Data Visualization with Python and Matplotlib

Big data has a wide range of benefits. Yet, many individuals lack the skill to interpret big data in its original structure. To understand it ideally, data visualization is used. This creates visual representations of data like charts, graphs, etc which makes it simple to read and easy to understand

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Course Overview

In this course, you will be guided through the setup of Matplotlib- A plotting library for Python programming language. You will learn various types of visual representations like pie charts, histograms, scatter plots and many more. This course has been specifically outlined for individuals are interested in learning the various ways of displaying data visually. At the end of this course, you will be able to create live graphs and visualize geographical data on maps.

Course Outline


This course helps you visualize varied forms of 2D and 3D graphs, like bar charts, line graphs, scatter plots, etc. You will also learn how to customize those graphs such as modifying lines, colors, etc.


This course is aligned to help you learn various ways to visually present python data


On finishing this course, you will gain a complete understanding of the options available for visualizing data and know how to create well presented, visually appealing graphs.

Getting Matplotlib And Setting Up
Section Introduction
Basic matplotlib graph
Labels, titles and window buttons
Bar Charts
Scatter Plots
Stack Plots
Pie Chart
Loading data from a CSV
Loading data with NumPy
Section Conclusion
Section Introduction
Source for our Data*
Parsing stock prices from the internet*
Plotting basic stock data*
Modifying labels and adding a grid*
Converting from unix time and adjusting subplots*
Customizing ticks*
Fills and Alpha*
Add, remove, and customize spines*
Candlestick OHLC charts*
Styles with Matplotlib*
Creating our own Style*
Live Graphs*
Adding and placing text*
Annotating a specific plot*
Dynamic annotation of last price*
Section Conclusion
Section Introduction
Basic suplot additions*
Subplot2grid *
Incorporating changes to candlestick graph*
Creating moving averages with our data*
Adding a High minus Low indicator to graph*
Customizing the dates that show*
Label and Tick customizations*
Share X axis*
Multi Y axis*
Customizing Legends*
Section Conclusion
Section Introduction
Downloading and installing Basemap
Basic basemap example
Customizing the projection
More customization, like colors, fills, and forms of boundaries
Plotting Coordinates*
Connecting Coordinates*
Section Conclusion
Section Introduction
Basic 3D graph example using wire_frame
3D scatter plots
3D Bar Charts
More advanced Wireframe example
Section Conclusion


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