Series.
dropna
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.
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.
Series with NA entries dropped from it.
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 mars.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.
None
>>> 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