Remove redundant escape characters, remove unrelated changes

G-Research · Nov 20, 2023 · 8bd554d · 8bd554d
1 parent 08cbab0
commit 8bd554d
Showing 1 changed file with 7 additions and 7 deletions.
diff --git a/python/pyspark/sql/pandas/group_ops.py b/python/pyspark/sql/pandas/group_ops.py
@@ -524,7 +524,7 @@ def applyInPandas(
         self, func: "PandasCogroupedMapFunction", schema: Union[StructType, str]
     ) -> DataFrame:
         """
-        Applies a function to each cogroup using Pandas and returns the result
+        Applies a function to each cogroup using pandas and returns the result
         as a `DataFrame`.
 
         The function should take two `pandas.DataFrame`\\s and return another
@@ -582,7 +582,7 @@ def applyInPandas(
         the grouping key(s) will be passed as the first argument and the data will be passed as the
         second and third arguments.  The grouping key(s) will be passed as a tuple of numpy data
         types, e.g., `numpy.int32` and `numpy.float64`. The data will still be passed in as two
-        `pandas.DataFrame`\\s containing all columns from the original Spark DataFrames.
+        `pandas.DataFrame` containing all columns from the original Spark DataFrames.
 
         >>> def asof_join(k, l, r):
         ...     if k == (1,):
@@ -630,9 +630,9 @@ def applyInArrow(
         Applies a function to each cogroup using Arrow and returns the result
         as a `DataFrame`.
 
-        The function should take two `pyarrow.Table`\\s and return another
+        The function should take two `pyarrow.Table`s and return another
         `pyarrow.Table`. Alternatively, the user can pass a function that takes
-        a tuple of `pyarrow.Scalar` grouping key(s) and the two `pyarrow.Table`\\s.
+        a tuple of `pyarrow.Scalar` grouping key(s) and the two `pyarrow.Table`s.
         For each side of the cogroup, all columns are passed together as a
         `pyarrow.Table` to the user-function and the returned `pyarrow.Table` are combined as
         a :class:`DataFrame`.
@@ -648,9 +648,9 @@ def applyInArrow(
         Parameters
         ----------
         func : function
-            a Python native function that takes two `pyarrow.Table`\\s, and
+            a Python native function that takes two `pyarrow.Table`s, and
             outputs a `pyarrow.Table`, or that takes one tuple (grouping keys) and two
-            ``pyarrow.Table``\\s, and outputs a ``pyarrow.Table``.
+            ``pyarrow.Table``s, and outputs a ``pyarrow.Table``.
         schema : :class:`pyspark.sql.types.DataType` or str
             the return type of the `func` in PySpark. The value can be either a
             :class:`pyspark.sql.types.DataType` object or a DDL-formatted type string.
@@ -679,7 +679,7 @@ def applyInArrow(
         the grouping key(s) will be passed as the first argument and the data will be passed as the
         second and third arguments.  The grouping key(s) will be passed as a tuple of Arrow scalars
         types, e.g., `pyarrow.Int32Scalar` and `pyarrow.FloatScalar`. The data will still be passed
-        in as two `pyarrow.Table`\\s containing all columns from the original Spark DataFrames.
+        in as two `pyarrow.Table`s containing all columns from the original Spark DataFrames.
 
         >>> def summarize(key, l, r):
         ...     return pyarrow.Table.from_pydict({