fetch row where column is equal to a value pandas
df.loc[df['column_name'] == 'value']
fetch row where column is equal to a value pandas
df.loc[df['column_name'] == 'value']
count nans after groupby pandas
A B C
0 foo one NaN
1 bar one bla2
2 foo two NaN
3 bar three bla3
4 foo two NaN
5 bar two NaN
6 foo one NaN
df2 = df.C.isnull().groupby([df['A'],df['B']]).sum().astype(int).reset_index(name='count')
print (df2)
A B count
0 bar one 0
1 bar three 0
2 bar two 1
3 foo one 2
4 foo three 1
5 foo two 2
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