Python notebooks to analyze data from the PICAPS project (CIAI-Onlus)

Includes notebooks for: cleaning data, visualizing data, classifying data with a decision tree classifier

The procedure to perform the full analysis is as follows:

1. In order not to have errors, create in your local directory two directories named: output_files/ and output_figures/; all files and figures produced during the run of the code are stored in these two directories.
2. Run the clean_data.ipynb (this uses data_small.csv as input file). This will produce in the same directory an output file at the end, data_clean.csv, which is a clean, transformed and integrated version of the original dataset.
3. Run the visualize_data.ipynb (this uses data_clean.csv as input file).
4. Run the classify_predict_data.ipynb (this uses data_clean.csv as input file).

Run notebooks using Jupyter.

For info write to dev@gnucoop.com