From c25ed02b4079917eb421d2a4e3d0cfb249a95a0b Mon Sep 17 00:00:00 2001
From: Ashley Xu <ashleyxu@google.com>
Date: Fri, 26 Jan 2024 23:09:29 +0000
Subject: [PATCH] docs: add code samples for Series.{between, cumprod}

---
 .../bigframes_vendored/pandas/core/series.py  | 60 +++++++++++++++++++
 1 file changed, 60 insertions(+)

diff --git a/third_party/bigframes_vendored/pandas/core/series.py b/third_party/bigframes_vendored/pandas/core/series.py
index 1aa4ffffbb..822ac3098e 100644
--- a/third_party/bigframes_vendored/pandas/core/series.py
+++ b/third_party/bigframes_vendored/pandas/core/series.py
@@ -1774,6 +1774,42 @@ def between(
         corresponding Series element is between the boundary values `left` and
         `right`. NA values are treated as `False`.
 
+        **Examples:**
+
+            >>> import bigframes.pandas as bpd
+            >>> bpd.options.display.progress_bar = None
+
+        Boundary values are included by default:
+
+            >>> s = bpd.Series([2, 0, 4, 8, np.nan])
+            >>> s.between(1, 4)
+            0     True
+            1    False
+            2     True
+            3    False
+            4     <NA>
+            dtype: boolean
+
+        With inclusive set to "neither" boundary values are excluded:
+
+            >>> s.between(1, 4, inclusive="neither")
+            0     True
+            1    False
+            2    False
+            3    False
+            4     <NA>
+            dtype: boolean
+
+        left and right can be any scalar value:
+
+            >>> s = bpd.Series(['Alice', 'Bob', 'Carol', 'Eve'])
+            >>> s.between('Anna', 'Daniel')
+            0    False
+            1     True
+            2     True
+            3    False
+            dtype: boolean
+
         Args:
             left (scalar or list-like):
                 Left boundary.
@@ -1796,6 +1832,30 @@ def cumprod(self):
         Returns a DataFrame or Series of the same size containing the cumulative
         product.
 
+        **Examples:**
+
+            >>> import bigframes.pandas as bpd
+            >>> bpd.options.display.progress_bar = None
+
+            >>> s = bpd.Series([2, np.nan, 5, -1, 0])
+            >>> s
+            0     2.0
+            1    <NA>
+            2     5.0
+            3    -1.0
+            4     0.0
+            dtype: Float64
+
+        By default, NA values are ignored.
+
+            >>> s.cumprod()
+            0     2.0
+            1    <NA>
+            2    10.0
+            3   -10.0
+            4     0.0
+            dtype: Float64
+
         Returns:
             bigframes.series.Series: Return cumulative sum of scalar or Series.
         """