Pandas DataFrame to drop rows in the groupby

Question

I have a DataFrame with three columns Date , Advertiser and ID. I grouped the data firsts to see if volumns of some Advertisers are too small (For example when count() less than 500). And then I want to drop those rows in the group table.

df.groupby(['Date','Advertiser']).ID.count()

The result likes this:

 Date         Advertiser
 2016-01        A             50000
                B               50
                C              4000
                D             24000
 2016-02        A              6800
                B              7800
                C               123
 2016-03        B              1111
                E              8600
                F               500

I want a result to be this:

 Date         Advertiser
 2016-01        A             50000
                C              4000
                D             24000
 2016-02        A              6800
                B              7800
 2016-03        B              1111
                E              8600

Followed up question:

How about if I want to filter out the rows in groupby in term of the total count() in date category. For example, I want to count() for a date larger than 15000. The table I want likes this:

Date         Advertiser
 2016-01        A             50000
                B               50
                C              4000
                D             24000
 2016-02        A              6800
                B              7800
                C               123

Answer 1

You have a Series object after the groupby , which can be filtered based on value with a chained lambda filter:

df.groupby(['Date','Advertiser']).ID.count()[lambda x: x >= 500]

#Date     Advertiser
#2016-01  A             50000
#         C              4000
#         D             24000
#2016-02  A              6800
#         B              7800
#2016-03  B              1111
#         E              8600
#         F               500