We aggregated school-level data from the California Department of Public Health to create these heat maps. It's interesting to see the changes over time.
I've been working on a project that's utilizing the amazing emotion metrics from Kanjoya. I don't want to say too much about the specific project yet, but I needed to get LexisNexis newspaper files from a text form into a csv file so it could easily be analyzed. LN doesn't allow users to download data this way (why? I don't know!) and no good tools existed to do this-- until now!
My friend Narek wrote python script that converts the text file into a CSV file. Each document from the original file is a row with each column containing some information about the article (Publication, Date, Headline, Body, etc.). Note that Excel has limits on how much text can be in each cell (32,000 characters), so not all of the text body can be included if it's particularly long.
The script requires Python to be installed but can be run directly from the command line if you want. This is especially easy on Macs, since you can just drag and drop the files into Terminal.
Sample usage from Terminal:
$ python lexis_nexis_parser.py lexisnexis.txt