Use the rollup() function to create a multidimensional rollup for a DataFrame using specified columns, and there by running aggregates on it produce the aggregations on different dimensions.
Required Argument:
- columns: Specifies the names of input teradataml DataFrame columns.
Example Setup
In this example, "admission_train" dataset is used.
>>> from teradataml import *
>>> load_example_data("dataframe", "admissions_train")
>>> df = DataFrame("admissions_train")
Example 1: Analyzes the data by grouping into masters and stats dimensions
>>> df1 = df.rollup(["masters", "stats"]).sum()
>>> df1 masters stats sum_id sum_gpa sum_admitted 0 no None 343 63.96 16 1 yes None 477 77.71 10 2 None None 820 141.67 26 3 no Novice 146 25.41 6 4 no Beginner 8 3.60 1 5 yes Novice 98 13.74 1 6 yes Beginner 13 14.71 2 7 yes Advanced 366 49.26 7 8 no Advanced 189 34.95 9