, 'max_score': 286.503, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI286503.jpg'}, {'end': 464.416, 'src': 'embed', 'start': 440.462, 'weight': 4, 'content': [{'end': 447.865, 'text': 'the values of a dictionary can be accessed in many ways, such as using key value pairs, using functions or implementing the for loop.', 'start': 440.462, 'duration': 7.403}, {'end': 448.925, 'text': 'now to show all this to you.', 'start': 447.865, 'duration': 1.06}, {'end': 450.386, 'text': "I'll jump on to my Jupiter notebook.", 'start': 449.005, 'duration': 1.381}, {'end': 458.874, 'text': "I'll just give a heading over here say accessing values or rather I'll say items.", 'start': 454.372, 'duration': 4.502}, {'end': 464.416, 'text': "So the first method that I'm going to show you is using the key values.", 'start': 461.275, 'duration': 3.141}], 'summary': 'Ways to access dictionary values demonstrated including key value pairs, functions, and for loop.', 'duration': 23.954, 'max_score': 440.462, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI440462.jpg'}], 'start': 94.983, 'title': 'Python dictionaries and nested operations', 'summary': 'Explains the implementation of hash tables in python using built-in dictionaries, demonstrating two creation methods and showcasing nested dictionaries, along with operations such as accessing, updating, and deleting elements using key-value pairs, functions, and for loops.', 'chapters': [{'end': 264.38, 'start': 94.983, 'title': 'Python dictionaries and hash maps', 'summary': 'Explains how hash tables or hash maps in python are implemented through the built-in dictionary data type, and demonstrates two methods to create dictionaries in python, showcasing examples and outputs for each method.', 'duration': 169.397, 'highlights': ['The chapter explains how hash tables or hash maps in python are implemented through the built-in dictionary data type. The built-in dictionary data type in Python is used to implement hash tables or hash maps.', 'Two methods to create dictionaries in python are showcased with examples and outputs for each method. The chapter demonstrates creating dictionaries in python using curly braces and the dict function, providing examples and outputs for both methods.', 'Example of creating a dictionary using curly braces is given, with key-value pairs for employee names and IDs. An example of creating a dictionary using curly braces with key-value pairs for employee names and IDs is demonstrated.', 'Demonstration of creating a dictionary using the dict function with and without parameters is provided, along with the resulting outputs. The chapter provides a demonstration of creating a dictionary using the dict function, both with and without parameters, and showcases the resulting outputs.']}, {'end': 647.928, 'start': 265.141, 'title': 'Nested dictionaries & operations on hash tables', 'summary': 'Covers the concept of nested dictionaries, illustrating their creation and usage in python, followed by a demonstration of accessing, updating, and deleting elements from dictionaries, including using key-value pairs, functions, and for loops.', 'duration': 382.787, 'highlights': ['Nested Dictionaries: Concept and Creation The chapter explains the concept of nested dictionaries with an example of project and teams, demonstrating the creation of nested dictionaries for employee details, including names, IDs, salaries, and designations.', 'Accessing Values in Dictionaries The chapter demonstrates various methods for accessing values in dictionaries, including using key-value pairs, functions like keys, values, and get, as well as iterating through key-value pairs using the for loop.']}], 'duration': 552.945, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI94983.jpg', 'highlights': ['The chapter explains the implementation of hash tables in Python using built-in dictionaries.', 'Two methods to create dictionaries in Python are showcased with examples and outputs for each method.', 'Demonstration of creating a dictionary using the dict function with and without parameters is provided, along with the resulting outputs.', 'The chapter explains the concept of nested dictionaries with an example of project and teams, demonstrating the creation of nested dictionaries for employee details.', 'The chapter demonstrates various methods for accessing values in dictionaries, including using key-value pairs, functions like keys, values, and get, as well as iterating through key-value pairs using the for loop.']