title
Tutorial 8- Matplotlib (Simple Visualization Library)

description
Hello All, Welcome to the Python Crash Course. In this video we will understand about as a simple visualization library called as matplotlib library github url : https://github.com/krishnaik06/Machine-Learning-in-90-days Support me in Patreon: https://www.patreon.com/join/2340909? Connect with me here: Twitter: https://twitter.com/Krishnaik06 Facebook: https://www.facebook.com/krishnaik06 instagram: https://www.instagram.com/krishnaik06 If you like music support my brother's channel https://www.youtube.com/channel/UCdupFqYIc6VMO-pXVlvmM4Q Buy the Best book of Machine Learning, Deep Learning with python sklearn and tensorflow from below amazon url: https://www.amazon.in/Hands-Machine-Learning-Scikit-Learn-Tensor/dp/9352135210/ref=as_sl_pc_qf_sp_asin_til?tag=krishnaik06-21&linkCode=w00&linkId=a706a13cecffd115aef76f33a760e197&creativeASIN=9352135210 You can buy my book on Finance with Machine Learning and Deep Learning from the below url amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=as_sl_pc_qf_sp_asin_til?tag=krishnaik06-21&linkCode=w00&linkId=ac229c9a45954acc19c1b2fa2ca96e23&creativeASIN=1789346371 Subscribe my unboxing Channel https://www.youtube.com/channel/UCjWY5hREA6FFYrthD0rZNIw Below are the various playlist created on ML,Data Science and Deep Learning. Please subscribe and support the channel. Happy Learning! Deep Learning Playlist: https://www.youtube.com/watch?v=DKSZHN7jftI&list=PLZoTAELRMXVPGU70ZGsckrMdr0FteeRUi Data Science Projects playlist: https://www.youtube.com/watch?v=5Txi0nHIe0o&list=PLZoTAELRMXVNUcr7osiU7CCm8hcaqSzGw NLP playlist: https://www.youtube.com/watch?v=6ZVf1jnEKGI&list=PLZoTAELRMXVMdJ5sqbCK2LiM0HhQVWNzm Statistics Playlist: https://www.youtube.com/watch?v=GGZfVeZs_v4&list=PLZoTAELRMXVMhVyr3Ri9IQ-t5QPBtxzJO Feature Engineering playlist: https://www.youtube.com/watch?v=NgoLMsaZ4HU&list=PLZoTAELRMXVPwYGE2PXD3x0bfKnR0cJjN Computer Vision playlist: https://www.youtube.com/watch?v=mT34_yu5pbg&list=PLZoTAELRMXVOIBRx0andphYJ7iakSg3Lk Data Science Interview Question playlist: https://www.youtube.com/watch?v=820Qr4BH0YM&list=PLZoTAELRMXVPkl7oRvzyNnyj1HS4wt2K- You can buy my book on Finance with Machine Learning and Deep Learning from the below url amazon url: https://www.amazon.in/Hands-Python-Finance-implementing-strategies/dp/1789346371/ref=sr_1_1?keywords=krish+naik&qid=1560943725&s=gateway&sr=8-1 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 THINGS to support my channel LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL

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{'title': 'Tutorial 8- Matplotlib (Simple Visualization Library)', 'heatmap': [{'end': 141.554, 'start': 120.427, 'weight': 0.745}, {'end': 205.528, 'start': 187.084, 'weight': 0.746}, {'end': 815.758, 'start': 771.632, 'weight': 0.75}, {'end': 845.532, 'start': 823.1, 'weight': 0.726}, {'end': 1016.024, 'start': 960.467, 'weight': 1}], 'summary': 'This tutorial covers the introduction to matplotlib in python, creating 2d visualization diagrams, line styles, subplot creation, visualization techniques including sine and cosine waves, bar plots, histograms, and box plots, and understanding percentiles and pie charts. it emphasizes the use of matplotlib for creating beautiful visualization diagrams and sharing them as png files.', 'chapters': [{'end': 162.691, 'segs': [{'end': 51.784, 'src': 'embed', 'start': 18.372, 'weight': 0, 'content': [{'end': 22.953, 'text': 'Suppose you want to see some plotting of a data set in 2D or 3D, you can basically use matplotlib.', 'start': 18.372, 'duration': 4.581}, {'end': 26.694, 'text': 'So let us begin and try to understand what exactly is matplotlib.', 'start': 23.474, 'duration': 3.22}, {'end': 32.856, 'text': "So matplotlib is a plotting library from Python programming language and it's numerical mathematical extension numpy.", 'start': 27.155, 'duration': 5.701}, {'end': 41.098, 'text': 'So in matplotlib again the base library is numpy and you know it provides an object-oriented API for embedding plots into applications.', 'start': 33.376, 'duration': 7.722}, {'end': 46.461, 'text': 'Again guys the other visualization library which is very very much important is CBON.', 'start': 41.638, 'duration': 4.823}, {'end': 49.503, 'text': 'First of all we will try to discuss about Matplotlib.', 'start': 47.301, 'duration': 2.202}, {'end': 51.784, 'text': 'We will try to see some of the examples in Matplotlib.', 'start': 49.523, 'duration': 2.261}], 'summary': 'Matplotlib is a plotting library from python, with numpy as its base library and an api for embedding plots. cbon is another important visualization library.', 'duration': 33.412, 'max_score': 18.372, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos18372.jpg'}, {'end': 99.464, 'src': 'embed', 'start': 70.968, 'weight': 2, 'content': [{'end': 80.013, 'text': "which you can later save it as a PNG file and share with your stakeholders whenever you're creating some visualization report.", 'start': 70.968, 'duration': 9.045}, {'end': 83.735, 'text': 'Let us go ahead and try to understand how to import matplotlib.', 'start': 80.533, 'duration': 3.202}, {'end': 91.919, 'text': 'So to begin with, in order to import matplotlib, we will basically be using import matplotlib.pyplot as PLT.', 'start': 83.775, 'duration': 8.144}, {'end': 99.464, 'text': 'Again, the PLT is an alias and