The goal of the project was to analyze all of the data my partner and I have collected over roughly the past year and a half on when and where we’ve parked our car on the street. We have been tracking this information via a mobile app that we created called Car Here Now. In the future, we are hoping to be able to work with this data in realtime, but for the purposes of this project I downloaded a raw JSON dataset to work with that contained all of our parking entries to date.

In order to traverse the data, I began by writing a program in Python to parse the raw dataset and make it easier to work with. I split up multiple pieces of information that were contained in a single string, and filled in some gaps in the data from a glitch in a previous version of the app. I then utilized a few Python modules to augment the raw data—determining the day of the week for each entry and using the geographic coordinates to  get more location information for each parking entry. Finally, I wrote this out out to a new JSON file.

With a clean new JSON dataset to work with, I wrote a second program in Python to explore our parking habits by day of the week and sorted all of the entries into 7 lists based on the days of the week. Since we moved somewhat recently I also wanted to just look at parking habits in my current neighborhood; I weeded out all entries that weren’t in my current neighborhood and sorted those results into 7 more lists based on days of the week. I exported all 14 of these lists as separate CSV files to import into Google My Maps as well as into Airtable in order to make visualizations.

I was also interested in seeing our parking habits from before the COVID-19 pandemic and how those compared to our current parking habits, so I wrote a third program in Python. I separated all of our parking entries by pre- and post-COVID. I used the datetime Python module to then figure out the oldest entry in our dataset and then calculate the total number of days we used Car Here Now to track our parking both pre-COVID and post-COVID. I was them able to use simple operations to determine the average number of times we parked per week pre-COVID and post-COVID as well as our percentage decrease in parking since the start of the pandemic.