pyspark.sql.GroupedData.min#

GroupedData.min(*cols)[source]#

Computes the min value for each numeric column for each group.

New in version 1.3.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters

colsstr: column names. Non-numeric columns are ignored.

Examples

>>> df = spark.createDataFrame([
...     (2, "Alice", 80), (3, "Alice", 100),
...     (5, "Bob", 120), (10, "Bob", 140)], ["age", "name", "height"])
>>> df.show()
+---+-----+------+
|age| name|height|
+---+-----+------+
|  2|Alice|    80|
|  3|Alice|   100|
|  5|  Bob|   120|
| 10|  Bob|   140|
+---+-----+------+

Group-by name, and calculate the min of the age in each group.

>>> df.groupBy("name").min("age").sort("name").show()
+-----+--------+
| name|min(age)|
+-----+--------+
|Alice|       2|
|  Bob|       5|
+-----+--------+

Calculate the min of the age and height in all data.

>>> df.groupBy().min("age", "height").show()
+--------+-----------+
|min(age)|min(height)|
+--------+-----------+
|       2|         80|
+--------+-----------+