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- GetRowsWithMissingValues(data=None, target_columns=None, accumulate=None, **generic_arguments)
- DESCRIPTION:
The GetRowsWithMissingValues() function displays the rows that have
NULL values in the specified input data columns.
Notes:
* This function requires the UTF8 client character set for
UNICODE data.
* This function does not support Pass Through Characters (PTCs).
For information about PTCs, see Teradata Vantage™ -
Analytics Database International Character Set Support.
* This function does not support KanjiSJIS or Graphic data types.
PARAMETERS:
data:
Required Argument.
Specifies the input teradataml DataFrame.
Types: teradataml DataFrame
target_columns:
Optional Argument.
Specifies the name(s) of the column(s) in "data", in which NULL value should be checked.
By default, all columns of the input teradataml DataFrame are considered as target.
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.
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: boolean
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 volatile a 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 function supports it, else an exception is raised.
RETURNS:
Instance of GetRowsWithMissingValues.
Output teradataml DataFrames can be accessed using attribute
references, such as GetRowsWithMissingValuesObj.<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_data = DataFrame.from_table("titanic")
# Check the list of available analytic functions.
display_analytic_functions()
# Example 1: Get the rows that contain NULL values in columns
# 'name', 'sex', 'age', 'passenger'.
obj = GetRowsWithMissingValues(data=titanic_data,
target_columns=['name', 'sex', 'age', 'passenger'])
# Print the result DataFrame.
print(obj.result)
# Example 2: Get the rows that contain NULL values in columns
# 'name', 'sex', 'age', 'passenger' by specifying
# input teradataml dataframe columns to copy to the
# output.
obj1 = GetRowsWithMissingValues(data=titanic_data,
target_columns=['name', 'sex', 'age', 'passenger'],
accumulate=["survived", "pclass"])
# Print the result DataFrame.
print(obj1.result)
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