Data Visualization Projects in Python

Data Visualization Projects in Python

English | MP4 | AVC 1920×1080 | AAC 48KHz 2ch | 1h 06m | 182 MB

Data Visualization with bqplot, NetworkX, and Bokeh in Python

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.

This friendly course takes you through data visualization in Python using bqplot, NetworkX, Bokeh, and Dash. It is packed with step-by-step instructions and working examples. This comprehensive course is divided into clear bite-size chunks so you can learn at your own pace and focus on the areas of most interest to you.

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
Table of Contents

Programming Data Visualization with Bloomberg’s ‘bqplot’ Library
1 The Course Overview
2 Getting Started with Plotting with bqplot in Jupyter Notebook
3 Plots Comparing Different US Presidential Elections – Period 1
4 Plots Comparing Different US Presidential Elections – Period 2
5 Customize Plots to Show Wealth of Nations – Period 1
6 Customize Plots to Show Wealth of Nations – Period 2

Programming Graph and Network Data Visualization
7 Setting Up and Getting Started with NetworkX
8 Creating a Network Graph Showing a LAN Network for the Office Environment
9 Creating a Network Graph Showing a LAN Network for an Organizational Environment
10 Visualizing a Social Network with NetworkX (Trends in the Beginning of Social Media)
11 Visualizing a Social Network with NetworkX (Current Trends)

Data Visualizations with Bokeh Python Library
12 Getting Started with Bokeh Python Library
13 Plotting Weather Data with Bokeh – Forecasts for the USA
14 Plotting Weather Data with Bokeh – Forecasts for the UK
15 Plotting Various Kinds of Plot with Bokeh – Manned Missions
16 Plotting Various Kinds of Plot with Bokeh – Unmanned Missions

Build Interactive Web Visualizations Using Dash
17 Getting Started with Dash
18 Turning Dash Plots into Interactive Visualizations for Android Releases – Early Versions
19 Turning Dash Plots into Interactive Visualizations for Android Releases – Recent Versions
20 Customizing Visualizations for Walmart Growth with Dash (Geographical Area ‘A’)
21 Customizing Visualizations for Walmart Growth with Dash (Geographical Area ‘B’)