Count occurrences of items in Series in each row of a DataFrame

Question

I have a pandas.DataFrame that looks like this.

COL1    COL2    COL3
C1      None    None
C1      C2      None
C1      C1      None
C1      C2           


        

Answer 1

Usually apply + serise function to whole dataframe will slowing down the whole process , Additional Reading : Link

df.mask(df.eq('None')).stack().str.get_dummies().sum(level=0)
Out[165]: 
   C1  C2  C3
0   1   0   0
1   1   1   0
2   2   0   0
3   1   1   1

---

Or you can do with Counter

from  collections import Counter

pd.DataFrame([ Counter(x) for x in df.values]).drop('None',1)
Out[170]: 
   C1   C2   C3
0   1  NaN  NaN
1   1  1.0  NaN
2   2  NaN  NaN
3   1  1.0  1.0