cudf.Series.fillna#
- Series.fillna(value=None, method=None, axis=None, inplace=False, limit=None)[source]#
Fill null values with
value
or specifiedmethod
.- Parameters:
- valuescalar, Series-like or dict
Value to use to fill nulls. If Series-like, null values are filled with values in corresponding indices. A dict can be used to provide different values to fill nulls in different columns. Cannot be used with
method
.- method{‘ffill’, ‘bfill’}, default None
Method to use for filling null values in the dataframe or series. ffill propagates the last non-null values forward to the next non-null value. bfill propagates backward with the next non-null value. Cannot be used with
value
.Deprecated since version 24.04: method is deprecated.
- Returns:
- resultDataFrame, Series, or Index
Copy with nulls filled.
Examples
>>> import cudf >>> df = cudf.DataFrame({'a': [1, 2, None], 'b': [3, None, 5]}) >>> df a b 0 1 3 1 2 <NA> 2 <NA> 5 >>> df.fillna(4) a b 0 1 3 1 2 4 2 4 5 >>> df.fillna({'a': 3, 'b': 4}) a b 0 1 3 1 2 4 2 3 5
fillna
on a Series object:>>> ser = cudf.Series(['a', 'b', None, 'c']) >>> ser 0 a 1 b 2 <NA> 3 c dtype: object >>> ser.fillna('z') 0 a 1 b 2 z 3 c dtype: object
fillna
can also supports inplace operation:>>> ser.fillna('z', inplace=True) >>> ser 0 a 1 b 2 z 3 c dtype: object >>> df.fillna({'a': 3, 'b': 4}, inplace=True) >>> df a b 0 1 3 1 2 4 2 3 5
fillna
specified with fillmethod
>>> ser = cudf.Series([1, None, None, 2, 3, None, None]) >>> ser.fillna(method='ffill') 0 1 1 1 2 1 3 2 4 3 5 3 6 3 dtype: int64 >>> ser.fillna(method='bfill') 0 1 1 2 2 2 3 2 4 3 5 <NA> 6 <NA> dtype: int64