First non-null value per row from a list of Pandas columns

Question

If I\'ve got a DataFrame in pandas which looks something like:

    A   B   C
0   1 NaN   2
1 NaN   3 NaN
2 NaN   4   5
3 NaN NaN NaN

How ca

Answer 1

Here is a one line solution:

[row[row.first_valid_index()] if row.first_valid_index() else None for _, row in df.iterrows()]

Edit:

This solution iterates over rows of df. row.first_valid_index() returns label for first non-NA/null value, which will be used as index to get the first non-null item in each row.

If there is no non-null value in the row, row.first_valid_index() would be None, thus cannot be used as index, so I need a if-else statement.

I packed everything into a list comprehension for brevity.