pandas check null in data frame except one column

Question

I have a data frame and I want do a null check and store the null value rows in separate data frame. But, one constrain is, I don't want to do null check for one particular column. How can I achieve this?

For example, In below Data Frame,

   Name  Age  Class
0   tom   10      NaN
1  nick   15     10
2  juli   14      9

If I apply, df[df.isnull().any(axis=1)], It gives me

   Name  Age  Class
0  tom   10    NaN

But, I want don't want to do null check for Class column and I'm expecting empty data frame for this case. I have searched in SO but couldn't find the solution.

Georgina Skibinski · Accepted Answer · 2020-10-22 16:01:59Z

2

Try:

cols_to_excl = ['Class']

df.loc[df[df.columns ^ cols_to_excl].isnull().any(axis=1)]

In essence: df.columns ^ cols_to_excl will return all columns, besides all the columns from the list cols_to_excl.

answered Oct 22, 2020 at 16:01

Georgina Skibinski

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SOURAV KUMAR · Accepted Answer · 2020-10-22 16:10:05Z

1

You can try the following :

df[df.iloc[:, :2].isnull().any(axis=1)]

This can work if you know that your function will only work on this dataframe otherwise you can try generalized approach as stated by @Grzegorz Skibinski

answered Oct 22, 2020 at 16:10

SOURAV KUMAR

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BehRouz · Accepted Answer · 2023-01-04 19:05:56Z

0

xor operation will be deprecated in newer versions. Pandas suggests using symmetric_difference instead.

cols_to_excl = ['Class']

df.loc[df[df.columns.symmetric_difference(cols_to_excl)].isnull().any(axis=1)]

answered Jan 4, 2023 at 19:05

BehRouz

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