pandas.DataFrame.isnull

DataFrame.isnull()

DataFrame.isnull is an alias for DataFrame.isna.

Detect missing values.

Return a boolean same-sized object indicating if the values are NA. NA values, such as None or numpy.NaN, gets mapped to True values. Everything else gets mapped to False values. Characters such as empty strings '' or numpy.inf are not considered NA values.

Returns:

Series/DataFrame

Mask of bool values for each element in Series/DataFrame that indicates whether an element is an NA value.

See also

Series.isnull

Alias of isna.

DataFrame.isnull

Alias of isna.

Series.notna

Boolean inverse of isna.

DataFrame.notna

Boolean inverse of isna.

Series.dropna

Omit axes labels with missing values.

DataFrame.dropna

Omit axes labels with missing values.

isna

Top-level isna.

Examples

Show which entries in a DataFrame are NA.

>>> df = pd.DataFrame(
...     dict(
...         age=[5, 6, np.nan],
...         born=[
...             pd.NaT,
...             pd.Timestamp("1939-05-27"),
...             pd.Timestamp("1940-04-25"),
...         ],
...         name=["Alfred", "Batman", ""],
...         toy=[None, "Batmobile", "Joker"],
...     )
... )
>>> df
   age       born    name        toy
0  5.0        NaT  Alfred        NaN
1  6.0 1939-05-27  Batman  Batmobile
2  NaN 1940-04-25              Joker

>>> df.isna()
     age   born   name    toy
0  False   True  False   True
1  False  False  False  False
2   True  False  False  False

Show which entries in a Series are NA.

>>> ser = pd.Series([5, 6, np.nan])
>>> ser
0    5.0
1    6.0
2    NaN
dtype: float64

>>> ser.isna()
0    False
1    False
2     True
dtype: bool