| | |
- nvp(instring, name_to_search, name_delimiters, value_delimiters, occurrence)
- 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:
instring:
Required Argument.
Specifies a ColumnExpression of a string column or a string literal
containing the name-value pairs separated by multi-byte delimiters..
Format of a ColumnExpression of a string column: '<dataframe>.<dataframe_column>.expression'.
name_to_search:
Required Argument.
Specifies a ColumnExpression of a string column or a string literal
whose instring value NVP returns.
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.
The default value is & (ampersand).
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.
The default value is = (equal sign).
occurrence:
Optional Argument.
Specifies the number of occurrences of name_to_search that NVP searches for.
The default value is 1.
NOTE:
Function accepts positional arguments only.
EXAMPLES:
# Load the data to run the example.
>>> load_example_data("dataframe", "employee_info")
>>>
# Create a DataFrame on 'employee_info' table.
>>> employee_info = DataFrame("employee_info")
>>> employee_info
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
>>>
# Import func from sqlalchemy to execute nvp function.
>>> from sqlalchemy import func
# Create a sqlalchemy Function object.
# Retrieve nvp value for string literal "entree:orange chicken#entree2:honey salmon"
# and return a new teradataml DataFrame by adding retrieved nvp value as a column
# to admission_train
>>> nvp_func_ = func.NVP('entree:orange chicken#entree2:honey salmon', 'entree','#', ':', 1)
>>>
# Pass the Function object as input to DataFrame.assign().
>>> df = employee_info.assign(nvp_literal_=nvp_func_)
>>> print(df)
first_name marks dob joined_date nvp_literal_
employee_no
101 abcde None None 02/12/05 orange chicken
100 abcd None None None orange chicken
112 None None None 18/12/05 orange chicken
>>>
|