nxcals.api.extraction.data.builders.DataFrame.agg

DataFrame.agg(*exprs: Union[Column, Dict[str, str]]) → DataFrame

Aggregate on the entire DataFrame without groups (shorthand for df.groupBy().agg()).

New in version 1.3.0.

Changed in version 3.4.0: Supports Spark Connect.

Parameters:

exprs (Column or dict of key and value strings) – Columns or expressions to aggregate DataFrame by.

Returns:

Aggregated DataFrame.

Return type:

DataFrame

Examples

>>> from pyspark.sql import functions as sf
>>> df = spark.createDataFrame([(2, "Alice"), (5, "Bob")], schema=["age", "name"])
>>> df.agg({"age": "max"}).show()
+--------+
|max(age)|
+--------+
|       5|
+--------+
>>> df.agg(sf.min(df.age)).show()
+--------+
|min(age)|
+--------+
|       2|
+--------+