matplotlib.pyplot is the library that we will be basically using.', 'start': 92.278, 'duration': 7.186}], 'summary': 'Learn how to import matplotlib for visualization using plt alias.', 'duration': 28.496, 'max_score': 70.968, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos70968.jpg'}, {'end': 147.041, 'src': 'heatmap', 'start': 120.427, 'weight': 0.745, 'content': [{'end': 126.589, 'text': 'But if you are using this particular line within your cell, at that time you need not write plot.show.', 'start': 120.427, 'duration': 6.162}, {'end': 133.151, 'text': 'Directly you can execute the codes which I will be showing you right now and by that you will be able to see the diagrams itself.', 'start': 127.249, 'duration': 5.902}, {'end': 136.432, 'text': 'So let us go ahead and first of all import numpy.', 'start': 133.711, 'duration': 2.721}, {'end': 138.693, 'text': 'So I am importing numpy as np.', 'start': 136.952, 'duration': 1.741}, {'end': 141.554, 'text': 'I have created two variables x and y.', 'start': 138.793, 'duration': 2.761}, {'end': 143.675, 'text': 'Here you can see x is np.arrange.', 'start': 141.554, 'duration': 2.121}, {'end': 147.041, 'text': 'and you know why arrange is basically used.', 'start': 144.457, 'duration': 2.584}], 'summary': 'Demonstrating how to use numpy to create variables and execute code for generating diagrams.', 'duration': 26.614, 'max_score': 120.427, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos120427.jpg'}, {'end': 175.943, 'src': 'embed', 'start': 144.457, 'weight': 3, 'content': [{'end': 147.041, 'text': 'and you know why arrange is basically used.', 'start': 144.457, 'duration': 2.584}, {'end': 149.766, 'text': 'again, arrange is used for creating an array.', 'start': 147.041, 'duration': 2.725}, {'end': 158.088, 'text': 'It usually takes the range between start and stop, which we have already discussed in my previous videos of Python tutorial, right?', 'start': 151.542, 'duration': 6.546}, {'end': 160.85, 'text': "So here I'll be giving my start and stop value.", 'start': 158.588, 'duration': 2.262}, {'end': 162.691, 'text': "Similarly, I'll be creating my Y array.", 'start': 160.89, 'duration': 1.801}, {'end': 171.419, 'text': 'And since I need to create a 2D graph, okay, 2D diagram or 2D visualization diagram, I at least require two variables.', 'start': 163.452, 'duration': 7.967}, {'end': 175.943, 'text': "So one variable I've created as X, the another variable I've created as Y.", 'start': 171.879, 'duration': 4.064}], 'summary': 'Using arrange to create arrays for 2d graph visualization.', 'duration': 31.486, 'max_score': 144.457, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos144457.jpg'}], 'start': 1.055, 'title': 'Introduction to matplotlib in python', 'summary': 'Introduces matplotlib as a powerful visualization library in python, emphasizing its use for creating 2d diagrams and highlighting the importance of understanding both matplotlib and cbon for creating beautiful visualization diagrams and sharing them as png files.', 'chapters': [{'end': 162.691, 'start': 1.055, 'title': 'Introduction to matplotlib in python', 'summary': 'Introduces matplotlib as a powerful visualization library in python, emphasizing its use for creating 2d diagrams and highlighting the importance of understanding both matplotlib and cbon for creating beautiful visualization diagrams and sharing them as png files.', 'duration': 161.636, 'highlights': ['Matplotlib is introduced as a powerful visualization library in Python, emphasizing its use for creating 2D diagrams and its importance in exploratory data analysis for applying statistical analysis.', 'CBON is highlighted as another important visualization library in Python, emphasizing the importance of understanding both Matplotlib and CBON for creating beautiful visualization diagrams and sharing them as PNG files.', "The process of importing Matplotlib and setting it up for display in Jupyter Notebook is explained, emphasizing the use of 'matplotlib.pyplot' and 'inline' for displaying matplotlib graphs or diagrams.", 'The usage of numpy.arrange for creating an array and its application in defining the range between start and stop values is demonstrated.']}], 'duration': 161.636, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos1055.jpg', 'highlights': ['Matplotlib is introduced as a powerful visualization library in Python, emphasizing its use for creating 2D diagrams and its importance in exploratory data analysis for applying statistical analysis.', 'CBON is highlighted as another important visualization library in Python, emphasizing the importance of understanding both Matplotlib and CBON for creating beautiful visualization diagrams and sharing them as PNG files.', "The process of importing Matplotlib and setting it up for display in Jupyter Notebook is explained, emphasizing the use of 'matplotlib.pyplot' and 'inline' for displaying matplotlib graphs or diagrams.", 'The usage of numpy.arrange for creating an array and its application in defining the range between start and stop values is demonstrated.']