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Checking if a DataFrame contains any missing values in Pandas

schedule Aug 12, 2023
Last updated
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Example

Consider the following DataFrame:

df = pd.DataFrame({"A":[np.nan,3], "B":[4,5]})
df
   A    B
0  NaN  4
1  3.0  5

Solution

To check if a DataFrame contains any missing values:

df.isna().any(axis=None)
True

Explanation

Here, isna() returns a DataFrame of booleans where True indicates a missing value:

df.isna()
   A      B
0  True   False
1  False  False

Finally, we use the DataFrame.any(~) method to check whether or not there are any True values in this DataFrame. The parameter axis=None indicates that we want to scan the entire DataFrame rather than to scan each row/column:

df.isna().any(axis=None)
True
robocat
Published by Isshin Inada
Edited by 0 others
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