Pandas groupby and filter

I think groupby is not necessary, use boolean indexing only if need all rows where V is 0:

print (df[df.V == 0])    C  ID  V  YEAR0   0   1  0  20113  33   2  0  20135  55   3  0  2014

But if need return all groups where is at least one value of column V equal 0 add any, because filter need True or False for filtering all rows in group:

print(df.groupby(['ID']).filter(lambda x: (x['V'] == 0).any()))     C  ID  V  YEAR0   0   1  0  20111  11   1  1  20122  22   2  1  20123  33   2  0  20134  44   3  1  20135  55   3  0  2014

Better for testing is change column for groupby - row with 2012 is filter out because no V==0:

print(df.groupby(['YEAR']).filter(lambda x: (x['V'] == 0).any()))     C  ID  V  YEAR0   0   1  0  20113  33   2  0  20134  44   3  1  20135  55   3  0  2014

If performance is important use GroupBy.transform with boolean indexing:

print(df[(df['V'] == 0).groupby(df['YEAR']).transform('any')])    ID  YEAR  V   C0   1  2011  0   03   2  2013  0  334   3  2013  1  445   3  2014  0  55

Detail:

print((df['V'] == 0).groupby(df['YEAR']).transform('any')) 0     True1    False2    False3     True4     True5     TrueName: V, dtype: bool