}, {'end': 476.599, 'segs': [{'end': 212.223, 'src': 'heatmap', 'start': 187.084, 'weight': 0, 'content': [{'end': 190.745, 'text': 'Here first of all I am starting with something called a scattered plot.', 'start': 187.084, 'duration': 3.661}, {'end': 197.706, 'text': 'A scattered plot is basically used to scatter the values of x and y and it will be scattering it in a 2D graph.', 'start': 191.285, 'duration': 6.421}, {'end': 205.528, 'text': 'So inside the scatter if you press shift tab you will be having your first value as the x-axis value and y-axis value.', 'start': 198.206, 'duration': 7.322}, {'end': 209.479, 'text': 'and s is basically the solid value.', 'start': 206.536, 'duration': 2.943}, {'end': 212.223, 'text': 'c is basically the color and this will be in pixels.', 'start': 209.479, 'duration': 2.744}], 'summary': 'Scatter plot visualizes x and y values in 2d graph with s as size and c as color.', 'duration': 48.771, 'max_score': 187.084, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos187084.jpg'}, {'end': 387.593, 'src': 'embed', 'start': 363.502, 'weight': 1, 'content': [{'end': 369.647, 'text': 'And if you just go to the same working location, you can see over here, I have this particular image that is got saved that is called as desktop.', 'start': 363.502, 'duration': 6.145}, {'end': 372.028, 'text': 'okay, pretty much simple.', 'start': 369.947, 'duration': 2.081}, {'end': 373.668, 'text': 'so you can do all these things now.', 'start': 372.028, 'duration': 1.64}, {'end': 378.13, 'text': 'another function inside matplotlib is something called as plot.', 'start': 373.668, 'duration': 4.462}, {'end': 384.452, 'text': 'okay now, if you want to use plot before, i have actually shown you scatter now you will be seeing plot.', 'start': 378.13, 'duration': 6.322}, {'end': 385.252, 'text': 'in plot.', 'start': 384.452, 'duration': 0.8}, {'end': 387.593, 'text': 'you will be specifically getting a straight line.', 'start': 385.252, 'duration': 2.341}], 'summary': 'Using matplotlib, you can create a plot with a straight line.', 'duration': 24.091, 'max_score': 363.502, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos363502.jpg'}, {'end': 455.087, 'src': 'embed', 'start': 430.261, 'weight': 2, 'content': [{'end': 438.602, 'text': 'okay now, uh, If you go and see some more parameters inside this plot or something like line width, I will be showing you everything.', 'start': 430.261, 'duration': 8.341}, {'end': 441.443, 'text': 'First of all, let me just show you X and Y.', 'start': 439.122, 'duration': 2.321}, {'end': 451.005, 'text': 'As soon as I write X and Y, let me just write Y is equal to X square first of all because always we should just not get a straight line.', 'start': 441.443, 'duration': 9.562}, {'end': 452.466, 'text': 'We will see some other examples also.', 'start': 451.025, 'duration': 1.441}, {'end': 455.087, 'text': 'I will write plot is equal to x comma y.', 'start': 453.146, 'duration': 1.941}], 'summary': 'Demonstrating plot parameters, showing x and y relationship with y=x^2.', 'duration': 24.826, 'max_score': 430.261, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos430261.jpg'}], 'start': 163.452, 'title': '2d visualization and matplotlib', 'summary': 'Discusses creating a 2d visualization diagram with x and y variables, allowing customization of color. it also covers creating and customizing plots using matplotlib, including inline execution, labeling axes, titling graphs, and saving images, and demonstrates the use of the plot function to create a straight line.', 'chapters': [{'end': 232.983, 'start': 163.452, 'title': 'Creating 2d visualization diagram', 'summary': 'Discusses the creation of a 2d visualization diagram using two variables, x and y, to display a scattered plot in a 2d graph, allowing customization of color and other visual attributes.', 'duration': 69.531, 'highlights': ['The chapter explains the creation of a scattered plot to display the values of x and y in a 2D graph, offering customization options for color and size.', 'It mentions the use of variables X and Y to create a 2D visualization diagram, emphasizing the importance of having at least two variables for the process.']}, {'end': 476.599, 'start': 232.983, 'title': 'Matplotlib: creating and customizing plots', 'summary': 'Covers the process of creating and customizing plots using matplotlib, including inline execution, labeling x and y axes, titling graphs, and saving images, and demonstrates the use of the plot function to create a straight line with examples of customizing color and line width.', 'duration': 243.616, 'highlights': ['The chapter demonstrates the process of creating and customizing plots using Matplotlib, including inline execution, labeling x and y axes, titling graphs, and saving images. The process of creating and customizing plots using Matplotlib, including inline execution, labeling x and y axes, titling graphs, and saving images.', 'The chapter covers the use of the plot function to create a straight line with examples of customizing color and line width. Demonstrates the use of the plot function to create a straight line with examples of customizing color and line width.', 'The chapter also shows examples of customizing colors for the plots, such as using red color for the line. Examples of customizing colors for the plots, such as using red color for the line.']}], 'duration': 313.147, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos163452.jpg', 'highlights': ['The chapter explains the creation of a scattered plot to display the values of x and y in a 2D graph, offering customization options for color and size.', 'The chapter demonstrates the process of creating and customizing plots using Matplotlib, including inline execution, labeling x and y axes, titling graphs, and saving images.', 'The chapter covers the use of the plot function to create a straight line with examples of customizing color and line width.', 'It mentions the use of variables X and Y to create a 2D visualization diagram, emphasizing the importance of having at least two variables for the process.']