Skip to content

DOC: update docstrings for ffill and bfill (no longer aliases for fillna with method) #54803

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 1 commit into from
Aug 28, 2023
Merged

DOC: update docstrings for ffill and bfill (no longer aliases for fillna with method) #54803

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
60 changes: 55 additions & 5 deletions pandas/core/generic.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -7099,6 +7099,8 @@ def fillna(

See Also
--------
ffill : Fill values by propagating the last valid observation to next valid.
bfill : Fill values by using the next valid observation to fill the gap.
interpolate : Fill NaN values using interpolation.
reindex : Conform object to new index.
asfreq : Convert TimeSeries to specified frequency.
Expand Down Expand Up @@ -7358,7 +7360,10 @@ def ffill(
...

@final
@doc(klass=_shared_doc_kwargs["klass"])
@doc(
klass=_shared_doc_kwargs["klass"],
axes_single_arg=_shared_doc_kwargs["axes_single_arg"],
)
def ffill(
self,
*,
Expand All @@ -7370,6 +7375,27 @@ def ffill(
"""
Fill NA/NaN values by propagating the last valid observation to next valid.

Parameters
----------
axis : {axes_single_arg}
Axis along which to fill missing values. For `Series`
this parameter is unused and defaults to 0.
inplace : bool, default False
If True, fill in-place. Note: this will modify any
other views on this object (e.g., a no-copy slice for a column in a
DataFrame).
limit : int, 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.
downcast : dict, default is None
A dict of item->dtype of what to downcast if possible,
or the string 'infer' which will try to downcast to an appropriate
equal type (e.g. float64 to int64 if possible).

Returns
-------
{klass} or None
Expand Down Expand Up @@ -7437,7 +7463,7 @@ def pad(
downcast: dict | None | lib.NoDefault = lib.no_default,
) -> Self | None:
"""
Synonym for :meth:`DataFrame.fillna` with ``method='ffill'``.
Fill NA/NaN values by propagating the last valid observation to next valid.

.. deprecated:: 2.0

Expand Down Expand Up @@ -7494,7 +7520,10 @@ def bfill(
...

@final
@doc(klass=_shared_doc_kwargs["klass"])
@doc(
klass=_shared_doc_kwargs["klass"],
axes_single_arg=_shared_doc_kwargs["axes_single_arg"],
)
def bfill(
self,
*,
Expand All @@ -7504,7 +7533,28 @@ def bfill(
downcast: dict | None | lib.NoDefault = lib.no_default,
) -> Self | None:
"""
Synonym for :meth:`DataFrame.fillna` with ``method='bfill'``.
Fill NA/NaN values by using the next valid observation to fill the gap.

Parameters
----------
axis : {axes_single_arg}
Axis along which to fill missing values. For `Series`
this parameter is unused and defaults to 0.
inplace : bool, default False
If True, fill in-place. Note: this will modify any
other views on this object (e.g., a no-copy slice for a column in a
DataFrame).
limit : int, 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.
downcast : dict, default is None
A dict of item->dtype of what to downcast if possible,
or the string 'infer' which will try to downcast to an appropriate
equal type (e.g. float64 to int64 if possible).

Returns
-------
Expand Down Expand Up @@ -7583,7 +7633,7 @@ def backfill(
downcast: dict | None | lib.NoDefault = lib.no_default,
) -> Self | None:
"""
Synonym for :meth:`DataFrame.fillna` with ``method='bfill'``.
Fill NA/NaN values by using the next valid observation to fill the gap.

.. deprecated:: 2.0

Expand Down