itertuples() | teradataml | Teradata - itertuples() Method - 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 itertuples() method to iterate over teradataml DataFrame rows as namedtuples.

Optional Arguments:
  • name: Specifies the name of the returned namedtuples.

    When set to None, the method returns the row in a list instead of namedtuple.

    The default value is 'Row'.

  • num_rows: Specifies the number of rows to retrieve from the DataFrame.

    When set to None, the method retrieves all the records. This is the default value.

This method returns iterator, an object to iterate over namedtuples for each row in the DataFrame.

Example 1: Retrieve all records from a teradataml DataFrame

>>> df = DataFrame("titanic")
>>> rows = df.itertuples()
>>> next(rows)
Row(passenger=78, survived=0, pclass=3, name='Moutal Mr. Rahamin Haim', gender='male', age=None, sibsp=0, parch=0, ticket='374746', fare=8.05, cabin=None, embarked='S')
>>> next(rows)
Row(passenger=93, survived=0, pclass=1, name='Chaffee Mr. Herbert Fuller', gender='male', age=46, sibsp=1, parch=0, ticket='W.E.P. 5734', fare=61.175, cabin='E31', embarked='S')
>>> next(rows)
Row(passenger=5, survived=0, pclass=3, name='Allen Mr. William Henry', gender='male', age=35, sibsp=0, parch=0, ticket='373450', fare=8.05, cabin=None, embarked='S')

Example 2: Retrieve the first 20 records from a teradataml DataFrame in a list, when DataFrame is ordered

This example retrieves the first 20 records from a teradataml DataFrame in a list, when the DataFrame is ordered by column "passenger".

>>> df = DataFrame("titanic")
>>> rows = df.sort("passenger").itertuples(name=None, num_rows=20)
>>> next(rows)
[1, 0, 3, 'Braund, Mr. Owen Harris', 'male', 22, 1, 0, 'A/5 21171', 7.25, None, 'S']
>>> next(rows)
[2, 1, 1, 'Cumings, Mrs. John Bradley (Florence Briggs Thayer)', 'female', 38, 1, 0, 'PC 17599', 71.2833, 'C85', 'C']
>>> next(rows)
[3, 1, 3, 'Heikkinen, Miss. Laina', 'female', 26, 0, 0, 'STON/O2. 3101282', 7.925, None, 'S']