HyukjinKwon commented on a change in pull request #32835:
URL: https://github.com/apache/spark/pull/32835#discussion_r648801975
##########
File path: python/docs/source/user_guide/pandas_on_spark/types.rst
##########
@@ -44,11 +44,11 @@ The example below shows how data types are casted from
PySpark DataFrame to Koal
dtype: object
-The example below shows how data types are casted from Koalas DataFrame to
PySpark DataFrame.
+The example below shows how data types are casted from pandas APIs on Spark
DataFrame to PySpark DataFrame.
.. code-block:: python
- # 1. Create a Koalas DataFrame
+ # 1. Create a pandas APIs on Spark DataFrame
Review comment:
pandas-on-Spark DataFrame
##########
File path: python/docs/source/user_guide/pandas_on_spark/types.rst
##########
@@ -57,7 +57,7 @@ The example below shows how data types are casted from Koalas
DataFrame to PySpa
>>> kdf['int32'] = kdf['int32'].astype('int32')
>>> kdf['float32'] = kdf['float32'].astype('float32')
- # 3. Check the Koalas data types
+ # 3. Check the pandas APIs on Spark data types
Review comment:
pandas-on-Spark data types
##########
File path: python/docs/source/user_guide/pandas_on_spark/types.rst
##########
@@ -72,22 +72,22 @@ The example below shows how data types are casted from
Koalas DataFrame to PySpa
object_date object
dtype: object
- # 4. Convert Koalas DataFrame to PySpark DataFrame
+ # 4. Convert pandas APIs on Spark DataFrame to PySpark DataFrame
Review comment:
pandas-on-Spark DataFrame
##########
File path: python/docs/source/user_guide/pandas_on_spark/types.rst
##########
@@ -72,22 +72,22 @@ The example below shows how data types are casted from
Koalas DataFrame to PySpa
object_date object
dtype: object
- # 4. Convert Koalas DataFrame to PySpark DataFrame
+ # 4. Convert pandas APIs on Spark DataFrame to PySpark DataFrame
>>> sdf = kdf.to_spark()
# 5. Check the PySpark data types
>>> sdf
DataFrame[int8: tinyint, bool: boolean, float32: float, float64: double,
int32: int, int64: bigint, int16: smallint, datetime: timestamp, object_string:
string, object_decimal: decimal(2,1), object_date: date]
-Type casting between pandas and Koalas
---------------------------------------
+Type casting between pandas and pandas APIs on Spark
+----------------------------------------------------
-When converting Koalas DataFrame to pandas DataFrame, and the data types are
basically same as pandas.
+When converting pandas APIs on Spark DataFrame to pandas DataFrame, and the
data types are basically same as pandas.
Review comment:
pandas-on-Spark DataFrame
##########
File path: python/docs/source/user_guide/pandas_on_spark/types.rst
##########
@@ -72,22 +72,22 @@ The example below shows how data types are casted from
Koalas DataFrame to PySpa
object_date object
dtype: object
- # 4. Convert Koalas DataFrame to PySpark DataFrame
+ # 4. Convert pandas APIs on Spark DataFrame to PySpark DataFrame
>>> sdf = kdf.to_spark()
# 5. Check the PySpark data types
>>> sdf
DataFrame[int8: tinyint, bool: boolean, float32: float, float64: double,
int32: int, int64: bigint, int16: smallint, datetime: timestamp, object_string:
string, object_decimal: decimal(2,1), object_date: date]
-Type casting between pandas and Koalas
---------------------------------------
+Type casting between pandas and pandas APIs on Spark
+----------------------------------------------------
-When converting Koalas DataFrame to pandas DataFrame, and the data types are
basically same as pandas.
+When converting pandas APIs on Spark DataFrame to pandas DataFrame, and the
data types are basically same as pandas.
.. code-block:: python
- # Convert Koalas DataFrame to pandas DataFrame
+ # Convert pandas APIs on Spark DataFrame to pandas DataFrame
Review comment:
pandas-on-Spark DataFrame
##########
File path: python/docs/source/user_guide/pandas_on_spark/types.rst
##########
@@ -177,7 +177,7 @@ datetime.date DateType
decimal.Decimal DecimalType(38, 18)
================= ===================
-For decimal type, Koalas uses Spark's system default precision and scale.
+For decimal type, pandas APIs on Spark uses Spark's system default precision
and scale.
Review comment:
```suggestion
For decimal type, pandas APIs on Spark use Spark's system default precision
and scale.
```
##########
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
Review comment:
```suggestion
>>> ks.Series(["welcome", "to", "pandas-on-Spark"]).spark.data_type
```
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