I have a data frame df which looks like this. Date and Time are 2 multilevel index
observation1 observation2
date Time
2012-11-02 9:15:00 79.373668 224
9:16:00 130.841316 477
2012-11-03 9:15:00 45.312814 835
9:16:00 123.776946 623
9:17:00 153.76646 624
9:18:00 463.276946 626
9:19:00 663.176934 622
9:20:00 763.77333 621
2012-11-04 9:15:00 115.449437 122
9:16:00 123.776946 555
9:17:00 153.76646 344
9:18:00 463.276946 212
I want to have do some complex process over daily data block.
Psuedo code would look like
for count in df(level 0 index) :
new_df = get only chunk for count
complex_process(new_df)
So, first of all, I could not find a way to access only blocks for a date
2012-11-03 9:15:00 45.312814 835
9:16:00 123.776946 623
9:17:00 153.76646 624
9:18:00 463.276946 626
9:19:00 663.176934 622
9:20:00 763.77333 621
and then send it for processing. I am doing this in for loop as I am not sure if there is any way to do it without mentioning exact value of level 0 column. I did some basic search and able to get df.index.get_level_values(0), but it returns me all the values and that causes loop to run multiple times for a day. I want to create a dataframe per day and send it for processing.