cube() | DataFrame Manipulation | Teradata Package for Python - cube() Function - Teradata Package for Python

Teradata® Package for Python User Guide

Deployment
VantageCloud
VantageCore
Edition
Enterprise
IntelliFlex
VMware
Product
Teradata Package for Python
Release Number
20.00
Published
March 2024
Language
English (United States)
Last Update
2024-04-09
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Product Category
Teradata Vantage

Use the cube() function to create a multidimensional cube for a teradataml 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.cube(["masters", "stats"]).sum()
>>> df1
  masters     stats  sum_id  sum_gpa  sum_admitted
0      no  Beginner       8     3.60             1
1    None  Advanced     555    84.21            16
2    None  Beginner      21    18.31             3
3     yes  Beginner      13    14.71             2
4    None      None     820   141.67            26
5     yes  Advanced     366    49.26             7
6      no      None     343    63.96            16
7    None    Novice     244    39.15             7
8      no  Advanced     189    34.95             9
9     yes    Novice      98    13.74             1