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- ConvertTo(data=None, target_columns=None, target_datatype=None, **generic_arguments)
- DESCRIPTION:
The ConvertTo() function converts the specified input DataFrame columns to
specified data types.
PARAMETERS:
data:
Required Argument.
Specifies the input teradataml DataFrame.
Types: teradataml DataFrame
target_columns:
Required Argument.
Specifies the input teradataml DataFrame columns which needs to be
casted/converted to another data type.
Types: str OR list of Strings (str)
target_datatype:
Required Argument.
Specify target data type(s) into which "target_columns" need to be
converted. If one value is provided, it applies to all "target_columns".
If more than one value is specified, each "target_datatype" value applies to
corresponding "target_columns" value (in the order specified by the user).
Types: str OR list of strs
**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 ConvertTo.
Output teradataml DataFrames can be accessed using attribute
references, such as ConvertToObj.<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 ConvertTo
from teradataml import ConvertTo
# Example: Convert datatype of 'fare' to integer.
obj = ConvertTo(data=titanic_data,
target_columns="fare", target_datatype="integer"
)
# Print the result DataFrame.
print(obj.result)
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