Teradata Package for Python Function Reference | 20.00 - floordiv - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference - 20.00
- Deployment
- VantageCloud
- VantageCore
- Edition
- Enterprise
- IntelliFlex
- VMware
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Enterprise_2000
- lifecycle
- latest
- Product Category
- Teradata Vantage
- teradataml.dataframe.sql.DataFrameColumn.floordiv = floordiv(self, other)
- Compute the floor-division between two ColumnExpressions.
PARAMETRS:
other:
Required Argument.
Specifies Python literal or another ColumnExpression.
Types: ColumnExpression, Python literal
RETURNS:
ColumnExpression
EXAMPLES:
>>> load_example_data("burst", "finance_data")
>>> df = DataFrame("finance_data")
>>> df
start_time_column end_time_column expenditure income investment
id
1 67/06/30 07/07/10 415.0 451.0 180.0
4 67/06/30 07/07/10 448.0 493.0 192.0
2 67/06/30 07/07/10 421.0 465.0 179.0
3 67/06/30 07/07/10 434.0 485.0 185.0
5 67/06/30 07/07/10 459.0 509.0 211.0
# Example 1: Calculate the percent of investment of income and assign the
# final amount to new column 'percentage_investment'.
>>> df.assign(percentage_investment=(df.investment.mul(100)).floordiv(df.income))
start_time_column end_time_column expenditure income investment percentage_investment
id
3 67/06/30 07/07/10 434.0 485.0 185.0 38.144330
2 67/06/30 07/07/10 421.0 465.0 179.0 38.494624
1 67/06/30 07/07/10 415.0 451.0 180.0 39.911308
5 67/06/30 07/07/10 459.0 509.0 211.0 41.453831
4 67/06/30 07/07/10 448.0 493.0 192.0 38.945233
# Example 2: Filter out the rows after diving income amount by 2 is less than 240.
>>> df[(df.income.floordiv(2)) < 240]
start_time_column end_time_column expenditure income investment
id
2 67/06/30 07/07/10 421.0 465.0 179.0
1 67/06/30 07/07/10 415.0 451.0 180.0