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new b2aa17ca5afd [SPARK-45985][PYTHON][DOCS] Refine docstring of
`DataFrame.intersect`
b2aa17ca5afd is described below
commit b2aa17ca5afd6ab1d5e47b0e1722193465684f36
Author: Hyukjin Kwon <gurwls...@apache.org>
AuthorDate: Sat Nov 18 10:16:02 2023 -0800
[SPARK-45985][PYTHON][DOCS] Refine docstring of `DataFrame.intersect`
### What changes were proposed in this pull request?
This PR proposes to improve the docstring of `DataFrame.intersect`.
### Why are the changes needed?
For end users, and better usability of PySpark.
### Does this PR introduce _any_ user-facing change?
Yes, it fixes the user facing documentation.
### How was this patch tested?
Manually tested.
### Was this patch authored or co-authored using generative AI tooling?
No.
Closes #43884 from HyukjinKwon/SPARK-45985.
Authored-by: Hyukjin Kwon <gurwls...@apache.org>
Signed-off-by: Dongjoon Hyun <dh...@apple.com>
---
python/pyspark/sql/dataframe.py | 31 +++++++++++++++++++++++++++++--
1 file changed, 29 insertions(+), 2 deletions(-)
diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py
index 8d7c7d70a501..01067bd4c482 100644
--- a/python/pyspark/sql/dataframe.py
+++ b/python/pyspark/sql/dataframe.py
@@ -4755,14 +4755,41 @@ class DataFrame(PandasMapOpsMixin,
PandasConversionMixin):
Examples
--------
+ Example 1: Intersecting two DataFrames with the same schema
+
>>> df1 = spark.createDataFrame([("a", 1), ("a", 1), ("b", 3), ("c",
4)], ["C1", "C2"])
>>> df2 = spark.createDataFrame([("a", 1), ("a", 1), ("b", 3)], ["C1",
"C2"])
- >>> df1.intersect(df2).sort(df1.C1.desc()).show()
+ >>> result_df = df1.intersect(df2).sort("C1", "C2")
+ >>> result_df.show()
+---+---+
| C1| C2|
+---+---+
- | b| 3|
| a| 1|
+ | b| 3|
+ +---+---+
+
+ Example 2: Intersecting two DataFrames with different schemas
+
+ >>> df1 = spark.createDataFrame([(1, "A"), (2, "B")], ["id", "value"])
+ >>> df2 = spark.createDataFrame([(2, "B"), (3, "C")], ["id", "value"])
+ >>> result_df = df1.intersect(df2).sort("id", "value")
+ >>> result_df.show()
+ +---+-----+
+ | id|value|
+ +---+-----+
+ | 2| B|
+ +---+-----+
+
+ Example 3: Intersecting all rows from two DataFrames with mismatched
columns
+
+ >>> df1 = spark.createDataFrame([(1, 2), (1, 2), (3, 4)], ["A", "B"])
+ >>> df2 = spark.createDataFrame([(1, 2), (1, 2)], ["C", "D"])
+ >>> result_df = df1.intersect(df2).sort("A", "B")
+ >>> result_df.show()
+ +---+---+
+ | A| B|
+ +---+---+
+ | 1| 2|
+---+---+
"""
return DataFrame(self._jdf.intersect(other._jdf), self.sparkSession)
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