cs-02

Case Study 2: Wealth and Life Expectancy (Gapminder)

Background

Hans Rosling is one of the most popular data scientists on the web. His original TED talk was very popular among my friends when it came out. We are going to create some graphics using his formatted data as our weekly case study. Note that we need to remove Kuwait from the data (discussion on this)

• Back or Course Website

Reading

This reading will help you complete the tasks below.

• o Python for Data Science - Data visualization

Tasks

• Recreate the two graphics shown below using gapminder dataset from gapminder #uv add gapminder library (get them to match as closely as you can)
  • Use the facet_col parameter in your plotly graph function to facet the chart
  • Use pl.with_columns(pl.col("y_axis_columm").sqrt().alias("scaled_column")) to get the correct scale on the y-axis.
  • Group by Continent and Year and aggregate GDP with a weighted average using population as the weight. That will be the black continent average line on the second plot
  • You will need to use the new dataframe to make the black lines and dots showing the continent average on the second plot.
  • Use fig.show(suggested_width=900) and download each output plot as a .png
• Build a marimo notebook that has the following features
  • The title is the same as listed in the task
  • You have two sections – 1) Background, 2) Images
  • In the background section write a few sentences about what you learned making these plots
  • In the Image section have two chunks. One for each image
• Export your notebook to .html and have both the notebook and HTML into your git repository
  • Share the .html file on slack to get feedback

Plots