Data Visualization with Python and Matplotlib Training Course

2k learners

In this course, you will learn how to present data in an explicit manner using the Python as a Data Visualization Tool. This course will help you learn how to arrange critical and meaningful data in a simple yet sophisticated way that is required for decision making.

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12 courses
USD 30

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Course Overview

Data visualization means representing the data in a visual format. Visual formats include graphs, charts, and pictograms. It's of great advantage to learn to deploy data visualization through Python using Matplotlib. Matplotlib is a library of Python that helps in the viewing of the data. You will learn how to deploy various commands for creating multiple graphs, 3D scatter diagrams, and Pie Charts among others. In this course, you will also learn about actual geographical plotting using Matplotlib extension called Basemap.
  • 1-year access to audio-video lectures
  • Course completion certificate

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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