Teradata Package for Python Function Reference | 20.00 - lpad - 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.lpad = lpad(length, fill_string=' ')
- DESCRIPTION:
Function returns the string value in column padded to the left with the characters
in "fill_string" so that the resulting string has "length" characters.
PARAMETERS:
length:
Required Argument.
Specifies a ColumnExpression of an int column or an integer literal specifying
the number of characters in the resulting string.
Format of a ColumnExpression of a string column: '<dataframe>.<dataframe_column>'.
Supported column types: INTEGER, BIGINT, or NUMBER
Types: ColumnExpression, int
fill_string:
Optional Argument.
Specifies a ColumnExpression of a string column or a string literal
used to pad the source_string.
The sequence of characters in fill_string is replicated as necessary.
Format of a ColumnExpression of a string column: '<dataframe>.<dataframe_column>'.
Supported column types: CHAR, VARCHAR, or CLOB
Default Value: ' '
Types: ColumnExpression, str
RAISES:
TypeError, ValueError, TeradataMlException
RETURNS:
DataFrameColumn
EXAMPLES:
# Load the data to run the example.
>>> load_example_data("dataframe", "admissions_train")
# Create a DataFrame on 'admissions_train' table.
>>> df = DataFrame("admissions_train").iloc[:4]
>>> print(df)
masters gpa stats programming admitted
id
3 no 3.70 Novice Beginner 1
4 yes 3.50 Beginner Novice 1
2 yes 3.76 Beginner Beginner 0
1 yes 3.95 Beginner Beginner 0
# Example 1: Pad string in "stats" column with 0 and pass it as input to DataFrame.assign().
>>> res = df.assign(col = df.stats.lpad(10, "0"))
>>> print(res)
masters gpa stats programming admitted col
id
3 no 3.70 Novice Beginner 1 0000Novice
4 yes 3.50 Beginner Novice 1 00Beginner
2 yes 3.76 Beginner Beginner 0 00Beginner
1 yes 3.95 Beginner Beginner 0 00Beginner
# Example 2: Pad string in "stats" column with strings from "masters" column and pass it
# as input to DataFrame.assign().
>>> res = df.assign(col = df.stats.lpad(20, df.masters))
>>> print(res)
masters gpa stats programming admitted col
id
3 no 3.70 Novice Beginner 1 nononononononoNovice
4 yes 3.50 Beginner Novice 1 yesyesyesyesBeginner
2 yes 3.76 Beginner Beginner 0 yesyesyesyesBeginner
1 yes 3.95 Beginner Beginner 0 yesyesyesyesBeginner