Python – Pandas filter and group by

I need most similar column file, I have data:

Input:

I need cluster-1 to be equal to cluster-2 in the maximum count, a file that will not be specified not to be included in the cluster

Output:

>Solution :

Compare first Series.mode per groups by original column, filter and if necessary add not filtered rows with assign bin to cluster-2:

print (df)
  file  cluster-1  cluster-2
0    A          1          2
1    D          1          2
2    G          2          4
3    B          3          1
4    E          3          2
5    J          3          1

m = (df.groupby('cluster-1')['cluster-2']
      .transform(lambda x: x.mode().iat[0])
      .eq(df['cluster-2']))
df = (df[m].append(df[~m].assign(**{'cluster-1':'bin'}), ignore_index=True)
          .rename(columns={'cluster-1':'cluster'})
          .drop('cluster-2', axis=1))
print (df)
  file cluster
0    A       1
1    D       1
2    G       2
3    B       3
4    J       3
5    E     bin