Teradata Package for Python Function Reference on VantageCloud Lake - make_interval - 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 on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.11
- Published
- August 2026
- ft:locale
- en-US
- ft:lastEdition
- 2026-08-13
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.dataframe.functions.make_interval = make_interval(years=None, months=None, weeks=None, days=None, hours=None, minutes=None, seconds=None)
- DESCRIPTION:
Returns the interval based on the provided fields.
Notes:
* Combinations of year and month fields with day and time fields are not supported.
* At least one argument must be provided in order to create interval type.
PARAMETERS:
years:
Optional Argument.
Specifies number of years.
Types: int, float, ColumnExpression
months:
Optional Argument.
Specifies number of months.
Types: int, float, ColumnExpression
weeks:
Optional Argument.
Specifies number of weeks.
Types: int, float, ColumnExpression
days:
Optional Argument.
Specifies number of days.
Types: int, float, ColumnExpression
hours:
Optional Argument.
Specifies number of hours.
Types: int, float, ColumnExpression
minutes:
Optional Argument.
Specifies number of minutes.
Types: int, float, ColumnExpression
seconds:
Optional Argument.
Specifies number of seconds (fractional seconds allowed).
Types: int, float, ColumnExpression
RETURNS:
ColumnExpression
RAISES:
TeradataMlException
EXAMPLES:
# Load the data to run the example.
>>> load_example_data("teradataml", "make_interval_data")
# Create a DataFrame on 'make_interval_data' table.
>>> df = DataFrame("make_interval_data")
>>> df
months weeks days hours minutes seconds
years
5 0 0 0 0 0 0.000
1 2 0 10 5 30 20.500
0 0 0 7 23 59 59.999
0 6 2 0 12 0 0.000
# Example 1: Create YEAR TO MONTH interval with the values provided in 'years' and 'months' columns.
>>> from teradataml.dataframe.functions import make_interval
>>> res = df.assign(iv_ym = make_interval(years=df.year, months=df.month))
>>> res
months weeks days hours minutes seconds iv_ym
years
0 6 2 0 12 0 0.000 0-06
0 0 0 7 23 59 59.999 0-00
1 2 0 10 5 30 20.500 1-02
5 0 0 0 0 0 0.000 5-00
>>> res.tdtypes
years INTEGER()
months INTEGER()
weeks INTEGER()
days INTEGER()
hours INTEGER()
minutes INTEGER()
seconds FLOAT()
iv_ym INTERVAL_YEAR_TO_MONTH()
# Example 2: Creating YEAR interval with a constant value.
>>> res = df.assign(iv_year = make_interval(years=2))
>>> res
months weeks days hours minutes seconds iv_year
years
5 0 0 0 0 0 0.000 2-00
1 2 0 10 5 30 20.500 2-00
0 0 0 7 23 59 59.999 2-00
0 6 2 0 12 0 0.000 2-00
>>> res.tdtypes
years INTEGER()
months INTEGER()
weeks INTEGER()
days INTEGER()
hours INTEGER()
minutes INTEGER()
seconds FLOAT()
iv_year INTERVAL_YEAR()
# Example 4: Create DAY TO SECOND interval with the values provided in 'weeks', 'days',
# 'hours', 'minutes' and 'seconds' columns.
>>> res = df.assign(iv_d2s = make_interval(weeks=df.weeks, days=df.days, hours=df.hours,
... minutes=df.minutes, seconds=df.seconds))
>>> res
months weeks days hours minutes seconds iv_d2s
years
5 0 0 0 0 0 0.000 0 00:00:00.000000
1 2 0 10 5 30 20.500 10 05:30:20.500000
0 0 0 7 23 59 59.999 7 23:59:59.999000
0 6 2 0 12 0 0.000 14 12:00:00.000000
>>> res.tdtypes
years INTEGER()
months INTEGER()
weeks INTEGER()
days INTEGER()
hours INTEGER()
minutes INTEGER()
seconds FLOAT()
iv_d2s INTERVAL_DAY_TO_SECOND()