pyspark.pandas.groupby.GroupBy.backfill

GroupBy.backfill(limit: Optional[int] = None) → FrameLike

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

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 backward.

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

pyspark.pandas.groupby.GroupBy.head pyspark.pandas.groupby.GroupBy.shift