}, {'end': 782.196, 'segs': [{'end': 556.642, 'src': 'embed', 'start': 527.427, 'weight': 0, 'content': [{'end': 532.029, 'text': 'all the different different formats are there and it will be pretty much simple for you to understand.', 'start': 527.427, 'duration': 4.602}, {'end': 539.309, 'text': 'okay, so you can basically see all the different different values inside this and you can basically check it out.', 'start': 532.029, 'duration': 7.28}, {'end': 547.015, 'text': 'apart from this, uh, you can also give different different values like this, like line style, their values, like line style in line style.', 'start': 539.309, 'duration': 7.706}, {'end': 551.619, 'text': 'instead of just giving dash dash over here, you can also provide dashed values over here again.', 'start': 547.015, 'duration': 4.604}, {'end': 556.642, 'text': 'apart from this, there are other things also which you can verify after pressing shift tab.', 'start': 551.619, 'duration': 5.023}], 'summary': 'Various formats and values can be easily understood and checked, including line styles and values, with the option to verify additional elements by pressing shift tab.', 'duration': 29.215, 'max_score': 527.427, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos527427.jpg'}, {'end': 657.649, 'src': 'embed', 'start': 611.106, 'weight': 2, 'content': [{'end': 620.234, 'text': "Again, guys, if you are working on a real exploratory data analysis, this styling won't matter much, because when we'll go into CBON,", 'start': 611.106, 'duration': 9.128}, {'end': 622.917, 'text': "we'll be seeing a lot of examples, which is pretty much good.", 'start': 620.234, 'duration': 2.683}, {'end': 627.583, 'text': "And I think after seeing Seaborn, you won't be even using matplotlib.", 'start': 623.661, 'duration': 3.922}, {'end': 630.965, 'text': "So I'm just trying to show you all the basic things that are actually required.", 'start': 627.603, 'duration': 3.362}, {'end': 633.467, 'text': 'Now we can also create subplots.', 'start': 631.346, 'duration': 2.121}, {'end': 640.131, 'text': 'Subplots basically means that within one canvas, within one diagram, I can create multiple subplots inside that.', 'start': 634.167, 'duration': 5.964}, {'end': 647.856, 'text': 'So the function that is used is something called as plt.subplot and here I can press shift tab.', 'start': 640.891, 'duration': 6.965}, {'end': 655.247, 'text': 'As soon as I do shift tab, you will be seeing that we require two basic parameters, three basic parameters.', 'start': 649.764, 'duration': 5.483}, {'end': 657.649, 'text': 'One is number of rows, number of columns.', 'start': 655.347, 'duration': 2.302}], 'summary': 'Exploratory data analysis includes examples in cbon, transition from seaborn to matplotlib, creation of subplots within one diagram.', 'duration': 46.543, 'max_score': 611.106, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos611106.jpg'}], 'start': 476.599, 'title': 'Matplotlib line styles and subplot creation', 'summary': 'Explains line styles in matplotlib, including dashed lines, scatter plots, line width, and marker size, along with creating subplots using plt.subplot to position graphs and make changes to the plots.', 'chapters': [{'end': 633.467, 'start': 476.599, 'title': 'Different line styles in matplotlib', 'summary': 'Explains the various line styles and formatting options available in matplotlib, including dashed lines, scatter plots, line styles, line width, marker size, and the use of labels and titles, providing a comprehensive overview to aid in understanding and usage of the library.', 'duration': 156.868, 'highlights': ['The chapter covers various line styles and formatting options in Matplotlib, including dashed lines, scatter plots, line styles, line width, marker size, and the use of labels and titles. This is the main highlight encompassing the different line styles and formatting options available in Matplotlib, providing a comprehensive overview.', 'The demonstration of different line styles and formatting options will aid in better understanding and usage of the library. This emphasizes the usefulness of the demonstration in aiding understanding and usage of the Matplotlib library.', 'The mention of Seaborn indicates its potential superiority over Matplotlib for exploratory data analysis. This highlights the potential shift from using Matplotlib to Seaborn due to its advantages, indicating the evolving practices in data analysis.', "The explanation includes creating subplots, indicating the breadth of coverage in the chapter. This showcases the comprehensive nature of the chapter's coverage, including the creation of subplots."]