pyspark.pandas.groupby.GroupBy.ffill#

GroupBy.ffill(limit=None)[source]#

Synonym for DataFrame.fillna() with method=`ffill`.

Parameters

axis{0 or index}: 1 and columns are not supported.
inplaceboolean, default False: Fill in place (do not create a new object)
limitint, default None: If method is specified, this is the maximum number of consecutive NaN values to forward/backward fill. In other words, if there is a gap with more than this number of consecutive NaNs, it will only be partially filled. If method is not specified, this is the maximum number of entries along the entire axis where NaNs will be filled. Must be greater than 0 if not None

Returns

DataFrame: DataFrame with NA entries filled.

Examples

>>> df = ps.DataFrame({
...     'A': [1, 1, 2, 2],
...     'B': [2, 4, None, 3],
...     'C': [None, None, None, 1],
...     'D': [0, 1, 5, 4]
...     },
...     columns=['A', 'B', 'C', 'D'])
>>> df
   A    B    C  D
0  1  2.0  NaN  0
1  1  4.0  NaN  1
2  2  NaN  NaN  5
3  2  3.0  1.0  4

Propagate non-null values forward.

>>> df.groupby(['A']).ffill().sort_index()
     B    C  D
0  2.0  NaN  0
1  4.0  NaN  1
2  NaN  NaN  5
3  3.0  1.0  4