How to specify date format when using pandas.to_csv?
Since version v0.13.0 (January 3, 2014) of Pandas you can use the date_format parameter of the to_csv method:
df.to_csv(filename, date_format='%Y%m%d')
You could use strftime to save these as separate columns:
df['date'] = df['datetime'].apply(lambda x: x.strftime('%d%m%Y'))df['time'] = df['datetime'].apply(lambda x: x.strftime('%H%M%S'))and then be specific about which columns to export to csv:
df[['date', 'time', ... ]].to_csv('df.csv')
To export as a timestamp, do this:
df.to_csv(filename, date_format='%s')The %s format is not documented in python/pandas but works in this case.
I found the %s from the dates formats of ruby. Strftime doc for C here
Note that the timestamp miliseconds format %Q does not work with pandas (you'll have a litteral %Q in the field instead of the date). I caried my sets with python 3.6 and pandas 0.24.1