dask.dataframe.Index.dropna

dask.dataframe.Index.dropna¶

Index.dropna()¶

Return a new Series with missing values removed.

This docstring was copied from pandas.core.series.Series.dropna.

Some inconsistencies with the Dask version may exist.

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

Parameters

axis{0 or ‘index’} (Not supported in Dask): Unused. Parameter needed for compatibility with DataFrame.
inplacebool, default False (Not supported in Dask): If True, do operation inplace and return None.
howstr, optional (Not supported in Dask): Not in use. Kept for compatibility.
ignore_indexbool, default False (Not supported in Dask): If True, the resulting axis will be labeled 0, 1, …, n - 1.

New in version 2.0.0.

Returns

Series or None: Series with NA entries dropped from it or None if inplace=True.

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

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

dask.dataframe.Index.drop_duplicates

dask.dataframe.Index.dtype