pyspark.sql.GroupedData.min¶
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GroupedData.min(*cols: str) → pyspark.sql.dataframe.DataFrame[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| +--------+-----------+