Combining columns of dataframe [duplicate]

Answer 1

You could try this:

import pandas as pd
import numpy as np
a = pd.DataFrame({
    'c1': ['a',np.NaN,np.NaN,np.NaN,'a'],
    'c2': [np.NaN,'b',np.NaN,'b',np.NaN],
    'c3': [np.NaN,np.NaN,'c',np.NaN,np.NaN]
})

newdf=pd.DataFrame({'c4':a.fillna('').values.sum(axis=1)})

Output:

newdf

  c4
0  a
1  b
2  c
3  b
4  a

I just see this option retrieved from jpp's answer, where jpp take advantage of the fact that np.nan != np.nan and uses a list comprehension, maybe it could be the fastest way:

newdf=pd.DataFrame({'c4':[i  for row in a.values for i in row if i == i]})
print(newdf)