It took about 13 months to obtain all the data Often the data was incomplete, forcing us to get creative. To get past this hurdle, we asked for every application Anaheim approved for its pay-to-stay program, identifying 243 participants. To combine that into one complete record, we used Python via a jupyter notebook to aggregate and group each data set. First, we used the data analysis tool OpenRefine to cluster convictions that were very similar into smaller subsets. Categorization Once we did that, we had a data set containing almost 200 separate types of convictions.

Source: Los Angeles Times March 09, 2017 10:52 UTC