maxframe.dataframe.Series.dropna#

Series.dropna(axis=0, inplace=False, how=None, ignore_index=False)#

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.

  • how (str, optional) – Not in use. Kept for compatibility.

  • ignore_index (bool, default False) – If True, the resulting axis will be labeled 0, 1, …, n - 1.

Returns:

Series with NA entries dropped from it.

Return type:

Series

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

>>> import maxframe.dataframe as md
>>> ser = md.Series([1., 2., np.nan])
>>> ser.execute()
0    1.0
1    2.0
2    NaN
dtype: float64

Drop NA values from a Series.

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

Keep the Series with valid entries in the same variable.

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

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

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