cudf.DataFrame.fillna

DataFrame.fillna(value=None, method=None, axis=None, inplace=False, limit=None)

Fill null values with value or specified method.

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 fill method

>>> 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