}, {'end': 990.591, 'segs': [{'end': 705.153, 'src': 'embed', 'start': 648.908, 'weight': 1, 'content': [{'end': 652.411, 'text': "So now let's move on and see how you can actually update the values of a dictionary.", 'start': 648.908, 'duration': 3.503}, {'end': 657.488, 'text': 'Dictionaries are mutable data types and therefore you can update them as and when required.', 'start': 653.166, 'duration': 4.322}, {'end': 665.272, 'text': 'So in case if you want to change the ID of some employee or if you want to add some new key value pair to your dictionary, you can do it easily.', 'start': 658.169, 'duration': 7.103}, {'end': 668.994, 'text': "So now to show that to you guys, I'll get back to my Jupiter notebook.", 'start': 665.873, 'duration': 3.121}, {'end': 671.075, 'text': "I'll give a new heading.", 'start': 670.195, 'duration': 0.88}, {'end': 674.637, 'text': "I'll say updating.", 'start': 673.817, 'duration': 0.82}, {'end': 681.361, 'text': "So I've already created a dictionary over here.", 'start': 679.46, 'duration': 1.901}, {'end': 683.225, 'text': 'and from that dictionary.', 'start': 682.145, 'duration': 1.08}, {'end': 687.987, 'text': "I'll just change the value of Dave from 0 0 1 to 0 0 4 for that.", 'start': 683.485, 'duration': 4.502}, {'end': 689.688, 'text': "I'll just specify my dict.", 'start': 688.407, 'duration': 1.281}, {'end': 702.452, 'text': "And within this I'll specify the parameter as Dave and the value I'll change it from 0 0 1 to 0 0 4.", 'start': 692.408, 'duration': 10.044}, {'end': 705.153, 'text': 'Now, I want to add some new value to my dictionary.', 'start': 702.452, 'duration': 2.701}], 'summary': 'Dictionaries can be updated to change or add key value pairs easily.', 'duration': 56.245, 'max_score': 648.908, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI648908.jpg'}, {'end': 839.323, 'src': 'embed', 'start': 736.511, 'weight': 0, 'content': [{'end': 742.815, 'text': "You can also see over here that I've added a new key value pair and the key is Chris and the value is not not three.", 'start': 736.511, 'duration': 6.304}, {'end': 744.897, 'text': 'So I hope you guys are clear with this.', 'start': 743.516, 'duration': 1.381}, {'end': 750.901, 'text': "Okay So now let's get back to our presentation and see how we can actually delete items from a dictionary.", 'start': 744.917, 'duration': 5.984}, {'end': 758.986, 'text': 'There are a number of functions that allow you to delete items from a dictionary, such as the del function, the pop function, the pop item function,', 'start': 751.561, 'duration': 7.425}, {'end': 759.947, 'text': 'clear Etc.', 'start': 758.986, 'duration': 0.961}, {'end': 764.189, 'text': "So to implement this I'll get back to my Jupiter notebook and over here.", 'start': 760.627, 'duration': 3.562}, {'end': 773.836, 'text': "I'll create a new heading So the first thing that I'm going to do is use the pop function.", 'start': 764.229, 'duration': 9.607}, {'end': 776.537, 'text': "So I'll just copy the name of my dictionary from here.", 'start': 774.496, 'duration': 2.041}, {'end': 780.099, 'text': "And I'll use the pop function with this.", 'start': 776.557, 'duration': 3.542}, {'end': 786.642, 'text': "So the pop function will take one parameter and it's going to remove that key value pair from my dictionary.", 'start': 781.5, 'duration': 5.142}, {'end': 790.044, 'text': "So the specify Eva and I'll hit run.", 'start': 787.102, 'duration': 2.942}, {'end': 795.787, 'text': 'So as you can see over here the pop function has removed and returned the item from the dictionary.', 'start': 791.044, 'duration': 4.743}, {'end': 802.61, 'text': "So there's another function called as the pop item function which will remove the last inserted element from my dictionary.", 'start': 796.525, 'duration': 6.085}, {'end': 807.974, 'text': "So for that all I'm going to do is specify my dict dot pop item.", 'start': 803.07, 'duration': 4.904}, {'end': 811.216, 'text': 'And then I hit run.', 'start': 810.536, 'duration': 0.68}, {'end': 818.862, 'text': 'Okay, So, as you all know, the last item that I had added to my dictionary was Chris having the value of not, not three.', 'start': 812.097, 'duration': 6.765}, {'end': 821.484, 'text': 'pop item has removed that and returned it as well.', 'start': 818.862, 'duration': 2.622}, {'end': 827.916, 'text': 'So to use the delete function, all you have to do is specify del followed by the name of the dictionary.', 'start': 822.313, 'duration': 5.603}, {'end': 833.74, 'text': "And to this you'll have to specify the key whose value you want to remove from your dictionary.", 'start': 829.537, 'duration': 4.203}, {'end': 836.741, 'text': "So here I'll just specify Dave and I'll hit run.", 'start': 834.4, 'duration': 2.341}, {'end': 839.323, 'text': "Finally, I'll just print out my dictionary.", 'start': 837.542, 'duration': 1.781}], 'summary': 'Demonstrates deleting items from a dictionary using pop, pop item, and del functions.', 'duration': 102.812, 'max_score': 736.511, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI736511.jpg'}, {'end': 893.252, 'src': 'embed', 'start': 864.551, 'weight': 7, 'content': [{'end': 869.173, 'text': 'a data frame is a two-dimensional data structure that consists of columns of various types.', 'start': 864.551, 'duration': 4.622}, {'end': 874.515, 'text': 'It is very similar