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Instructions

Development Environment

You can either work online, via MyBinder, or locally.

MyBinder

Go to: https://mybinder.org/v2/gh/JKU-ICG/va_python_splom_heatmap_parallel_coordinates/main?urlpath=lab Binder and open the template.ipynb notebook.

Local

Checkout this repo and change into the folder:

git clone https://github.com/JKU-ICG/va_python_splom_heatmap_parallel_coordinates
cd va_python_splom_heatmap_parallel_coordinates

Create a new environemnt and install the packages:

conda create --name va_splom_heatmap_parallel_coord
conda activate va_splom_heatmap_parallel_coord
conda install -c conda-forge --yes --file requirements.txt

Hint: For more information on Anaconca and enviroments take a look at the README form our tutorial repository.

Then launch Jupyter Lab :

jupyter lab

Goto http://localhost:8888/ and open the template notebook.

Tasks

Perform the following tasks. Then download the notebook as HTML and submit it. You can use all or a subset of the data for the tasks. Additional data-wrangling may be necessary.

Scatterplot Matrix

  1. Inspect the data and attributes, e.g. with head(), and dtypes.
  2. Select more than two suitable attributes and create a scatterplot matrix.
  3. Create a color-coded scatterplot matrix using the same attributes and an additional categorical attribute, e.g. with altair.
  4. Interpret the results.

Heat map

  1. Inspect the data and attributes, e.g. with head(), and dtypes.
  2. Select suitable attributes and visualise the data in a heatmap, e.g. with seaborn
  3. Interpret the results.

Parallel Coordinates

  1. Inspect the data and attributes, e.g. with head(), and dtypes.
  2. Select suitable attributes and visualise the data in parallel coordinates chart, e.g. with altair.
  3. Interpret the results.