How to Check for NaN in a pandas DataFrame

TLDR solution

# check if there is a nan in the whole df
df.isna().values.any()

# check a specific column
df['column'].isna().values.any()

# show the row where a specific column has a nan
df.loc[df['column'].isna()]

Step-by-Step Example

Let's say, you have the following DataFrame:

      a    b
0  10.0  1.0
1   3.0  NaN
2   5.0  4.0
3 -20.0  0.0
4   NaN  NaN

Check if There are any NaN Values

Use the following code to check if there is at least one NaN value in your DataFrame:

df.isna().values.any()

The output:

True

Check if a Specific Column has a NaN Value

df['a'].isna().values.any()

Show all Rows That Have a NaN in a Specific Column

df.loc[df['a'].isna()]

Count NaN Values

df.isna().sum() # grouped by column
df.isna().sum().sum() # total

That's it! You just learned how to check for NaN values in a pandas DataFrame.