Here's an example:
A
0 V1
1 V1
2 V2
3 v4
4 v4
5 v7
And I would want to end up with something like this:
A
0 V1
1 V1
2 np.NaN
3 v4
4 v4
5 np.NaN
Basically it would be something like this:
df.A[df.A.value_counts() < 2] = np.NaN
Use groupby + transform, and then index with loc -
df.loc[df.groupby('A').A.transform('count').lt(2), 'A'] = np.nan
df
A
0 V1
1 V1
2 NaN
3 v4
4 v4
5 NaN
Use value_counts and then check values of index byisin :
a = df.A.value_counts()
m = df.A.isin(a.index[a<2])
print (m)
0 False
1 False
2 True
3 False
4 False
5 True
Name: A, dtype: bool
df.loc[m, 'A'] = np.NaN
print (df)
A
0 V1
1 V1
2 NaN
3 v4
4 v4
5 NaN
