Analyzing your email inbox with Python and Jupyter

I am learning Jupyter, Python and Julia as alternatives to my usual Matlab and Mathematica workflows for protyping scientific ideas and projects. In this blog post I use them as a tool to analyze the inflow of email at the office, with the hope that it will help me decide how to manage (and reduce) attention span to emails.

The notebook produces a plot like the one below, which shows the percentage of emails that arrive at certain hours of the day. In my case the distribution is rather uniform from 10am to 6pm, so probably my best strategy would be to concentrate attention around 9am to prepare for the day.

email stats plot.png

To use this notebook in Windows or Mac:

  1. Download Anaconda from Focus on the latest Python 3 version.
  2. Install Jupyter using conda install jupyter from a terminal.
  3. Download the notebook to some folder.
  4. Open a terminal, change directory to that folder and type jupyter notebook 'Email analysis.ipynb' to open the notebook in a browser.
  5. The notebook can be evaluated much like a Mathematica file.