HyukjinKwon commented on a change in pull request #32835:
URL: https://github.com/apache/spark/pull/32835#discussion_r648801334
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File path: python/docs/source/user_guide/pandas_on_spark/typehints.rst
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@@ -66,16 +66,16 @@ Likewise, pandas Series can be also used as a type hints:
>>> df = ks.DataFrame([[4, 9]] * 3, columns=['A', 'B'])
>>> df.apply(sqrt, axis=0)
-Currently, both Koalas and pandas instances can be used to specify the type
hints; however, Koalas
+Currently, both pandas APIs on Spark and pandas instances can be used to
specify the type hints; however, pandas APIs on Spark
plans to move gradually towards using pandas instances only as the stability
becomes proven.
Type Hinting with Names
-----------------------
-In Koalas 1.0, the new style of type hinting was introduced to overcome the
limitations in the existing type
+In pandas APIs on Spark 1.0, the new style of type hinting was introduced to
overcome the limitations in the existing type
hinting especially for DataFrame. When you use a DataFrame as the return type
hint, for example,
-``DataFrame[int, int]``, there is no way to specify the names of each Series.
In the old way, Koalas just generates
+``DataFrame[int, int]``, there is no way to specify the names of each Series.
In the old way, pandas APIs on Spark just generates
Review comment:
```suggestion
``DataFrame[int, int]``, there is no way to specify the names of each
Series. In the old way, pandas APIs on Spark just generate
```
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