to Python dictionary and you can even convert a dictionary into a pandas data frame.', 'start': 869.653, 'duration': 4.862}, {'end': 878.097, 'text': "So now to convert this I'll get back to my Jupiter notebook.", 'start': 875.316, 'duration': 2.781}, {'end': 893.252, 'text': 'Okay, So, as you all have seen previously, I had created a nested dictionary containing employee names and their details.', 'start': 886.71, 'duration': 6.542}], 'summary': 'Data frame is a 2d structure, similar to python dictionary. can convert dictionary to pandas data frame.', 'duration': 28.701, 'max_score': 864.551, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI864551.jpg'}, {'end': 970.615, 'src': 'heatmap', 'start': 942.528, 'weight': 1, 'content': [{'end': 945.309, 'text': 'I should have written the complete name of the library, which is pandas.', 'start': 942.528, 'duration': 2.781}, {'end': 947.369, 'text': "Okay, so now I'll just hit run.", 'start': 946.129, 'duration': 1.24}, {'end': 954.111, 'text': 'So as you all can see a clear table has been created for the dictionary which I had created earlier.', 'start': 949.25, 'duration': 4.861}, {'end': 956.872, 'text': 'So this brings us to the end of this session.', 'start': 955.011, 'duration': 1.861}, {'end': 960.993, 'text': 'I hope you guys are clear with all that has been shared with you in this tutorial.', 'start': 957.612, 'duration': 3.381}, {'end': 965.374, 'text': 'Make sure you practice as much as possible and revert your experience.', 'start': 961.813, 'duration': 3.561}, {'end': 970.615, 'text': 'in case you have any doubts or queries, please do let me know in the comment section, and I will revert to you at the earliest.', 'start': 965.374, 'duration': 5.241}], 'summary': 'Demonstrated pandas library usage to create a table from a dictionary.', 'duration': 28.087, 'max_score': 942.528, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI942528.jpg'}, {'end': 990.591, 'src': 'embed', 'start': 965.374, 'weight': 9, 'content': [{'end': 970.615, 'text': 'in case you have any doubts or queries, please do let me know in the comment section, and I will revert to you at the earliest.', 'start': 965.374, 'duration': 5.241}, {'end': 972.536, 'text': 'Goodbye and take care.', 'start': 971.416, 'duration': 1.12}, {'end': 975.581, 'text': 'I hope you have enjoyed listening to this video.', 'start': 973.439, 'duration': 2.142}, {'end': 983.526, 'text': 'Please be kind enough to like it and you can comment any of your doubts and queries and we will reply them at the earliest.', 'start': 975.941, 'duration': 7.585}, {'end': 989.39, 'text': 'Do look out for more videos in our playlist and subscribe to Edureka channel to learn more.', 'start': 983.906, 'duration': 5.484}, {'end': 990.591, 'text': 'Happy learning!.', 'start': 989.95, 'duration': 0.641}], 'summary': 'Encouraging viewers to engage with the video, like, comment, and subscribe for more content.', 'duration': 25.217, 'max_score': 965.374, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI965374.jpg'}], 'start': 648.908, 'title': 'Dictionary operations', 'summary': 'Covers updating dictionary values, demonstrating mutability and modification, deleting items using del, pop, and pop item functions, and converting a dictionary into a pandas data frame, including creating a data frame from a nested dictionary.', 'chapters': [{'end': 736.51, 'start': 648.908, 'title': 'Updating dictionary values', 'summary': 'Discusses the process of updating values in a dictionary, highlighting its mutability and ease of modification. an example demonstrates changing the value associated with a specific key and adding a new key-value pair.', 'duration': 87.602, 'highlights': ['The chapter emphasizes the mutability of dictionaries, allowing for easy updates as and when required, illustrating the flexibility of this data type.', "An example is provided where the value associated with the key 'Dave' is changed from '001' to '004', showcasing the process of updating specific key-value pairs within a dictionary.", "The addition of a new key-value pair ('Chris' : '003') to the dictionary is demonstrated, highlighting the ease of expanding the dictionary with new data."]}, {'end': 839.323, 'start': 736.511, 'title': 'Deleting items from a dictionary', 'summary': 'Explains how to delete items from a dictionary using functions like del, pop, and pop item, removing key-value pairs and demonstrating the removal process with examples.', 'duration': 102.812, 'highlights': ['The chapter covers various functions for deleting items from a dictionary, including del, pop, and pop item.', 'The pop function removes a specified key-value pair from the dictionary, demonstrating the removal process with an example.', 'The pop item function removes the last inserted element from the dictionary, illustrated with an example of removing the last added item from the dictionary.', 'The process of using the delete function to remove a specified key-value pair from the dictionary is explained with an example.']