https://github.com/PacktPublishing/Data-visualization-projects-in-python

Data visualization projects in python [video], published by Packt
https://github.com/PacktPublishing/Data-visualization-projects-in-python

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Data visualization projects in python [video], published by Packt

• Host: GitHub
• URL: https://github.com/PacktPublishing/Data-visualization-projects-in-python
• Owner: PacktPublishing
• License: mit
• Created: 2018-03-15T12:10:50.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2021-01-14T16:00:09.000Z (almost 4 years ago)
• Last Synced: 2024-08-01T12:36:14.358Z (3 months ago)
• Language: Jupyter Notebook
• Size: 1.45 MB
• Stars: 17
• Watchers: 7
• Forks: 18
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Data-visualization-projects-in-python

Data visualization projects in python [video], published by Packt

# Data Visualization in Python by Examples [Video]

This is the code repository for [Data Visualization in Python by Examples [Video]](https://www.packtpub.com/virtualization-and-cloud/data-visualization-python-examples-video?utm_source=github&utm_medium=repository&utm_campaign=9781788838658), published by [Packt](https://www.packtpub.com/?utm_source=github). It contains all the supporting project files necessary to work through the video course from start to finish.

## About the Video Course

Some popular Python data visualization tools and techniques today include Data Visualization in Jupyter Notebook with Bloomberg's bqplot library, Programming Graph and Network Data Visualizations, Data Visualizations with Bokeh (a Python library), and building interactive web visualizations using Dash.

You will start by programming stunning interactive Data Visualizations using bqplot, an open source Python library developed by Bloomberg. Then you will learn how to programmatically create interactive network graphs and visualizations. You will then programmatically visualize data with the interactive Python visualization library, Bokeh.

Finally, you will build interactive web visualizations of data using Python: you will choose a number of inputs your users can control, then use any Python graphing library to create plots based on those inputs.

What You Will Learn





* Set up different data visualization tools in Python such as bqplot, NetworkX, Bokeh, and Dash 

* Plot data in Jupyter Notebook using bqplot 

* Use bqplot to compare different US Presidential election trends 

* Analyze the trends in previous and current FIFA rankings 

* Use the NetworkX library to plot the LAN networks in your office space and organization 

* Visualize a social network with NetworkX 

* Plot weather forecasts using Bokeh, for the weather in US and UK 

* See the frequency of Moon missions undertaken by NASA over the years 

* Turn dash plots into interactive visualizations for major Android version releases and Walmart's growth 





## Instructions and Navigation

### Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:


Be familiar with the Python programming language

Find your way around command line

### Technical Requirements

This course has the following software requirements:


Have access to a Windows, Mac or Linux Computer

Have Python 3.x installed

## Related Products

* [Data Visualization Solutions for Beginners [Video]](https://www.packtpub.com/big-data-and-business-intelligence/data-visualization-solutions-beginners-video?utm_source=github&utm_medium=repository&utm_campaign=9781788395786)

* [Advanced Data Visualization Solutions [Video]](https://www.packtpub.com/big-data-and-business-intelligence/advanced-data-visualization-solutions-video?utm_source=github&utm_medium=repository&utm_campaign=9781788838269)

* [Data Visualization with Tableau [Video]](https://www.packtpub.com/big-data-and-business-intelligence/data-visualization-tableau-video?utm_source=github&utm_medium=repository&utm_campaign=9781788837330)