Matplotlib - Complete Python Data Visualization Course

Free download скачать Matplotlib - Complete Python Data Visualization Course

Published 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

What you'll learn
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.

Requirements
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.

Description
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

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