}, {'end': 782.196, 'start': 634.167, 'title': 'Creating subplots with plt.subplot', 'summary': 'Explains how to use plt.subplot to create multiple subplots within one canvas, allowing for the placement of graphs in different positions, with an example of creating four subplots in a 2x2 grid and making changes to the plots such as colors and styles.', 'duration': 148.029, 'highlights': ['The function plt.subplot is used to create multiple subplots within one canvas, requiring parameters for the number of rows, number of columns, and position, such as plt.subplot(2, 2, 1) to place a plot in the first position.', 'Demonstration of creating four subplots in a 2x2 grid by specifying the position for each plot, allowing for making changes to the plots such as colors and styles like double dash or scattered plot.', 'An example of selecting values between one to 10 in an array and an assignment to plot the fourth plot by specifying plt.subplot(2, 2, 4) to indicate the position.']}], 'duration': 305.597, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos476599.jpg', 'highlights': ['The chapter covers various line styles and formatting options in Matplotlib, providing a comprehensive overview.', 'The demonstration of different line styles and formatting options will aid in better understanding and usage of the library.', 'The mention of Seaborn indicates its potential superiority over Matplotlib for exploratory data analysis.', 'The function plt.subplot is used to create multiple subplots within one canvas, requiring parameters for the number of rows, number of columns, and position.']}, {'end': 1328.435, 'segs': [{'end': 830.803, 'src': 'embed', 'start': 801.813, 'weight': 5, 'content': [{'end': 804.756, 'text': 'And here you will be using np.py.', 'start': 801.813, 'duration': 2.943}, {'end': 807.458, 'text': 'And np.py is basically nothing but 22 by 7, 3.142 approximately.', 'start': 805.296, 'duration': 2.162}, {'end': 815.758, 'text': "Here again, I'm taking array saying as np.arrange between zero to this much value.", 'start': 810.396, 'duration': 5.362}, {'end': 818.819, 'text': 'And the third parameter is basically the step size.', 'start': 816.258, 'duration': 2.561}, {'end': 822.86, 'text': "Then I'm saying that np.sign of x, okay?", 'start': 819.559, 'duration': 3.301}, {'end': 830.803, 'text': 'So that basically means that the sign is a function which will actually take up all the values in this x and it will create.', 'start': 823.1, 'duration': 7.703}], 'summary': 'Utilizing np.py with 22 by 7 (3.142), np.arrange, and np.sign function.', 'duration': 28.99, 'max_score': 801.813, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos801813.jpg'}, {'end': 845.532, 'src': 'heatmap', 'start': 823.1, 'weight': 0.726, 'content': [{'end': 830.803, 'text': 'So that basically means that the sign is a function which will actually take up all the values in this x and it will create.', 'start': 823.1, 'duration': 7.703}, {'end': 833.244, 'text': 'it will basically find out the sign of that value, okay?', 'start': 830.803, 'duration': 2.441}, {'end': 839.046, 'text': 'And if I just execute it, you will be able to see that will also be possible to get this kind of sign wave, okay?', 'start': 833.904, 'duration': 5.142}, {'end': 845.532, 'text': 'Again, these are some more complex diagrams if you are really really interested in forming.', 'start': 839.266, 'duration': 6.266}], 'summary': 'The function creates a sign wave for all x values.', 'duration': 22.432, 'max_score': 823.1, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos823100.jpg'}, {'end': 873.709, 'src': 'embed', 'start': 845.973, 'weight': 0, 'content': [{'end': 850.898, 'text': 'Now, I can also use subplots like how I used over here and I can create sine waves and cos waves.', 'start': 845.973, 'duration': 4.925}, {'end': 857.004, 'text': 'And you know they have inbuilt functions in NumPy like np.sine, np.cos over here.', 'start': 851.018, 'duration': 5.986}, {'end': 859.625, 'text': 'See this np.sign, np.cos.', 'start': 857.765, 'duration': 1.86}, {'end': 865.287, 'text': 'I am taking this x value, finding out my y different different values, and here again I am taking a subplot.', 'start': 859.625, 'duration': 5.662}, {'end': 869.968, 'text': 'see over here, guys, you can download this particular file, but everything is same almost.', 'start': 865.287, 'duration': 4.681}, {'end': 873.709, 'text': 'subplot 2, comma 1 basically indicates two rows, one column.', 'start': 869.968, 'duration': 3.741}], 'summary': 'Demonstrating the use of subplots with sine and cosine waves using numpy functions, showcasing the layout of subplot 2,1.', 'duration': 27.736, 'max_score': 845.973, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos845973.jpg'}, {'end': 1016.024, 'src': 'heatmap', 'start': 960.467, 'weight': 1, 'content': [{'end': 966.748, 'text': "if I don't give this also, it is no need to worry, because, see, I am just plotting the bar of x comma y,", 'start': 960.467, 'duration': 6.281}, {'end': 971.13, 'text': 'so I will execute it and the next is again plot dot bar x2, y2.', 'start': 966.748, 'duration': 4.382}, {'end': 975.711, 'text': 'okay, and bar basically helps us to get a bar plot okay.', 'start': 971.13, 'duration': 4.581}, {'end': 977.953, 'text': 'remember, this is my x value.', 'start': 976.471, 'duration': 1.482}, {'end': 979.255, 'text': 'this is my y value.', 'start': 977.953, 'duration': 1.302}, {'end': 980.997, 'text': 'so like this, you can also compare.', 'start': 979.255, 'duration': 1.742}, {'end': 985.042, 'text': 'you can also compare between different, different list of values.', 'start': 980.997, 'duration': 4.045}, {'end': 986.464, 'text': 'so this was my x1 y1.', 'start': 985.042, 'duration': 1.422}, {'end': 987.926, 'text': 'this was my x2 y2, right.', 'start': 