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pandas.Series.dropna

Series.dropna(axis=0, inplace=False, **kwargs) [source]

Return a new Series with missing values removed.

See the User Guide for more on which values are considered missing, and how to work with missing data.

Parameters:

axis : {0 or ‘index’}, default 0

There is only one axis to drop values from.

inplace : bool, default False

If True, do operation inplace and return None.

**kwargs

Not in use.

Returns:

Series

Series with NA entries dropped from it.

See also

Series.isna
Indicate missing values.
Series.notna
Indicate existing (non-missing) values.
Series.fillna
Replace missing values.
DataFrame.dropna
Drop rows or columns which contain NA values.
Index.dropna
Drop missing indices.

Examples

>>> ser = pd.Series([1., 2., np.nan])
>>> ser
0    1.0
1    2.0
2    NaN
dtype: float64

Drop NA values from a Series.

>>> ser.dropna()
0    1.0
1    2.0
dtype: float64

Keep the Series with valid entries in the same variable.

>>> ser.dropna(inplace=True)
>>> ser
0    1.0
1    2.0
dtype: float64

Empty strings are not considered NA values. None is considered an NA value.

>>> ser = pd.Series([np.NaN, 2, pd.NaT, '', None, 'I stay'])
>>> ser
0       NaN
1         2
2       NaT
3
4      None
5    I stay
dtype: object
>>> ser.dropna()
1         2
3
5    I stay
dtype: object

© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.Series.dropna.html