This project mainly served as an intro into machine learning basics. The goal was to model an existing project with data I sourced myself and then catering it to my needs. The data I used was weather data from boston over the last 10 years, with the meteostat API I was able to gather data for Boston. The historical weather data went back all the way to the early 1900s but I found that going abck that far left a lot of holes which would be tricky once I trimmed my data.
After getting my data into a csv format I then looked at some basic statistics using basic mean, median, and other basic statistical functions to see how many data was layed out. As well as finding out how many empty portions of data there where in the dataframe, including common ones such as windspeed.