Applications Analysis

Perform quantitative analysis on raw data from job applications in preparation for qualitative write-up and evaluation. Designed to run through Jupyter/IPython and output SVG files, as well as some Markdown. Written mostly in Python 3, tested in Python 3.5.2 through Jupyter 4.1.1.

Notebooks are run consecutively, as follows:

  1. JSON.ipynb (transforms .txt-files into JSON)
  2. SQLite.ipynb (transforms JSON into SQLite database)
  3. Display.ipynb (creates plots)
  4. MarkdownTable.ipynb (creates Markdown table of data)



Added docs.


Cleaned raw data and repository.


Simplified structure and measurements, replaced GGPlot with Seaborn/Matplotlib.


Dropped LinesPerDay.ipynb Python/Plotly plot in favor of R's GGPlot. Added Descriptives.ipynb, Textstats.ipynb, MarkdownTable.ipynb, and ReadingTime.ipynb which use RPy2 to bridge Python and R, and creates the Descriptives, Texstats, Consensus, and ReadingTime plots.