Data Visualization with Python and Matplotlib course is structured in a way to give step-by-step instructions on data visualization techniques and processes. This training will help you learn how to use Python 3, Matplotlib and IDLE for visualizing data in various 2D and 3D formats.
Preview
By the end of Data Visualization with Python and Matplotlib course, you will be able to:
1.Load and organize data from various sources
2.Import data from CSV and NumPy
3.Create and customize live 2D and 3D Python graphs
4.Create geographic maps, live updating graphs, and multiple/combined graphs
5.Familiarize with the various options for visualizing data
In this course, you will learn:
Visualize multiple forms of both 2D and 3D graphs, like line graphs, scatter plots, bar charts, and more
Load data from files or from internet sources for data visualization.
Create live graphs
Customize graphs, modifying colors, lines, fonts, and more
Visualize Geographical data on maps
Course Contents
Day 1
Introduction
Getting matplotlib and setting up
Different types of basic Matplotlib charts
Basic Matplotlib Graph
Labels Titles And Window Buttons
Legends
Bar Chart
Histogram
Scatter Plot
Pie Chart
Loading Data From A Csv
Loading Data With Numpy
Basic Customization Options
Getting Stock Prices For Our Data Set
Parsing Stock Prices From Internet Source
Plotting The Basic Stock Data
Modifying Labels And Adding A Grid
Converting From Unix Time And Adjust Subplots
Customizing Ticks
Fills And Alpha
Add Remove And Customize Spines
Styles With Matplotlib
Live Graphs
Adding And Placing Text
Dynamic Annotation Of Last Price
Advanced Customization Options
Basic sub plots
Label and tick fixes sharing x axis
customizing legends
Basemap
3D Graphing
3d Graph Example Wireframe
3d Scatter
3d Bar Charts
Conclusion
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