I have the following df:
Timestamp A B C ...
2014-11-09 00:00:00 NaN 1 NaN NaN
Assumed that you have your Timestamp
as index to begin with, you need to do the resample first, and reset_index
before doing a groupby
, here's the working sample:
import pandas as pd
df
A B C ...
Timestamp
2014-11-09 00:00:00 NaN 1 NaN NaN
2014-11-09 00:00:00 2 NaN NaN NaN
2014-11-09 00:00:00 NaN NaN 3 NaN
2014-11-09 08:24:00 NaN NaN 1 NaN
2014-11-09 08:24:00 105 NaN NaN NaN
2014-11-09 09:19:00 NaN NaN 23 NaN
df.resample('1Min', how='max').reset_index().groupby('Timestamp').sum()
A B C ...
Timestamp
2014-11-09 00:00:00 2 1 3 NaN
2014-11-09 00:01:00 NaN NaN NaN NaN
2014-11-09 00:02:00 NaN NaN NaN NaN
2014-11-09 00:03:00 NaN NaN NaN NaN
2014-11-09 00:04:00 NaN NaN NaN NaN
...
2014-11-09 09:17:00 NaN NaN NaN NaN
2014-11-09 09:18:00 NaN NaN NaN NaN
2014-11-09 09:19:00 NaN NaN 23 NaN
Hope this helps.
As said in comment, your 'Timestamp' isn't datetime and probably as string so you cannot resample by DatetimeIndex, just reset_index and convert it something like this:
df = df.reset_index()
df['ts'] = pd.to_datetime(df['Timestamp'])
# 'ts' is now datetime of 'Timestamp', you just need to set it to index
df = df.set_index('ts')
...
Now just run the previous code again but replace 'Timestamp' with 'ts' and you should be OK.