From fa66249bbcb04b3054c200dbe9ba0b1e29ec4a7b Mon Sep 17 00:00:00 2001
From: Ashley Xu <ashleyxu@google.com>
Date: Sat, 6 Jan 2024 04:39:59 +0000
Subject: [PATCH 1/2] docs: add code samples for Series.ffill and
 DataFrame.ffill

---
 .../bigframes_vendored/pandas/core/generic.py | 42 +++++++++++++++++++
 1 file changed, 42 insertions(+)

diff --git a/third_party/bigframes_vendored/pandas/core/generic.py b/third_party/bigframes_vendored/pandas/core/generic.py
index 72b947f96c..cc35571bf6 100644
--- a/third_party/bigframes_vendored/pandas/core/generic.py
+++ b/third_party/bigframes_vendored/pandas/core/generic.py
@@ -627,6 +627,48 @@ def copy(self):
     def ffill(self, *, limit: Optional[int] = None):
         """Fill NA/NaN values by propagating the last valid observation to next valid.
 
+        **Examples:**
+
+            >>> import bigframes.pandas as bpd
+            >>> import numpy as np
+            >>> bpd.options.display.progress_bar = None
+
+            >>> df = bpd.DataFrame([[np.nan, 2, np.nan, 0],
+            ...                     [3, 4, np.nan, 1],
+            ...                     [np.nan, np.nan, np.nan, np.nan],
+            ...                     [np.nan, 3, np.nan, 4]],
+            ...                    columns=list("ABCD")).astype("Float64")
+            >>> df
+                A     B     C     D
+            0  <NA>   2.0  <NA>   0.0
+            1   3.0   4.0  <NA>   1.0
+            2  <NA>  <NA>  <NA>  <NA>
+            3  <NA>   3.0  <NA>   4.0
+            <BLANKLINE>
+            [4 rows x 4 columns]
+
+        Fill NA/NaN values in DataFrames:
+
+            >>> df.ffill()
+                   A    B     C    D
+            0  <NA>  2.0  <NA>  0.0
+            1   3.0  4.0  <NA>  1.0
+            2   3.0  4.0  <NA>  1.0
+            3   3.0  3.0  <NA>  4.0
+            <BLANKLINE>
+            [4 rows x 4 columns]
+
+
+        Fill NA/NaN values in Series:
+
+            >>> series = bpd.Series([1, np.nan, 2, 3])
+            >>> series.ffill()
+            0    1.0
+            1    1.0
+            2    2.0
+            3    3.0
+            dtype: Float64
+
         Args:
             limit : int, default None
                 If method is specified, this is the maximum number of consecutive

From e24537e896b3182f1d11ac09880ec5f16d03bc5d Mon Sep 17 00:00:00 2001
From: Ashley Xu <ashleyxu@google.com>
Date: Mon, 8 Jan 2024 04:39:21 +0000
Subject: [PATCH 2/2] address comments

---
 third_party/bigframes_vendored/pandas/core/generic.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/third_party/bigframes_vendored/pandas/core/generic.py b/third_party/bigframes_vendored/pandas/core/generic.py
index cc35571bf6..2ca51f6493 100644
--- a/third_party/bigframes_vendored/pandas/core/generic.py
+++ b/third_party/bigframes_vendored/pandas/core/generic.py
@@ -639,7 +639,7 @@ def ffill(self, *, limit: Optional[int] = None):
             ...                     [np.nan, 3, np.nan, 4]],
             ...                    columns=list("ABCD")).astype("Float64")
             >>> df
-                A     B     C     D
+                  A     B     C     D
             0  <NA>   2.0  <NA>   0.0
             1   3.0   4.0  <NA>   1.0
             2  <NA>  <NA>  <NA>  <NA>
@@ -650,7 +650,7 @@ def ffill(self, *, limit: Optional[int] = None):
         Fill NA/NaN values in DataFrames:
 
             >>> df.ffill()
-                   A    B     C    D
+                  A    B     C    D
             0  <NA>  2.0  <NA>  0.0
             1   3.0  4.0  <NA>  1.0
             2   3.0  4.0  <NA>  1.0