Python Pandas : Convert multiple rows into single row, ignoring NaN's

Question

I have a DataFrame similar to the one mentioned below,

 Age    Sex    Name ....
 12     NaN    NaN
 NaN    Male   NaN
 NaN    NaN    David

I want to convert it into a dataframe with one row, ignoring the NaN's and merging them

 Age    Sex    Name
 12     Male   David

How to do this is Pandas?

Answer 1

You can use pd.concat to combine all columns after .dropna() and .reset_index() like so:

pd.concat([df[col].dropna().reset_index(drop=True) for col in df], axis=1)

to get:

    Age   Sex   Name
0  12.0  Male  David

Answer 2

Another method is to apply a lambda that calls first_valid_index to return the first valid row value:

In [246]:
df.apply(lambda x: pd.Series(x[x.first_valid_index()]))

Out[246]:
    Age   Sex   Name
0  12.0  Male  David