Get first non-null value per row

Question

I have a sample dataframe show as below. For each line, I want to check the c1 first, if it is not null, then check c2. By this way, find the first notnull column and store

Answer 1

Setup

df = df.set_index('ID') # if necessary
df
     c1   c2  c3   c4
ID                   
1     a    b   a  NaN
2   NaN   cc  dd   cc
3   NaN   ee  ff   ee
4   NaN  NaN  gg   gg

Solution
stack + groupby + first
stack implicitly drops NaNs, so groupby.first is guarantee to give you the first non-null value if it exists. Assigning the result back will expose any NaNs at missing indices which you can fillna with a subsequent call.

df['result'] = df.stack().groupby(level=0).first()
# df['result'] = df['result'].fillna('unknown') # if necessary 
df
     c1   c2  c3   c4 result
ID                          
1     a    b   a  NaN      a
2   NaN   cc  dd   cc     cc
3   NaN   ee  ff   ee     ee
4   NaN  NaN  gg   gg     gg

(beware, this is slow for larger dataframes, for performance you may use @jezrael's solution)