pandas - how to filter "most frequent" Datetime objects

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I'm working with a DataFrame like the following:

User_ID    Datetime
01    2014-01-01 08:00:00
01    2014-01-02 09:00:00
02    2014-01-02 10:00:00
02    2014-01-03 11:00:00
03    2014-01-04 12:00:00
04    2014-01-04 13:00:00
05    2014-01-02 14:00:00

I would like to filter Users under certain conditions based on the Datetime columns, e.g. filter only Users with one occurrence / month, or only Users with occurrences only in summer etc.

So far I've group the df with:

g = df.groupby(['User_ID','Datetime']).size()

obtaining the "traces" in time of each User:

User_ID    Datetime
01    2014-01-01 08:00:00
      2014-01-02 09:00:00
02    2014-01-02 10:00:00
      2014-01-03 11:00:00
03    2014-01-04 12:00:00
04    2014-01-04 13:00:00
05    2014-01-02 14:00:00

Then I applied a mask to filter, for instance, the Users with more than one trace:

mask = df.groupby('User_ID')['Datetime'].apply(lambda g: len(g)>1)
df = df[df['User_ID'].isin(mask[mask].index)]

So this is fine. I'm looking for a function instead of the lambda g: len(g)>1 able to filter Users under different conditions, as I said before. In particular filter Users with with one occurrence / month.

asked 1 min ago

fblamanna

74

pandas - how to filter "most frequent" Datetime objects