1. Extract data from https://www.gapminder.org/data/ to construct a d-dimensional (d � 5) dataset. In this dataset, countries or regions are individual data points. Each data point will have d number of attributes which come from https://www.gapminder.org/data/. You need to clean the dataset to ensure consistencies. For example, all attributes should come from roughly the same time period, and missing data should be avoided or lled. The selection of attributes to download should be based on some interesting ideas or hypothesis that you are trying to demonstrate or con rm.
2. Use D3 to visualize your d-dimensional dataset with 3 di�erent multi-dimensional data visualization techniques that D3 provides: Scatterplot Matrix, Parallel Coordinate, and Streamgraph. You will need to provide some interactive functions in each of these visualizations, and they should reveal di�erent aspects of the data to demonstrate your hypothesis or insight.
3. Write a description about what insight you gain from these visualizations: discovery, revelation, surprises, etc.

• Data is stored in here
• Data is cleaned by Python script (can be found in here) and cleaned data is stored in here.
• Visualization Code can be found in here.

conda env remove -n Offline1 -y
#conda env create -f environment.yml
conda env update --file environment.yml
activate Offline1
#deactivate

And then activate the Offline1 environment for the code.

Report can be found in here.