How to merge two DataFrame columns and apply pandas.to_datetime to it?
You can do everythin in the read_csv function:
pd.read_csv('test.csv', parse_dates={'timestamp': ['date','time']}, index_col='timestamp', usecols=['date', 'time', 'o', 'c'])parse_dates tells the read_csv function to combine the date and time column into one timestamp column and parse it as a timestamp. (pandas is smart enough to know how to parse a date in various formats)
index_col sets the timestamp column to be the index.
usecols tells the read_csv function to select only the subset of the columns.
As far as loading the data in, I think you've got it. To set the index do this:
st_new = pd.concat([(st.o + st.c) / 2, st.vol], axis=1, ignore_index=True)st_new.set_index(pd.to_datetime(st.date + " " + st.time), drop=True, inplace=True)Here's the API documentation for set_index.