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- Pack(data=None, input_columns=None, output_column=None, delimiter=',', include_column_name=True, col_cast=False, accumulate=None, **generic_arguments)
- DESCRIPTION:
The Pack() function packs data from multiple input DataFrame columns into a single column.
PARAMETERS:
data:
Required Argument.
Specifies the input teradataml DataFrame.
Types: teradataml DataFrame
input_columns:
Optional Argument.
Specifies the names of the input columns to pack into a single output
column. These names become the column names of the virtual columns.
By default, all input teradataml DataFrame columns are packed into a
single output column. If you specify this argument, but do not
specify all input teradataml DataFrame columns, the function copies
the unspecified input tablecolumns to the output table.
Types: str OR list of Strings (str)
output_column:
Required Argument.
Specifies the name to give to the packed output column.
Types: str
delimiter:
Optional Argument.
Specifies the delimiter (a string) that separates the virtual columns
in the packed data.
Default Value: ","
Types: str
include_column_name:
Optional Argument.
Specifies whether to label each virtual column value with its column
name (making the virtual column "input_column:value").
Default Value: True
Types: bool
col_cast:
Optional Argument.
Specifies whether to get better elapsed times with use cases involving numeric
columns to be packed.
Default Value: False
Types: bool
accumulate:
Optional Argument.
Specifies the input teradataml DataFrame columns to copy to the
output table. By default, the function copies no input teradataml
DataFrame columns to the output table.
Types: str OR list of Strings (str)
**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, else an exception is raised.
RETURNS:
Instance of Pack.
Output teradataml DataFrames can be accessed using attribute
references, such as PackObj.<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("pack", ["ville_temperature"])
# Create teradataml DataFrame object.
ville_temperature = DataFrame.from_table("ville_temperature")
# Check the list of available analytic functions.
display_analytic_functions()
# Import function Pack.
from teradataml import Pack
# Example 1: Packs data from multiple input DataFrame columns
# into a single column.
obj = Pack(data=ville_temperature,
input_columns=['city','state','period','temp_f'],
output_column='packed_data',
delimiter=',',
accumulate='city',
include_column_name=True)
# Print the result DataFrame.
print(obj.result)
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