doctests

Author: TrevorBergeron

packages/bigframes/third_party/bigframes_vendored/pandas/core/frame.py

@@ -4470,6 +4470,22 @@ def map(self, func, na_action: Optional[str] = None) -> DataFrame:
             <BLANKLINE>
             [7 rows x 2 columns]
 
+        With experimental Python Transpiler enabled, you can use some lambda functions without
+        deploying them as remote functions.
+
+            >>> bpd.options.experiments.enable_python_transpiler = True
+            >>> df_minutes.map(lambda hours: hours / 60)
+            system_minutes  user_minutes
+            0             0.0           0.0
+            1             0.5          0.25
+            2             1.0          1.25
+            3            <NA>           1.5
+            4             1.5           0.1
+            5             2.0          <NA>
+            6            <NA>          <NA>
+            <BLANKLINE>
+            [7 rows x 2 columns]
+
         Args:
             func (function):
                 Python function wrapped by ``remote_function`` decorator,
@@ -5053,6 +5069,15 @@ def apply(self, func, *, axis=0, args=(), **kwargs):
             1    3.8
             dtype: Float64
 
+        With experimental Python Transpiler enabled, you can use some lambda functions without
+        deploying them as remote functions:
+
+            >>> bpd.options.experiments.enable_python_transpiler = True
+            >>> df.apply(lambda row: 1 + row.col1 + row.col2/row.col3, axis=1)
+            0    2.6
+            1    3.8
+            dtype: Float64
+
         Args:
             func (function):
                 Function to apply to each column or row. To apply to each row

packages/bigframes/third_party/bigframes_vendored/pandas/core/series.py

@@ -5631,6 +5631,17 @@ def map(
             3    rAbbIt
             dtype: string
 
+        With experimental Python Transpiler enabled, you can use some lambda functions without
+        deploying them as remote functions:
+
+            >>> bpd.options.experiments.enable_python_transpiler = True
+            >>> s.map(lambda val: val + "fish")
+            0       catfish
+            1       dogfish
+            2          <NA>
+            3    rabbitfish
+            dtype: string
+
         Args:
             arg (function, Mapping, Series):
                 remote function, collections.abc.Mapping subclass or Series