1

How can I select the rows with null values in respect of columns name?

What I have:

ID A B
1 a b
2 v
3 y
4 w j
5 w

What I want:

Select rows with null in respect with e.g. column B:

ID B
3 y
5 w
3
  • why 2 not selected? Commented Feb 7, 2021 at 16:01
  • Because I want to select the null values only in column B! Commented Feb 7, 2021 at 16:03
  • 2
    df[df['B'].isna()] Commented Feb 7, 2021 at 16:05

2 Answers 2

1

Use pandas.DataFrame.pop and pandas.Series.isna:

>>> df
   ID    A    B
0   1    a    b
1   2  NaN    v
2   3    y  NaN
3   4    w    j
4   5    w  NaN

>>> df[df.pop('B').isna()]

   ID  A
2   3  y
4   5  w

Use pop if you do not need column 'B' in the original dataframe afterwards. Otherwise, use pandas.DataFrame.drop:

>>> df[df['B'].isna()].drop('B', axis=1)
Sign up to request clarification or add additional context in comments.

Comments

1

I guess you can use isna() or isnull() functions.

df[df['column name'].isna()]

(or)

df[df['column name'].isnull()]

Comments

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy.

Start asking to get answers

Find the answer to your question by asking.

Ask question

Explore related questions

See similar questions with these tags.