Sorry in advance if I mess anything up. This is my first issue.
I have hourly data for 3 years using a Pandas datetime as the index. Pandas allows me load/save .csv with the following code (only one month with 2 variables shown):
jan90.to_csv('PEC fine course 1 grid 199001.csv', index=True)
jan90 = pd.read_csv('PEC fine course 1 grid 199001.csv', index_col=0, parse_dates=True)
Using .csv works, but is slow when I get to the full dataset of 26k+ rows and 21.6k+ columns (and more columns may be coming if I have to add lags to my data). So, a more efficient load/save routine is very desirable. I was excited when I found feather, but the lost index is a no-go for my use.
Thanks for your consideration.