Script Release ::: Climate Parser

Climate Parser is a Python script which allows one to run quick analyses on US-city-specific climate data.

LINK: Climate Parser (it's also linked from my gitHub page)

What this script does
As said in the opening statement, it intakes CSV-based climate records for individual US cities. It then prepares the data in a way that can either be utilized by core-functions of the script or even on-the-fly. For a robust look at the capabilities, reference the readme.md on the repository page.

There are 4 temporal periods supported as of the initial release (v1.4): day, week, month, and year.

For each of the temporal periods, one can run Stats, which returns specific statistics to the time desired. Reports can be ran to get a climatological perspective on the data, including the enabling of climatological tendency: how averages change over time. I like this type of analysis as it allows you to compare previous climate-eras to newer ones. Ranks can be returned to see the individual records, based on the time-period of interest. With the week function, stats are based on a (typically) 7-day period with the searched day being the center of the week.

About
I started working on this program in late September 2019, I believe. In the past I'd tried to work with city-data in spreadsheet format, but felt it to be cumbersome. It also didn't help that my computer is/was slow. Recently, I realized that spreadsheet formats are perfect for utilizing objects in programming. Initially, I started this just to see how easy it was to intake the data. As I kept thinking of features I wanted to include, it morphed from being object-driven to a dictionary-driven format. It also gave me experience that helped broaden my Python skills. Enjoy!