allisonwang-db commented on code in PR #43685:
URL: https://github.com/apache/spark/pull/43685#discussion_r1384263186
##########
python/pyspark/sql/functions.py:
##########
@@ -1162,15 +1162,48 @@ def count(col: "ColumnOrName") -> Column:
Examples
--------
- Count by all columns (start), and by a column that does not count ``None``.
+ Example 1: Count all rows in a DataFrame
+ >>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([(None,), ("a",), ("b",), ("c",)],
schema=["alphabets"])
- >>> df.select(count(expr("*")), count(df.alphabets)).show()
- +--------+----------------+
- |count(1)|count(alphabets)|
- +--------+----------------+
- | 4| 3|
- +--------+----------------+
+ >>> df.select(sf.count(sf.expr("*"))).show()
+ +--------+
+ |count(1)|
+ +--------+
+ | 4|
+ +--------+
+
+ Example 2: Count non-null values in a specific column
+
+ >>> from pyspark.sql import functions as sf
+ >>> df.select(sf.count(df.alphabets)).show()
+ +----------------+
+ |count(alphabets)|
+ +----------------+
+ | 3|
+ +----------------+
+
+ Example 3: Count all rows in a DataFrame with multiple columns
+
+ >>> from pyspark.sql import functions as sf
+ >>> df = spark.createDataFrame(
+ ... [(1, "apple"), (2, "banana"), (3, None)], schema=["id", "fruit"])
+ >>> df.select(sf.count(sf.expr("*"))).show()
+ +--------+
+ |count(1)|
+ +--------+
+ | 3|
+ +--------+
+
+ Example 4: Count non-null values in multiple columns
+
+ >>> from pyspark.sql import functions as sf
+ >>> df.select(sf.count(df.id), sf.count(df.fruit)).show()
+ +---------+------------+
+ |count(id)|count(fruit)|
+ +---------+------------+
+ | 3| 2|
+ +---------+------------+
Review Comment:
It would be great to include some examples for groupby count.
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