How to iterate over an array using a lambda function with pandas apply

Question

I have the following dataset:

     0    1     2   
0   2.0  2.0    4   
0   1.0  1.0    2   
0   1.0  1.0    3   
3   1.0  1.0    5   
4   1.0  1.0    2   
5   1.0  NaN    1   
6   NaN  1.0    1

and what I want to do is insert a new column that iterates over each row, and if there is a NaN then give it a 0, if not then copy the value from column '2' to get this:

     0    1     2   3
0   2.0  2.0    4   4
0   1.0  1.0    2   2
0   1.0  1.0    3   3
3   1.0  1.0    5   5
4   1.0  1.0    2   2
5   1.0  NaN    1   0
6   NaN  1.0    1   0

The following code is what I have so far, which works fine but does not iterate over the values of column '2'.

df.isna().sum(axis=1).apply(lambda x: df[2].iloc[x] if x==0 else 0)

if I use df.iloc[x] I get

How can I iterate over the column '2'?

U13-Forward · Accepted Answer · 2021-08-21 05:50:02Z

2

Try the below code with np.where with isna and any:

>>> df['3'] = np.where(df[['0', '1']].isna().any(1), 0, df['2'])
>>> df
     0    1  2  3
0  2.0  2.0  4  4
0  1.0  1.0  2  2
0  1.0  1.0  3  3
3  1.0  1.0  5  5
4  1.0  1.0  2  2
5  1.0  NaN  1  0
6  NaN  1.0  1  0
>>>

edited Aug 21, 2021 at 5:50

answered Aug 21, 2021 at 5:43

U13-Forward

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2 Comments

Corralien Over a year ago

To be more precise, you can replace df.isna().any(1) by df[['0', '1']].isna().any(1)

U13-Forward Over a year ago

@Corralien That is true, edited my answer!

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