python - gropuby and remove specified groups in pandas DataFrame -

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i have pandas dataframe:

df=pd.dataframe({'a':[1,1,2,2,3,3],'b':['c','t','k','c','c','k']})

i need group df , remove groups b ='t'. pandas groupby syntax this? in example answer groups 2 , 3.

a groupby/filter work here (filter return groups meet condition). so, example, following:

>>> df.groupby('a').filter(lambda x: (x['b'] != 't').all())      b 2  2  k 3  2  c 4  3  c 5  3  k

(x['b'] != 't').all() allows keep group if there no rows 't' in column b

or write filter following way: create booleen series based on whether row of column b 't'. if sum booleen series, sum greater 0 if of elements 't':

>>> df.groupby('a').filter(lambda x: (x['b'] == 't').sum() == 0)      b 2  2  k 3  2  c 4  3  c 5  3  k

there other ways write filter condition have same flavor.


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