snowflake.snowpark.DataFrame.agg¶
- DataFrame.agg(*exprs: Column | Tuple[ColumnOrName, str] | Dict[str, str]) DataFrame [source]¶
Aggregate the data in the DataFrame. Use this method if you don’t need to group the data (
group_by()
).- Parameters:
exprs –
A variable length arguments list where every element is
A Column object
A tuple where the first element is a column object or a column name and the second element is the name of the aggregate function
A list of the above
or a
dict
maps column names to aggregate function names.
Examples:
>>> from snowflake.snowpark.functions import col, stddev, stddev_pop >>> df = session.create_dataframe([[1, 2], [3, 4], [1, 4]], schema=["A", "B"]) >>> df.agg(stddev(col("a"))).show() ---------------------- |"STDDEV(A)" | ---------------------- |1.1547003940416753 | ---------------------- >>> df.agg(stddev(col("a")), stddev_pop(col("a"))).show() ------------------------------------------- |"STDDEV(A)" |"STDDEV_POP(A)" | ------------------------------------------- |1.1547003940416753 |0.9428091005076267 | ------------------------------------------- >>> df.agg(("a", "min"), ("b", "max")).show() ----------------------- |"MIN(A)" |"MAX(B)" | ----------------------- |1 |4 | ----------------------- >>> df.agg({"a": "count", "b": "sum"}).show() ------------------------- |"COUNT(A)" |"SUM(B)" | ------------------------- |3 |10 | -------------------------
Note
The name of the aggregate function to compute must be a valid Snowflake aggregate function.