Python Pandas: Create new column out of other columns where value is not null

numpy, pandas, python

Solution

In the case of multiple columns, you can use forward fill. This example assumes that you want to build a combination of all columns 'A' through 'Z':

df['AZ'] = df.loc[:,'A':'Z'].fillna(method='ffill',axis=1)['Z']

This method works for two columns, too:

df['C'] = df.loc[:,'A':'B'].fillna(method='ffill',axis=1)['B']
#0    x
#1    y
#2    z
#3    a
#4    b

Problem

I have a data frame like this ``` ---------------- RecID| A |B ---------------- 1 |NaN | x 2 |y | NaN 3 |z | NaN 4 |NaN | a 5 |NaN | b ``` And I want to create a new column, C, from A and B such that if A is null then fill with B and if B is null then fill with A: ``` ---------------------- RecID|A |B |C ---------------------- 1 |NaN | x |x 2 |y | NaN |y 3 |z | NaN |z 4 |NaN | a |a 5 |NaN | b |b ``` Lastly, is there an efficient way to do this if I have more than two columns, e.g. I have columns A-Z and want create a new column A1 out of columns A-Z similar to above?

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