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- ConvertTo(data=None, target_columns=None, target_datatype=None, accumulate=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 a different data type.
Types: str OR list of Strings (str)
target_datatype:
Required Argument.
Specifies 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 Strings (str)
accumulate:
Optional Argument.
Specifies the name(s) of input teradataml DataFrame column(s) to
copy to the output. By default, the function copies all input teradataml
DataFrame columns to the output.
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 a table or not. When set to True,
results are persisted in a table; otherwise,
results are garbage collected at the end of the
session.
Default Value: False
Types: bool
volatile:
Optional Argument.
Specifies whether to put the results of the
function in a volatile table or not. When set to
True, results are stored in a volatile table,
otherwise not.
Default Value: False
Types: bool
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 SQL 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 to execute the function.
# 2. One must import the required functions mentioned in
# the example from teradataml.
# 3. Function will raise error if not supported on the Vantage
# user is connected to.
# Load the example data.
load_example_data("teradataml", ["titanic"])
# Create teradataml DataFrame object.
titanic = DataFrame.from_table("titanic")
# Check the list of available analytic functions.
display_analytic_functions()
# Example 1 : Convert datatype of 'fare' to integer.
ConvertTo_out = ConvertTo(data = titanic,
target_columns = ["fare"],
target_datatype = ["integer"],
accumulate=['passenger', 'name', 'ticket']
)
# Print the result DataFrame.
print(ConvertTo_out.result)
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