Teradata Package for Python Function Reference | 20.00 - index - 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.index = index(expression)
- DESCRIPTION:
Function returns the position in string values in column where string specified
in the argument starts.
NOTES:
a. If string in argument is not found in string in column, then the result is zero.
b. If string in argument is null, then the result is null.
c. If the arguments are character types, index returns a logical character position,
not a byte position, except when the server character set of the arguments is KANJI1
and the session client character set is KanjiEBCDIC.
PARAMETERS:
expression:
Required Argument.
Specifies a ColumnExpression of a string column or a string literal
which is used as a substring to be searched for its position within the
full string in column.
Format of a ColumnExpression of a string column: '<dataframe>.<dataframe_column>'.
Supported column types are:
1. Character
2. Byte - If value of column is of type BYTE, then "expression" must be of type BYTE.
3. Numeric - If value of column is numeric, then it is converted implicitly to CHARACTER type.
Types: ColumnExpression, str
RAISES:
TypeError, ValueError, TeradataMlException
RETURNS:
DataFrameColumn
EXAMPLES:
# Load the data to execute 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: Returns the start position of "ce" in "stats" column and pass it as input
# to DataFrame.assign().
>>> res = df.assign(col = df.stats.index("ner"))
>>> print(res)
masters gpa stats programming admitted col
id
3 no 3.70 Novice Beginner 1 0
4 yes 3.50 Beginner Novice 1 6
2 yes 3.76 Beginner Beginner 0 6
1 yes 3.95 Beginner Beginner 0 6
# Example 2: Executed index() function on "stats" column and filtered computed
# values which are equal to 0.
>>> print(df[df.stats.index("ner") != 0])
masters gpa stats programming admitted
id
4 yes 3.50 Beginner Novice 1
2 yes 3.76 Beginner Beginner 0
1 yes 3.95 Beginner Beginner 0