How Do I Aggregate Recorded Daily Incidents Into Monthly Counts

Question

I have a large pandas dataframe of daily crime incidents. One of my columns (‘date’) is datatype datetime64[ns].

Take, for example, the dataframe below:

ID	Date	Crime
987AL4	1991-08-15	Robbery
987AL4	1991-08-16	Asasult
124576IL	1991-09-21	Breaking and Entering
…	…	…
4689CA	2016-08-17	Sexaul Assault

What I would like to do is create a new dataframe with monthly counts of incidents for each year and each ID.
So, ideally, the resulting dataframe might look something like:

ID	Month	Count
987AL4	1991-08	200,870
124576IL	1991-08	190,000
…	…	…
45678CA	2016-08	60,000

I’ve tried various groupby and count methods, but I’ve had no luck. I would greatly appreciate any help.

Asked By: TheMaffGuy

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Source

Answer 1

You can convert your DatetimeIndex as PeriodIndex and use value_counts:

out = (df.value_counts(['ID', df['Date'].dt.to_period('M').rename('Month')])
         .rename('Count').reset_index())
print(out)

# Output
         ID    Month  Count
0    987AL4  1991-08      2
1  124576IL  1991-09      1
2    4689CA  2016-08      1

Answered By: Corralien

How Do I Aggregate Recorded Daily Incidents Into Monthly Counts

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