taking the first non null in python

Question

I'm trying to get the first non null value from multiple pandas series in a dataframe.

df = pd.DataFrame({'a':[2, np.nan, np.nan, np.nan],
              'b':[np.nan, 5, np.nan, np.nan],
              'c':[np.nan, 55, 13, 14],
              'd':[np.nan, np.nan, np.nan, 4],
              'e':[12, np.nan, np.nan, 22],
          })

     a    b     c    d     e
0  2.0  NaN   NaN  NaN  12.0
1  NaN  5.0  55.0  NaN   NaN
2  NaN  NaN  13.0  NaN   NaN
3  NaN  NaN  14.0  4.0  22.0

in this df I want to create a new column 'f', and set it equal to 'a' if a is not null, 'b' if b is not null etc. down to e.

I could do a bunch of np.where statements which is inefficient.

df['f'] = np.where(df.a.notnull(), df.a,
              np.where(df.b.notnull(), df.b,
                   etc.))

I looked into doing df.a or df.b or df.c etc.

result should look like:

     a    b     c    d     e   f
0  2.0  NaN   NaN  NaN  12.0   2
1  NaN  5.0  55.0  NaN   NaN   5
2  NaN  NaN  13.0  NaN   NaN  13
3  NaN  NaN  14.0  4.0  22.0  14

Answer 1

One solution

df.groupby(['f']*df.shape[1], axis=1).first()
Out[385]: 
      f
0   2.0
1   5.0
2  13.0
3  14.0

The orther

df.bfill(1)['a']
Out[388]: 
0     2.0
1     5.0
2    13.0
3    14.0
Name: a, dtype: float64