Geoff Boeing has a nice demonstration of Visualizing a GMail Inbox. You can export your email data as an mbox file from Google. Using Python and several packages, you can sort, count, and plot the message dates. I followed his instructions almost exactly and here are my results.
Emails I’ve received have definitely gone up over time. The other interesting thing is that there are two very high traffic days in July 2015. One was because I had a lot of pictures shared with me. The other was because a friend wrote a PowerShell script to send me 100 emails in a row as a prank.
This is a more zoomed in look at the start of 2017 where you can see each day.
Here we can see more clearly how I’ve received more emails in the last year or so. I wanted the axis to be more detailed so I labeled each month. I also had the January label display the year. That was done in Python. I’ve added in the primary sources of emails which explain the rises in emails over the months. That was done with GIMP.
The average for each day was influenced by the time period 2014-2015 when I used Gmail little, so to get a better idea of the average emails I see currently, I plotted the same graph with just 2016 and 2017.
The average about doubled for each day.
My plot for traffic by hour of the day is eerily similar to Geoff Boeing’s in his tutorial. Here’s his.
Here’s mine.
There are spikes at 10 AM and Noon. If you look at it closely, there are small spikes at the beginning of almost every hour. This must be due to automated emails.
