Note
Access to this page requires authorization. You can try signing in or changing directories.
Access to this page requires authorization. You can try changing directories.
Computes the max value for each numeric column for each group.
Syntax
max(*cols)
Parameters
| Parameter | Type | Description |
|---|---|---|
cols |
str | Column names. Non-numeric columns are ignored. |
Returns
DataFrame
Examples
df = spark.createDataFrame([
(2, "Alice", 80), (3, "Alice", 100),
(5, "Bob", 120), (10, "Bob", 140)], ["age", "name", "height"])
# Group-by name, and calculate the max of the age in each group.
df.groupBy("name").max("age").sort("name").show()
# +-----+--------+
# | name|max(age)|
# +-----+--------+
# |Alice| 3|
# | Bob| 10|
# +-----+--------+
# Calculate the max of the age and height in all data.
df.groupBy().max("age", "height").show()
# +--------+-----------+
# |max(age)|max(height)|
# +--------+-----------+
# | 10| 140|
# +--------+-----------+