986.464, 'duration': 1.462}, {'end': 994.773, 'text': 'so here you can basically compare different, different bar plots, and this is with respect to the count, and as you go there is.', 'start': 987.926, 'duration': 6.847}, {'end': 997.254, 'text': 'there is also something called as histograms.', 'start': 994.773, 'duration': 2.481}, {'end': 1003.357, 'text': 'now, histograms helps you to find out with respect to the numbers right over here, what is the?', 'start': 997.254, 'duration': 6.103}, {'end': 1007.199, 'text': 'what is the density, what is the count that you can see on the y-axis?', 'start': 1003.357, 'duration': 3.842}, {'end': 1010.061, 'text': 'okay, and that is what histogram basically does.', 'start': 1007.199, 'duration': 2.862}, {'end': 1016.024, 'text': "so if you write plt, dot, hist and just see this definition over here, you'll be able to understand plot, a histogram,", 'start': 1010.061, 'duration': 5.963}], 'summary': 'Plotting bar and histogram, comparing different values and counts.', 'duration': 55.557, 'max_score': 960.467, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos960467.jpg'}, {'end': 1010.061, 'src': 'embed', 'start': 979.255, 'weight': 2, 'content': [{'end': 980.997, 'text': 'so like this, you can also compare.', 'start': 979.255, 'duration': 1.742}, {'end': 985.042, 'text': 'you can also compare between different, different list of values.', 'start': 980.997, 'duration': 4.045}, {'end': 986.464, 'text': 'so this was my x1 y1.', 'start': 985.042, 'duration': 1.422}, {'end': 987.926, 'text': 'this was my x2 y2, right.', 'start': 986.464, 'duration': 1.462}, {'end': 994.773, 'text': 'so here you can basically compare different, different bar plots, and this is with respect to the count, and as you go there is.', 'start': 987.926, 'duration': 6.847}, {'end': 997.254, 'text': 'there is also something called as histograms.', 'start': 994.773, 'duration': 2.481}, {'end': 1003.357, 'text': 'now, histograms helps you to find out with respect to the numbers right over here, what is the?', 'start': 997.254, 'duration': 6.103}, {'end': 1007.199, 'text': 'what is the density, what is the count that you can see on the y-axis?', 'start': 1003.357, 'duration': 3.842}, {'end': 1010.061, 'text': 'okay, and that is what histogram basically does.', 'start': 1007.199, 'duration': 2.862}], 'summary': 'Compare different bar plots and histograms to analyze data.', 'duration': 30.806, 'max_score': 979.255, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos979255.jpg'}, {'end': 1113.896, 'src': 'embed', 'start': 1085.212, 'weight': 3, 'content': [{'end': 1090.214, 'text': 'It specifies the density of this particular numbers that I can find out in this particular array.', 'start': 1085.212, 'duration': 5.002}, {'end': 1092.054, 'text': 'Okay And this is with respect to the count.', 'start': 1090.434, 'duration': 1.62}, {'end': 1095.015, 'text': 'Okay And again, you can increase the bin size also.', 'start': 1092.494, 'duration': 2.521}, {'end': 1097.525, 'text': "Again, don't get confused guys.", 'start': 1096.244, 'duration': 1.281}, {'end': 1098.826, 'text': 'It is pretty much simple.', 'start': 1097.725, 'duration': 1.101}, {'end': 1103.89, 'text': 'Many of them gets confused with this histograms.', 'start': 1100.127, 'duration': 3.763}, {'end': 1109.353, 'text': 'It is just like you have all this range of values, which you can see from here inside this particular array,', 'start': 1104.03, 'duration': 5.323}, {'end': 1113.896, 'text': 'and this particular value says what is the density or what is the count of these numbers.', 'start': 1109.353, 'duration': 4.543}], 'summary': 'The transcript explains the density and count of numbers in an array and the option to adjust bin size.', 'duration': 28.684, 'max_score': 1085.212, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos1085212.jpg'}, {'end': 1283.675, 'src': 'embed', 'start': 1256.987, 'weight': 4, 'content': [{'end': 1263.148, 'text': 'Sometimes, when you are randomly selecting the value, there is a probability that some outliers also get selected okay?', 'start': 1256.987, 'duration': 6.161}, {'end': 1269.07, 'text': 'So because of that, please again, this is just a small example.', 'start': 1263.649, 'duration': 5.421}, {'end': 1283.675, 'text': "We'll see this in exploratory data analysis and probably I'll be using Seaborn to create a box plot because it gives us the visual representation will be pretty much better than this matplotlib.", 'start': 1269.19, 'duration': 14.485}], 'summary': 'Random selection may include outliers, addressed in exploratory data analysis using seaborn for better visual representation.', 'duration': 26.688, 'max_score': 1256.987, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos1256987.jpg'}], 'start': 782.196, 'title': 'Matplotlib visualization techniques', 'summary': 'Demonstrates creating sign waves, cosine waves, bar plots, histograms, and box plots using matplotlib and numpy, emphasizing visualization techniques and methods of representing data. it includes a sine wave diagram using np.py with a step size of 3.142 and an array ranging from 0 to a specified value.', 'chapters': [{'end': 822.86, 'start': 782.196, 'title': 'Creating diagrams with matplotlib', 'summary': 'Demonstrates using matplotlib to create diagrams, including a sine wave diagram using np.py with a step size of 3.142 and an array ranging from 0 to a specified