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Data Visualization in Python by Examples

Video Description

Data visualization with matplotlib, ggplot, and seaborn in Python

About This Video

  • Use data visualization as your preferred business reporting tool
  • Add impact to your data by representing information in the form of a chart, diagram, pictures, and so on
  • Deploy plots and charts using various data visualization tools in Python

In Detail

Data visualization is just a wise investment in your future big-data needs. You will learn how to deploy maps and networks to display geographic and network data. To do this, we will focus on the following very popular libraries in Python: matplotlib, ggplot, seaborn, and plotly.

In this course, you will walk through some of the fundamentals of data visualization, sharing many examples of how to handle different types of data and how best to present your insights. We'll take a look at chart types, such as Matplotlib for visualizing the impact of tornadoes in the US, North Korean nuke tests on global stocks, and analyze forex performances using charts. You will see how ggplot can be used to analyze trends in BRICS economies and crude oil price trends. You will see how to level up your data visualization skills using Python's advanced plotting libraries: matplotlib and Seaborn, and how you can present the data from the most unstable regions in the world through data visualization.

You will then carry out a visual analysis of the performance of various Hollywood releases. Finally, you will use Plotly to plot comparative graphs of Apple iPhone version releases and compare the performance of gaming consoles such as Xbox and PlayStation.

Table of Contents

  1. Chapter 1 : Programming Data Visualizations Using Python's Matplotlib
    1. The Course Overview 00:04:01
    2. Setting Up and Getting Started with Python Data Visualization 00:03:09
    3. Analyzing Effects of Tornadoes in the US – Most Affected States 00:05:29
    4. Analyzing Effects of Tornadoes in the US – Least Affected States 00:03:22
    5. Plots – Impact of North Korean Atomic Test on Global Stock Markets 00:04:34
    6. Analyzing Forex Performance Using Custom Charts 00:03:33
  2. Chapter 2 : Data Visualization with ggplot Python Library
    1. Setting Up and Getting Started with ggplot 00:02:47
    2. Plotting a Comparison of BRICS Market Economies – GDP Numbers 00:02:41
    3. Plotting a Comparison of BRICS Market Economies – GDP Growth Trends 00:02:14
    4. Crude Prices Representation Through Plots with ggplot 00:02:40
    5. Customizing Representation of Crude Prices with ggplot 00:03:30
  3. Chapter 3 : Programming Advanced Visualizations with Seaborn
    1. Setting Up and Getting Started with Seaborn Python Library 00:02:38
    2. Plotting the Most Unstable Areas in the World Using Seaborn 00:04:52
    3. Plotting the Most Unstable Areas – Advanced Customizations 00:03:13
    4. Visualizing Performance of Recent Hollywood Releases in Seaborn 00:04:19
    5. Visualizing Performance of Hollywood Releases in Seaborn Using Custom Plots 00:04:45
  4. Chapter 4 : Data Visualization Using Plotly
    1. Setting Up and Getting Started with Plotly 00:03:21
    2. Plotting the Data for Apple iPhone Launches with Plotly 00:04:38
    3. Plotting the Data for Apple iPhone Launches – Customizations 00:03:04
    4. Various Plots Showing Performance of Game Consoles Sales 00:05:28
    5. Performance of Game Consoles Sales – Building Online Dashboards 00:03:28