HyukjinKwon commented on a change in pull request #32835:
URL: https://github.com/apache/spark/pull/32835#discussion_r648802230
##########
File path: python/docs/source/user_guide/pandas_on_spark/types.rst
##########
@@ -204,21 +204,21 @@ You can also check the underlying PySpark data type of
`Series` or schema of `Da
>>> ks.Series([0.3, 0.1, 0.8]).spark.data_type
DoubleType
- >>> ks.Series(["welcome", "to", "Koalas"]).spark.data_type
+ >>> ks.Series(["welcome", "to", "pandas APIs on Spark"]).spark.data_type
StringType
>>> ks.Series([[False, True, False]]).spark.data_type
ArrayType(BooleanType,true)
- >>> ks.DataFrame({"d": [0.3, 0.1, 0.8], "s": ["welcome", "to", "Koalas"],
"b": [False, True, False]}).spark.print_schema()
+ >>> ks.DataFrame({"d": [0.3, 0.1, 0.8], "s": ["welcome", "to", "pandas
APIs on Spark"], "b": [False, True, False]}).spark.print_schema()
Review comment:
```suggestion
>>> ks.DataFrame({"d": [0.3, 0.1, 0.8], "s": ["welcome", "to",
"pandas-on-Spark"], "b": [False, True, False]}).spark.print_schema()
```
##########
File path: python/docs/source/user_guide/pandas_on_spark/types.rst
##########
@@ -204,21 +204,21 @@ You can also check the underlying PySpark data type of
`Series` or schema of `Da
>>> ks.Series([0.3, 0.1, 0.8]).spark.data_type
DoubleType
- >>> ks.Series(["welcome", "to", "Koalas"]).spark.data_type
+ >>> ks.Series(["welcome", "to", "pandas APIs on Spark"]).spark.data_type
StringType
>>> ks.Series([[False, True, False]]).spark.data_type
ArrayType(BooleanType,true)
- >>> ks.DataFrame({"d": [0.3, 0.1, 0.8], "s": ["welcome", "to", "Koalas"],
"b": [False, True, False]}).spark.print_schema()
+ >>> ks.DataFrame({"d": [0.3, 0.1, 0.8], "s": ["welcome", "to", "pandas
APIs on Spark"], "b": [False, True, False]}).spark.print_schema()
root
|-- d: double (nullable = false)
|-- s: string (nullable = false)
|-- b: boolean (nullable = false)
.. note::
- Koalas currently does not support multiple types of data in single column.
+ Pandas APIs on Spark currently does not support multiple types of data in
single column.
Review comment:
```suggestion
Pandas APIs on Spark currently do not support multiple types of data in
single column.
```
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