# How to count the NaN values in a column in pandas DataFrame

You can use the `isna()`

method (or it's alias `isnull()`

which is also compatible with older pandas versions < 0.21.0) and then sum to count the NaN values. For one column:

`In [1]: s = pd.Series([1,2,3, np.nan, np.nan])In [4]: s.isna().sum() # or s.isnull().sum() for older pandas versionsOut[4]: 2`

For several columns, it also works:

`In [5]: df = pd.DataFrame({'a':[1,2,np.nan], 'b':[np.nan,1,np.nan]})In [6]: df.isna().sum()Out[6]:a 1b 2dtype: int64`