min
Returns the minimum value of the expression in a group.
Syntax
Python
from pyspark.sql import functions as sf
sf.min(col)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| The target column on which the minimum value is computed. |
Returns
pyspark.sql.Column: A column that contains the minimum value computed.
Examples
Example 1: Compute the minimum value of a numeric column
Python
import pyspark.sql.functions as sf
df = spark.range(10)
df.select(sf.min(df.id)).show()
Output
+-------+
|min(id)|
+-------+
| 0|
+-------+
Example 2: Compute the minimum value of a string column
Python
import pyspark.sql.functions as sf
df = spark.createDataFrame([("Alice",), ("Bob",), ("Charlie",)], ["name"])
df.select(sf.min("name")).show()
Output
+---------+
|min(name)|
+---------+
| Alice|
+---------+
Example 3: Compute the minimum value of a column with null values
Python
import pyspark.sql.functions as sf
df = spark.createDataFrame([(1,), (None,), (3,)], ["value"])
df.select(sf.min("value")).show()
Output
+----------+
|min(value)|
+----------+
| 1|
+----------+
Example 4: Compute the minimum value of a column in a grouped DataFrame
Python
import pyspark.sql.functions as sf
df = spark.createDataFrame([("Alice", 1), ("Alice", 2), ("Bob", 3)], ["name", "value"])
df.groupBy("name").agg(sf.min("value")).show()
Output
+-----+----------+
| name|min(value)|
+-----+----------+
|Alice| 1|
| Bob| 3|
+-----+----------+
Example 5: Compute the minimum value of a column in a DataFrame with multiple columns
Python
import pyspark.sql.functions as sf
df = spark.createDataFrame(
[("Alice", 1, 100), ("Bob", 2, 200), ("Charlie", 3, 300)],
["name", "value1", "value2"])
df.select(sf.min("value1"), sf.min("value2")).show()
Output
+-----------+-----------+
|min(value1)|min(value2)|
+-----------+-----------+
| 1| 100|
+-----------+-----------+