value.', 'duration': 40.664, 'highlights': ['Using matplotlib to create diagrams, including sine wave diagrams using np.py', 'Defining np.py as 22 by 7, approximately 3.142', 'Generating an array using np.arrange with a step size']}, {'end': 1328.435, 'start': 823.1, 'title': 'Matplotlib visualization techniques', 'summary': 'Demonstrates the creation of sign waves, cosine waves, bar plots, histograms, and box plots using matplotlib and numpy, emphasizing the visualization techniques and methods of representing data.', 'duration': 505.335, 'highlights': ['Creation of sign waves and cosine waves using subplots and inbuilt NumPy functions The transcript explains the process of creating sign waves and cosine waves using subplots and inbuilt NumPy functions such as np.sine and np.cos.', 'Demonstration of bar plots to compare different list of values The transcript provides a demonstration of creating bar plots to compare different list of values, showcasing the comparison between x1 y1 and x2 y2.', 'Explanation of histograms to understand density and count of numbers The transcript explains histograms and their use in finding the density and count of numbers, elaborating on the concept of bins and their impact on the representation of data.', 'Insight into box plots for visualizing percentiles and outliers The transcript provides insight into box plots, illustrating their use in visualizing percentiles and outliers in data, including the explanation of the representation of percentiles and identification of outliers.']}], 'duration': 546.239, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos782196.jpg', 'highlights': ['Using matplotlib to create diagrams, including sine wave diagrams using np.py', 'Creation of sign waves and cosine waves using subplots and inbuilt NumPy functions', 'Demonstration of bar plots to compare different list of values', 'Explanation of histograms to understand density and count of numbers', 'Insight into box plots for visualizing percentiles and outliers', 'Defining np.py as 22 by 7, approximately 3.142', 'Generating an array using np.arrange with a step size']}, {'end': 1554.213, 'segs': [{'end': 1359.087, 'src': 'embed', 'start': 1328.435, 'weight': 0, 'content': [{'end': 1329.596, 'text': 'uh, you know, rotated.', 'start': 1328.435, 'duration': 1.161}, {'end': 1332.037, 'text': 'in short, i mean horizontally rotate, rotated.', 'start': 1329.596, 'duration': 2.441}, {'end': 1333.838, 'text': 'initially it was vertical right.', 'start': 1332.037, 'duration': 1.801}, {'end': 1335.058, 'text': 'so it is up to you.', 'start': 1333.838, 'duration': 1.22}, {'end': 1341.661, 'text': 'whichever look you want, you can basically select it, but i i prefer a vertical look because that helps me to give a good representation.', 'start': 1335.058, 'duration': 6.603}, {'end': 1350.603, 'text': 'remember, guys, this is zero percentile 25, 50, 75, 100 percentile and if you know about cat and gate exams, if you have given that,', 'start': 1342.939, 'duration': 7.664}, {'end': 1354.885, 'text': "you probably think, uh, you'll probably know how the percentile actually works.", 'start': 1350.603, 'duration': 4.282}, {'end': 1359.087, 'text': "okay, and if you don't know about that, please go and have a look on to my.", 'start': 1354.885, 'duration': 4.202}], 'summary': 'The speaker discusses rotating the representation, preferring a vertical look for better representation, and mentions the significance of percentiles in exams.', 'duration': 30.652, 'max_score': 1328.435, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos1328435.jpg'}, {'end': 1404.87, 'src': 'embed', 'start': 1373.545, 'weight': 1, 'content': [{'end': 1375.848, 'text': "in pie chart i'm taking some labels.", 'start': 1373.545, 'duration': 2.303}, {'end': 1382.698, 'text': "uh, so pie chart is basically like you probably haven't seen this kind of diagrams in your high school or your engineering days.", 'start': 1375.848, 'duration': 6.85}, {'end': 1386.133, 'text': 'this will actually and over here.', 'start': 1384.031, 'duration': 2.102}, {'end': 1389.335, 'text': "the first thing is that I'll be using this plot dot PI.", 'start': 1386.133, 'duration': 3.202}, {'end': 1392.598, 'text': 'in plot dot PI, there are four parameters you specifically give.', 'start': 1389.335, 'duration': 3.263}, {'end': 1394.24, 'text': 'one is your sizes sizes.', 'start': 1392.598, 'duration': 1.642}, {'end': 1400.225, 'text': 'is basically this kind of size okay, and this size is the cumulative.', 'start': 1394.24, 'duration': 5.985}, {'end': 1404.87, 'text': 'suppose, if this is the size that I am selecting, it will be based on the cumulative total.', 'start': 1400.225, 'duration': 4.645}], 'summary': 'Introduction to pie chart and its parameters for data visualization.', 'duration': 31.325, 'max_score': 1373.545, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos1373545.jpg'}, {'end': 1552.892, 'src': 'embed', 'start': 1526.956, 'weight': 4, 'content': [{'end': 1532.479, 'text': 'particular videos, guys, and I hope you have pretty much discussed about matplotlib and seen different types of diagrams.', 'start': 1526.956, 'duration': 5.523}, {'end': 1542.646, 'text': 'But, trust me, in exploratory data analysis We will try to mostly look on to, you know, seaborn diagrams because they are pretty much good.', 'start': 1532.479, 'duration': 10.167}, {'end': 1546.328, 'text': 'They are pretty