For us to be able to work with the data that we found in #3, we also need to ensure the data is in a form that's easily usable by some library functions and able to be visualized in some way. CSVs to the rescue! For most numerical data such as case counts, number of tests taken, number of students in quarantine, etc. a CSV format will be very helpful in setting us up for success to use and manipulate our data.
For the COVID massmail data, it could be a good idea to download a lot of them as .txt files if possible. This way we'll still have a lot of text data and we can calculate word frequencies, rank them, make predictions, etc.
Feel free to just drop the files in the comments here as you download/compile them!
For us to be able to work with the data that we found in #3, we also need to ensure the data is in a form that's easily usable by some library functions and able to be visualized in some way. CSVs to the rescue! For most numerical data such as case counts, number of tests taken, number of students in quarantine, etc. a CSV format will be very helpful in setting us up for success to use and manipulate our data.
For the COVID massmail data, it could be a good idea to download a lot of them as .txt files if possible. This way we'll still have a lot of text data and we can calculate word frequencies, rank them, make predictions, etc.
Feel free to just drop the files in the comments here as you download/compile them!