+- Softwarez.Info - Software's World! (https://softwarez.info)
+-- Forum: Library Zone (https://softwarez.info/Forum-Library-Zone)
+--- Forum: Video Tutorials (https://softwarez.info/Forum-Video-Tutorials)
+--- Thread: Matplotlib - Complete Python Data Visualization Course (/Thread-Matplotlib-Complete-Python-Data-Visualization-Course)
Matplotlib - Complete Python Data Visualization Course - BaDshaH - 11-16-2023
![[Image: d687ebeab9ae6f6518700fe1e12c0ac4.jpg]](https://i122.fastpic.org/big/2023/1116/c4/d687ebeab9ae6f6518700fe1e12c0ac4.jpg)
Last updated 11/2023
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 7.07 GB | Duration: 14h 45m
The course has been focused to help the trainees on achieving proficiency in working with MatPlotLib
[b]What you'll learn[/b]
The goal of this training is to help the trainees in learning all the aspects of MatPlotLib which is a python based plotting library
The trainees will be learning how to leverage Tkinter, QT python, etc as GUI to embed plots.
The course has been focused to help the trainees on achieving proficiency in working with MatPlotLib.
This course consists of four units that include one project and three units where you will be learning the concepts through the video tutorial.
[b]Requirements[/b]
There are a few things that you should be supposed to know before you can start learning about MatPlotLib. The very first thing is, you should know python fundamental. As MatPlotLib is a python library, you are supposed to know how does python works so that you can bring this library in use while developing a program in python. If you are already working as a python developer, you might find it very easy to learn python while if you are a beginner, you will need to give some time practicing it so that you can understand everything perfectly.
[b]Description[/b]
Which tangible skills you will learn in the course?These MatPlotLib Tutorials has been carefully developed to meet the requirement of the beginners as well as the professionals. We have tried to cover this topic from almost every angle. You make take some time to learn everything about MatPlotLib, but once you completed the course, you will be having a bundle of ideas about how it can be used and where it can be used. You will become the python developer who will know how to have the data presented graphically in an application. You will be ample comfortable to work with the python and its modules that are used to integrate this library to create an efficient application.There are various simple, intermediate, and complex examples added in this course to get you real work exposure so that you can immediately be job-ready right after finishing these MatPlotLib Tutorials. Not just this library, but you will also be learning how to use python in several ways as we have shown various ways to solve one example. You will be expected to do the things on your own together with the educator so that you can achieve proficiency. You will learn a lot of new topics that you might never hear before.The main purpose of this course is to get you a lucrative career where you can grow professionally and financially. Learning this course you give you an extra edge as the developers these days barely find themselves good with working on something that is even a bit complicated. You will be able to crack the interviews where the selection is based on the working experience or knowledge of the MatPlotLib library. We will make you all set for your next important step towards your goal if you want to become a proficient python developerXbox also performance on DirectX based games which provides the best user experience while using. There flexible to use on Systems, Laptops, Mobiles, and other devices so the scope of learning is high and demanding in the market. Handling codes and documents can be done and are easy to access to figure out the problems while working.
