Pandas - FillNa with another column

Question

How do I fill the missing value in one column with the value of another column?

I read that looping through each row would be very bad practice and that it would be better to do everything in one go but I could not find out how to do it with the fillna method.

Data Before

Day  Cat1  Cat2
1    cat   mouse
2    dog   elephant
3    cat   giraf
4    NaN   ant

Data After

Day  Cat1  Cat2
1    cat   mouse
2    dog   elephant
3    cat   giraf
4    ant   ant

How do I resolve this?

Answer 1

You can provide this column to fillna, it will use those values on matching indexes to fill:

In [17]: df['Cat1'].fillna(df['Cat2'])
Out[17]:
0    cat
1    dog
2    cat
3    ant
Name: Cat1, dtype: object

Answer 2

Assuming three columns of your data frame is a, b and c. This is what you want:

df['c'] = df.apply(
    lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
    axis=1
)

Full code:

df = pd.DataFrame(
    np.array([[1, 2, 3], [4, 5, np.nan], [7, 8, 9], [3, 2, np.nan], [5, 6, np.nan]]), 
    columns=['a', 'b', 'c']
)
df['c'] = df.apply(
    lambda row: row['a']*row['b'] if np.isnan(row['c']) else row['c'],
    axis=1
)

Answer 3

You could do

df.Cat1 = np.where(df.Cat1.isnull(), df.Cat2, df.Cat1)