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- StrApply(data=None, target_columns=None, output_columns=None, accumulate=None, string_operation=None, operating_side=None, in_place=True, string=None, escape_string=None, is_case_specific=True, ignore_trailing_blank=False, string_length=None, start_index=None, **generic_arguments)
- DESCRIPTION:
StrApply() function applies a specified string operator to the specified input DataFrame columns.
PARAMETERS:
data:
Required Argument.
Specifies the input teradataml DataFrame.
Types: teradataml DataFrame
target_columns:
Required Argument.
Specifies the name(s) of the column(s) in "data"
to perform string operations on.
Types: str OR list of Strings (str)
output_columns:
Optional Argument.
Specifies the output column names that contains the output of the
string operation on the columns values.
Types: str OR list Strings (str)
accumulate:
Optional Argument.
Specifies the names of input teradataml DataFrame columns to copy to
the output.
Types: str OR list of Strings (str)
string_operation:
Required Argument.
Specifies the string method to use on the target columns.
Permitted Values:
* TOUPPER
* TOLOWER
* strTRIM
* strCON
* strPAD
* strLIKE
* strINDEX
* INITCAP
* TRIMSPACES
* CHARTOHEXINT
* strREVERSE
* SUBstr
* GETNCHARS
* UNICODEstr
Types: str
operating_side:
Optional Argument.
Specifies the operating side to consider while performing operations
like 'stringPad', 'getNchars'.
Permitted Values: LEFT, RIGHT
Default Value: LEFT
Types: str
in_place:
Optional Argument.
Specifies whether to use the same column name for the resulted target
columns.
Default Value: True
Types: bool
string:
Optional Argument.
Specifies the names of the strings to use as input while applying
string operation.
Types: str OR list of Strings (str)
escape_string:
Optional Argument.
Specifies the names of the string to use as an escape string while
applying stringLike operation.
Types: str OR list of Strings (str)
is_case_specific:
Optional Argument.
Specifies whether to consider uppercase letters(e.g. "A") and lowercase
letters(e.g. "a") as same or different.
Default Value: True
Types: bool
ignore_trailing_blank:
Optional Argument.
Specifies whether to ignore trailing blanks in the column strings. Used
if the stringOperation is 'StringLike' only.
Default Value: False
Types: bool
string_length:
Optional Argument.
Specifies the length of a string.
Types: int
start_index:
Optional Argument.
Specifies the start index of the target column string. Used only if
the string operation is 'SubString'.
Types: int
**generic_arguments:
Specifies the generic keyword arguments SQLE functions accept.
Below are the generic keyword arguments:
persist:
Optional Argument.
Specifies whether to persist the results of the function in table or not.
When set to True, results are persisted in table; otherwise, results
are garbage collected at the end of the session.
Default Value: False
Types: boolean
volatile:
Optional Argument.
Specifies whether to put the results of the function in volatile table or not.
When set to True, results are stored in volatile table, otherwise not.
Default Value: False
Types: boolean
Function allows the user to partition, hash, order or local order the input
data. These generic arguments are available for each argument that accepts
teradataml DataFrame as input and can be accessed as:
* "<input_data_arg_name>_partition_column" accepts str or list of str (Strings)
* "<input_data_arg_name>_hash_column" accepts str or list of str (Strings)
* "<input_data_arg_name>_order_column" accepts str or list of str (Strings)
* "local_order_<input_data_arg_name>" accepts boolean
Note:
These generic arguments are supported by teradataml if the underlying SQLE Engine
function supports it, else an exception is raised.
RETURNS:
Instance of StrApply.
Output teradataml DataFrames can be accessed using attribute
references, such as StrApplyObj.<attribute_name>.
Output teradataml DataFrame attribute name is:
result
RAISES:
TeradataMlException, TypeError, ValueError
EXAMPLES:
# Notes:
# 1. Get the connection to Vantage, before importing the function in user space.
# 2. User can import the function, if it is available on the Vantage user is connected to.
# 3. To check the list of analytic functions available on the Vantage user connected to,
# use "display_analytic_functions()"
# Load the example data.
load_example_data("teradataml", ["titanic"])
# Create teradataml DataFrame object.
titanic_data = DataFrame.from_table("titanic")
# Check the list of available analytic functions.
display_analytic_functions()
# Import function StrApply.
from teradataml import StrApply
# Example 1: Apply 'TOUPPER' string operator to the
# specified input "name" columns.
obj = StrApply(data=titanic_data,
target_columns='name',
string_operation='TOUPPER',
in_place=False)
# Print the result DataFrame.
print(obj.result)
# Example 2: Apply StrApply using all the arguments.
obj = StrApply(data=titanic_view,
data_partition_column='age',
data_order_column='age',
target_columns='name',
accumulate='PASSENGER',
output_columns='str_op_output',
string_operation='TOUPPER',
in_place=False,
persist=True)
# Print the result DataFrame.
print(obj.result)
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