Overview
Section 1: Matplotlib for Python Data Visualization - Beginners
Lecture 1 Introduction to Matplolip
Lecture 2 Simple Graphs
Lecture 3 Simple Graphs Continue
Lecture 4 More on Line Graphs
Lecture 5 Bar Graph
Lecture 6 Scatter Graph
Lecture 7 Using Text
Lecture 8 Annotation in Graph
Lecture 9 Basic of Pyplot
Lecture 10 Basic of Pyplot Text
Lecture 11 Basic Bar and Fill
Lecture 12 Complex Fill Demo
Lecture 13 Custom Dashed Lines and Bar Charts
Lecture 14 Inch and cms and Color Bars
Lecture 15 Demo Image
Lecture 16 Pcolormesh and Pathpatch Demo
Lecture 17 Creating Streamplot
Lecture 18 Creating Streamplot Continue
Lecture 19 Eillpise Demo
Lecture 20 Eillpise Demo Continue
Lecture 21 Pie Chart
Lecture 22 Table Demo
Lecture 23 Log Demo and Polar Demo
Lecture 24 Customizing Image
Lecture 25 Customizing Image Continue
Lecture 26 Customizing Plot
Lecture 27 Customizing Styles
Section 2: Matplotlib for Python Data Visualization - Intermediate
Lecture 28 Introduction to Matplotlib Intermediate
Lecture 29 Simple Working with Legend
Lecture 30 Simple Working with Legends Continue
Lecture 31 More on Legends Part 1
Lecture 32 More on Legends Part 2
Lecture 33 Basic Customizing Figure Layout
Lecture 34 Advance Customizing Figure Layout
Lecture 35 More on Customizing Figure Layout
Lecture 36 More Examples
Lecture 37 Complex Nested Grid spec
Lecture 38 Constrained Layout Guide
Lecture 39 Constrained Layout Guide Continue
Lecture 40 Padding
Lecture 41 Spacing
Lecture 42 Use with Grid Spec
Lecture 43 More on Grid spec
Lecture 44 Examples on Grid Spec
Lecture 45 Examples on Grid Spec Continue
Lecture 46 Tight Layout Guide Basic
Lecture 47 Tight Layout Guide Advance
Section 3: Matplotlib for Python Data Visualization - Advanced
Lecture 48 Introduction to Matplotlib Advance Level
Lecture 49 Path Tutorial
Lecture 50 More on Path Tutorial
Lecture 51 Path Effect Guide
Lecture 52 Transformation Level 1
Lecture 53 Transformation Level 1 and Example
Lecture 54 Transformation Level 2 and Example
Lecture 55 Colors Tutorial
Lecture 56 Customized Colorbars
Lecture 57 Creating Colormaps Basic
Lecture 58 Creating Colormaps Advance
Lecture 59 Logarithmic and Symmetric Logarithmic
Lecture 60 Power-Law and Discrete bounds
Lecture 61 Two Linear Ranges
Lecture 62 Choosing Colormaps Overview
Lecture 63 Classes of Colormaps
Lecture 64 Lightness of Matplotlib Colormaps
Lecture 65 Lightness of Matplotlib Colormaps Continue
Lecture 66 Basic Text Command
Lecture 67 Legends and Annotations
Lecture 68 Text Properties
Lecture 69 Layouts
Lecture 70 Basic Annotation
Lecture 71 Annotation Polar
Lecture 72 Fancy Demo
Lecture 73 Connectionstyle Demo
Lecture 74 Using Connection Patch
Lecture 75 Zoom Effect Between Axes
Lecture 76 Simple Example
Lecture 77 Simple Example Continue
Lecture 78 Saving Multipage PDF Files
Lecture 79 Modifying Parameters
Lecture 80 Text Rendering with LaTex
Lecture 81 Simple Axes Grid
Lecture 82 Parasite Axes
Lecture 83 Anchored Artists
Lecture 84 RGB Axes
Lecture 85 Simple Axes Artist
Lecture 86 Axes Artist with Parasite Axes
Lecture 87 Floating Axis Demo Part 1
Lecture 88 Floating Axis Demo Part 2
Lecture 89 Axes Artist Demo
Lecture 90 Line 3D
Lecture 91 Bar 3D
Section 4: Matplotlib Case Study - E-commerce Data Analysis
Lecture 92 Introduction to Project
Lecture 93 Installation of Software's
Lecture 94 Installation of Anaconda and Code
Lecture 95 Inline Function
Lecture 96 Unique Value
Lecture 97 Prices Condition
Lecture 98 Understanding Basics of Graph
Lecture 99 Data Visualization
Lecture 100 Plotting of Line Graph
Lecture 101 Plotting of Histogram
Lecture 102 Plotting of Histogram Continue
Lecture 103 Plotting of Bar Graph
Lecture 104 Plotting of Scatter Plot
Lecture 105 Plotting of Pie Graph
Lecture 106 Plotting of Pie Graph Continue
Lecture 107 Plotting of Boxplot
The best target audience for this course is the python developers and the students who are working in the programming language. The professionals who are already working in python can opt for this course to learn something very important when it comes to developing an enterprise-level application. They will add the extra skill and will end up with enhancing their proficiency after the completion of this tutorial. They can make themselves ready for any opportunity that comes across their way in the domain of python development. Also, they can have themselves considered as a valuable developer who has an edge of knowing how to get the graphical presentation functionality in the application.
Homepage