How to replace blank values (white space) with NaN in Python Pandas?

Sometimes, we want to replace blank values (white space) with NaN in Python Pandas.

In this article, we’ll look at how to replace blank values (white space) with NaN in Python Pandas.

How to replace blank values (white space) with NaN in Python Pandas?

To replace blank values (white space) with NaN in Python Pandas, we can call replace on the data frame.

For instance, we write

df = pd.DataFrame([
    [-0.532681, 'foo', 0],
    [1.490752, 'bar', 1],
    [-1.387326, 'foo', 2],
    [0.814772, 'baz', ' '],     
    [-0.222552, '   ', 4],
    [-1.176781,  'qux', '  '],         
], columns='A B C'.split(), index=pd.date_range('2000-01-01','2000-01-06'))

print(df.replace(r'^\s*$', np.nan, regex=True))

to create the df` data frame.

Then we replace all whitespace values with NaN by call replace with the regex to match whitespaces, np.nan and regex set to True.

Conclusion

To replace blank values (white space) with NaN in Python Pandas, we can call replace on the data frame.