/vidl_data_viz

A working group put on by the Vanderbilt Institute for Digital Learning to talk about data visualization

Primary LanguageJupyter Notebook

Vanderbilt Institute for Digital Learning - Data Visualization

Collaborators:

  1. Kate Brady (katherine.a.brady@vanderbilt.edu)
  2. Victor Calderon (victor.calderon@vanderbilt.edu)
  3. Gayathri Narasimham (gayathri.narasimham@vanderbilt.edu)

Description:

A working group put on by the Vanderbilt Institute for Digital Learning to talk about data visualization.

Location:

The workshop meets at Kirkland Hall. For directions: https://goo.gl/maps/W17uyp6MF1t

Topics

  1. Sep - Tableau
  2. Oct - iPython Notebooks
  3. Nov - Seaborn
  4. Jan - Libraries for Non-Numerical Visualization
  5. Feb - R

Live Version

You can execute the iPython Notebooks in this repository by clicking the following button:

Binder

Installing Environment & Dependencies

To use the scripts in this repository, you must have Anaconda installed on the systems that will be running the scripts. This will simplify the process of installing all the dependencies.

If you are unsure if you have Anaconda on your machine run conda -h in your terminal. This should bring up a help message. If you get a command not found error, follow the installation instructions here. After installation, you may still need to add Anaconda to your path variable. If conda -h still doesn't work, see instructions on adding Anaconda to your path in the Anaconda installation instructions.

For reference on Anaconda environments, see: https://conda.io/docs/user-guide/tasks/manage-environments.html

The package counts with a Makefile with useful functions. You must use this Makefile to ensure that you have all the necessary dependencies, as well as the correct conda environment.

  • Show all available functions in the Makefile
$:  make show-help
    
    Available rules:
    
    clean               Delete all compiled Python files
    environment         Set up python interpreter environment - Using environment.yml
    remove_environment  Delete python interpreter environment
    test_environment    Test python environment is setup correctly
    update_environment  Update python interpreter environment
  • Create the environment from the environment.yml file:
    make environment
  • Activate the new environment vidl_viz.
    source activate vidl_viz
  • To update the environment.yml file (when the required packages have changed):
  make update_environment
  • Deactivate the new environment:
    source deactivate

Trouble Shooting

If you get an import error while running one of our notebooks, it may be because jupyter is not set up correctly in the environment.

You can check your jupyter path by running the following command while the environment is activated:

which jupyter

The result should be a path which ends with envs/vidl_viz/bin/jupyter. If you don't see vidl_viz in the path, run:

conda install jupyter

Make sure the path is now correct by running which jupyter again.