}, {'end': 990.591, 'start': 844.086, 'title': 'Convert dictionary to data frame', 'summary': 'Explains how to convert a python dictionary into a pandas data frame, using an example of creating a data frame from a nested dictionary, highlighting the process and the outcome.', 'duration': 146.505, 'highlights': ['A data frame is a two-dimensional data structure that consists of columns of various types, similar to a Python dictionary, and can be converted into a pandas data frame. Explains the concept of a data frame and its similarity to a Python dictionary.', 'Demonstrates the process of converting a nested dictionary into a data frame using the pandas library, creating a clear table for the dictionary. Demonstrates the process of converting a nested dictionary into a data frame using the pandas library, creating a clear table for the dictionary.', 'Encourages practice and invites questions and doubts, offering assistance and support for further learning. Encourages practice, invites questions and doubts, and offers assistance and support for further learning.']}], 'duration': 341.683, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/APAbRkrqDVI/pics/APAbRkrqDVI648908.jpg', 'highlights': ["The addition of a new key-value pair ('Chris' : '003') to the dictionary is demonstrated, highlighting the ease of expanding the dictionary with new data.", "An example is provided where the value associated with the key 'Dave' is changed from '001' to '004', showcasing the process of updating specific key-value pairs within a dictionary.", 'The chapter emphasizes the mutability of dictionaries, allowing for easy updates as and when required, illustrating the flexibility of this data type.', 'The chapter covers various functions for deleting items from a dictionary, including del, pop, and pop item.', 'The process of using the delete function to remove a specified key-value pair from the dictionary is explained with an example.', 'The pop function removes a specified key-value pair from the dictionary, demonstrating the removal process with an example.', 'The pop item function removes the last inserted element from the dictionary, illustrated with an example of removing the last added item from the dictionary.', 'Demonstrates the process of converting a nested dictionary into a data frame using the pandas library, creating a clear table for the dictionary.', 'A data frame is a two-dimensional data structure that consists of columns of various types, similar to a Python dictionary, and can be converted into a pandas data frame. Explains the concept of a data frame and its similarity to a Python dictionary.', 'Encourages practice and invites questions and doubts, offering assistance and support for further learning.']}], 'highlights': ['Covers the comprehensive discussion on hash tables and hash maps in Python, including implementation of dictionaries, nested dictionaries, operations on hash tables, and conversion to pandas data frame.', 'Explains the concept of a hash table or hash map as a data structure that maps keys to value pairs.', 'Demonstration of creating a dictionary using the dict function with and without parameters is provided, along with the resulting outputs.', 'The chapter demonstrates various methods for accessing values in dictionaries, including using key-value pairs, functions like keys, values, and get, as well as iterating through key-value pairs using the for loop.', "The addition of a new key-value pair ('Chris' : '003') to the dictionary is demonstrated, highlighting the ease of expanding the dictionary with new data.", "An example is provided where the value associated with the key 'Dave' is changed from '001' to '004', showcasing the process of updating specific key-value pairs within a dictionary.", 'The chapter emphasizes the mutability of dictionaries, allowing for easy updates as and when required, illustrating the flexibility of this data type.', 'The chapter covers various functions for deleting items from a dictionary, including del, pop, and pop item.', 'The process of using the delete function to remove a specified key-value pair from the dictionary is explained with an example.', 'The pop function removes a specified key-value pair from the dictionary, demonstrating the removal process with an example.', 'The pop item function removes the last inserted element from the dictionary, illustrated with an example of removing the last added item from the dictionary.', 'Demonstrates the process of converting a nested dictionary into a data frame using the pandas library, creating a clear table for the dictionary.', 'A data frame is a two-dimensional data structure that consists of columns of various types, similar to a Python dictionary, and can be converted into a pandas data frame. Explains the concept of a data frame and its similarity to a Python dictionary.']}