CODEWITHSUNDEEP
python-3.xpandas
Brilsmurfffje
Brilsmurfffje

Reputation: 173

Pandas, groupby/Grouper on month ignoring the year

I have the following data in a Pandas df:

index;Aircraft_Registration;issue;Leg_Number;Departure_Time;Departure_Date;Arrival_Time;Arrival_Date;Departure_Airport;Arrival_Airport
0;XXA;0;QQ464;01:07:00;2013-12-01;03:33:00;2013-12-01;JFK;AMS
1;XXA;0;QQQ445;06:08:00;2013-12-01;12:02:00;2013-12-01;AMS;CPT
2;XXA;0;QQQ446;13:04:00;2013-12-01;13:13:00;2013-12-01;JFK;SID
3;XXA;0;QQ446;14:17:00;2013-12-01;20:15:00;2013-12-01;SID;FRA
4;XXA;0;QQ453;02:02:00;2013-12-02;13:09:00;2013-12-02;JFK;BJL
5;XXA;0;QQ150;05:47:00;2018-12-03;12:37:00;2018-03-03;KAO;AMS
6;XXA;0;QQ457;15:09:00;2018-11-03;17:51:00;2018-03-03;AMS;AGP
7;XXA;0;QQ457;08:34:00;2018-12-03;22:47:00;2018-03-03;AGP;JFK
8;XXA;0;QQ458;03:34:00;2018-12-03;23:59:00;2018-03-03;ATL;BJL
9;XXA;0;QQ458;06:26:00;2018-10-04;07:01:00;2018-03-04;BJL;AMS

I want to group this data on the month ignoring the year so ideally would end up with 12 new dataframes each representing the events of that months ignoring the year. I tried the following:

sort = list(df.groupby(pd.Grouper(freq='M', key='Departure_Date')))

This results in a list containing a data frame for each month and year, in this case yielding 60 lists of which many are empty since there is no data for that month.

My expected result is a list containing 12 dataframes, one for each month (January, Februari etc.)

Upvotes: 2

Views: 1105

Answers (1)

jezrael
jezrael

Reputation: 862481

I think need dt.month for 1-12 months or dt.strftime for January-December:

sort = list(df.groupby(df['Departure_Date'].dt.month))

Or:

sort = list(df.groupby(df['Departure_Date'].dt.strftime('%B')))

Upvotes: 3

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