Teradata Package for Python Function Reference on VantageCloud Lake - nvp - 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
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.dataframe.sql.DataFrameColumn.nvp = nvp(name_to_search, name_delimiters='&', value_delimiters='=', occurrence=1)
- DESCRIPTION:
Function extracts the value of a name-value pair where the name in the pair matches
the name and the number of the "occurrence" specified.
PARAMETERS:
name_to_search:
Required Argument.
Specifies a ColumnExpression of a string column or a string literal
whose instring value NVP returns.
Types: ColumnExpression, str
name_delimiters:
Optional Argument.
Specifies the multi-byte delimiters used to separate name-value pairs.
Delimiters can contain any characters. They are separated from each
other in the string by spaces. If a space is used as part of a delimiter,
it must be escaped using a backslash (\). The maximum length of any
delimiter is 10, and the maximum size of this parameter is 32.
Default value: '&' (ampersand).
Types: str
value_delimiters:
Optional Argument.
Specifies the multi-byte delimiters used to associate a name to its value in a
name-value pair.
Delimiters can contain any characters. They are separated from each other in the
string by spaces. If a space is used as part of a delimiter, it must be escaped
using a backslash (\). The maximum length of any delimiter is 10, and the
maximum size of this parameter is 32.
Default value: '=' (equal sign).
Types: str
occurrence:
Optional Argument.
Specifies the number of occurrences of name_to_search that NVP searches for.
Default value: 1.
Types: int
RAISES:
TypeError, ValueError, TeradataMlException
RETURNS:
DataFrameColumn
EXAMPLES:
# Load the data to run the example.
>>> load_example_data("dataframe", "employee_info")
# Create a DataFrame on 'employee_info' table.
>>> df = DataFrame("employee_info")
>>> print(df)
first_name marks dob joined_date
employee_no
101 abcde None None 02/12/05
100 abcd None None None
112 None None None 18/12/05
# Create a column 'nvp_col' for specifying string literal 'entree:orange chicken#entree2:honey salmon'
>>> df = df.assign(nvp_col = 'entree:orange chicken#entree2:honey salmon')
>>> print(df)
first_name marks dob joined_date nvp_literal_ nvp_col
employee_no
112 None None None 18/12/05 orange chicken entree:orange chicken#entree2:honey salmon
100 abcd None None None orange chicken entree:orange chicken#entree2:honey salmon
101 abcde None None 02/12/05 orange chicken entree:orange chicken#entree2:honey salmon
# Example 1: Retrieve nvp value for "nvp_col" and pass it as input to DataFrame.assign().
>>> res = df.assign(col= df.nvp_col.nvp('entree','#', ':', 1))
>>> print(res)
first_name marks dob joined_date nvp_col col
employee_no
112 None None None 18/12/05 entree:orange chicken#entree2:honey salmon orange chicken
100 abcd None None None entree:orange chicken#entree2:honey salmon orange chicken
101 abcde None None 02/12/05 entree:orange chicken#entree2:honey salmon orange chicken
# Example 2: Executed nvp() function on "nvp_col" column and filtered computed
# values which are equal to 'orange chicken'.
>>> print(df[df.nvp_col.nvp('entree','#', ':', 1) == "orange chicken"])
first_name marks dob joined_date nvp_col
employee_no
100 abcd None None None entree:orange chicken#entree2:honey salmon
101 abcde None None 02/12/05 entree:orange chicken#entree2:honey salmon
112 None None None 18/12/05 entree:orange chicken#entree2:honey salmon