pandas.DataFrame.isnull#

DataFrame.isnull()[source] #

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 (unless you set pandas.options.mode.use_inf_as_na = True).

Returns:

DataFrame

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

See also

DataFrame.isnull

Alias of isna.

DataFrame.notna

Boolean inverse of isna.

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年05月27日'),
...  pd.Timestamp('1940年04月25日')],
...  name=['Alfred', 'Batman', ''],
...  toy=[None, 'Batmobile', 'Joker']))
>>> df
 age born name toy
0 5.0 NaT Alfred None
1 6.0 1939年05月27日 Batman Batmobile
2 NaN 1940年04月25日 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