much simple and a lot of statistical analysis.', 'start': 1542.646, 'duration': 3.682}, {'end': 1550.791, 'text': 'You can also perform into that So this was all about this particular video in the next video.', 'start': 1546.348, 'duration': 4.443}, {'end': 1552.892, 'text': "I'll be coming up with seaborn tutorial.", 'start': 1550.811, 'duration': 2.081}], 'summary': 'Exploratory data analysis will focus on seaborn diagrams for simplicity and statistical analysis.', 'duration': 25.936, 'max_score': 1526.956, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos1526956.jpg'}], 'start': 1328.435, 'title': 'Understanding percentile, pie chart, and matplotlib', 'summary': 'Explains the concept of percentile in exams like cat and gate, introduces pie chart calculation for a total value of 800, and discusses parameters for creating pie charts in matplotlib, emphasizing the use of seaborn diagrams for exploratory data analysis.', 'chapters': [{'end': 1394.24, 'start': 1328.435, 'title': 'Understanding percentile and pie charts', 'summary': 'Explains the concept of percentile with respect to exams like cat and gate, and introduces the topic of pie charts, emphasizing the use of vertical look for better representation.', 'duration': 65.805, 'highlights': ['The chapter discusses the concept of percentile in exams like CAT and GATE, highlighting the importance of understanding the 0, 25, 50, 75, and 100 percentiles for better performance.', 'The speaker recommends using a vertical look for better representation in the context of pie charts, emphasizing its utility in providing a clear and effective visualization.', 'The chapter introduces the topic of pie charts, emphasizing its relevance to high school and engineering education, offering insight into its application and significance in data representation.']}, {'end': 1441.101, 'start': 1394.24, 'title': 'Pie diagram size calculation', 'summary': 'Discusses the calculation of pie diagram size based on cumulative total, with an example of a total value of 800 and a segment size of 215, representing 20 to 25% importance.', 'duration': 46.861, 'highlights': ['The pie diagram size is calculated based on the cumulative total, with an example of a total value of 800.', 'An example of a segment size of 215 represents 20 to 25% importance in the pie diagram.', 'It is important to give the sizes internally to ensure accurate calculation based on percentage.']}, {'end': 1554.213, 'start': 1441.581, 'title': 'Exploring matplotlib for data visualization', 'summary': 'Discusses the parameters for creating pie charts in matplotlib, such as explode, labels, colors, autopct, and shadow, and emphasizes the importance of using seaborn diagrams for exploratory data analysis.', 'duration': 112.632, 'highlights': ['The chapter explains the parameters for creating pie charts in Matplotlib, including explode, labels, colors, autopct, and shadow.', 'The speaker emphasizes the importance of using seaborn diagrams for exploratory data analysis, highlighting their simplicity and suitability for statistical analysis.', 'The speaker mentions using values like 0.1 or 0.4 for the explode parameter to determine the displacement of slices in the pie chart.', "The speaker mentions assigning different values for labels, such as 'Python', 'C++', 'Ruby', and 'Java', for different segments of the pie chart.", 'The speaker discusses the use of colors and shadows in pie charts, and the choice of formatting for autopct, such as using floating format to display percentages.', 'The speaker concludes the tutorial by mentioning the upcoming seaborn tutorial and expressing gratitude to the audience.']}], 'duration': 225.778, 'thumbnail': 'https://coursnap.oss-ap-southeast-1.aliyuncs.com/video-capture/czQO1_GEEos/pics/czQO1_GEEos1328435.jpg', 'highlights': ['The chapter discusses the concept of percentile in exams like CAT and GATE, highlighting the importance of understanding the 0, 25, 50, 75, and 100 percentiles for better performance.', 'The chapter introduces the topic of pie charts, emphasizing its relevance to high school and engineering education, offering insight into its application and significance in data representation.', 'The speaker recommends using a vertical look for better representation in the context of pie charts, emphasizing its utility in providing a clear and effective visualization.', 'The chapter explains the parameters for creating pie charts in Matplotlib, including explode, labels, colors, autopct, and shadow.', 'The speaker emphasizes the importance of using seaborn diagrams for exploratory data analysis, highlighting their simplicity and suitability for statistical analysis.']}], 'highlights': ['Matplotlib is introduced as a powerful visualization library in Python, emphasizing its use for creating 2D diagrams and its importance in exploratory data analysis for applying statistical analysis.', 'The chapter explains the creation of a scattered plot to display the values of x and y in a 2D graph, offering customization options for color and size.', 'The chapter covers various line styles and formatting options in Matplotlib, providing a comprehensive overview.', 'Using matplotlib to create diagrams, including sine wave diagrams using np.py', 'The chapter discusses the concept of percentile in exams like CAT and GATE, highlighting the importance of understanding the 0, 25, 50, 75, and 100 percentiles for better performance.']}