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- nullifzero(column_expression_or_constant)
- DESCRIPTION:
Function converts data from zero to null to avoid problems with division by zero.
PARAMETERS:
column_expression_or_constant:
Required Argument.
Specifies a ColumnExpression of a numeric column or a constant value to be converted to null.
Format for the argument: '<dataframe>.<dataframe_column>.expression'.
Notes:
1. If the type of the column/argument is not FLOAT, column values are converted to FLOAT
based on implicit type conversion rules. If an argument cannot be converted, an
error is reported. For more information on implicit type conversion,
see Teradata Vantage™ Data Types and Literals, B035-1143.
2. Unsupported column types:
a. BYTE or VARBYTE
b. LOBs (BLOB or CLOB)
c. CHARACTER or VARCHAR if the server character set is GRAPHIC
NOTE:
Function accepts positional arguments only.
EXAMPLES:
# Load the data to run the example.
>>> load_example_data("dataframe", "admissions_train")
>>>
# Create a DataFrame on 'admissions_train' table.
>>> admissions_train = DataFrame("admissions_train")
>>> admissions_train
masters gpa stats programming admitted
id
22 yes 3.46 Novice Beginner 0
36 no 3.00 Advanced Novice 0
15 yes 4.00 Advanced Advanced 1
38 yes 2.65 Advanced Beginner 1
5 no 3.44 Novice Novice 0
17 no 3.83 Advanced Advanced 1
34 yes 3.85 Advanced Beginner 0
13 no 4.00 Advanced Novice 1
26 yes 3.57 Advanced Advanced 1
19 yes 1.98 Advanced Advanced 0
>>>
# Import func from sqlalchemy to execute nullifzero() function.
>>> from sqlalchemy import func
# Use case of NULLIFZERO() function - Function can be used, when we are dividing by a column that
# may contain 0, so that we can avoid errors coming from expressions such as:
# 8 / 0
# Note:
# In this example, we have combined teradataml ColumnExpression and SQLAlchemy func object
# admissions_train.gpa -- Is a teradataml ColumnExpression
# func.nullifzero(admissions_train.admitted.expression) -- Is SQLAlchemy func object
>>> df = admissions_train.assign(admitted_null_if_zero = func.nullifzero(admissions_train.admitted.expression))
>>> print(df)
masters gpa stats programming admitted admitted_null_if_zero
id
22 yes 3.46 Novice Beginner 0 NaN
36 no 3.00 Advanced Novice 0 NaN
15 yes 4.00 Advanced Advanced 1 1.0
38 yes 2.65 Advanced Beginner 1 1.0
5 no 3.44 Novice Novice 0 NaN
17 no 3.83 Advanced Advanced 1 1.0
34 yes 3.85 Advanced Beginner 0 NaN
13 no 4.00 Advanced Novice 1 1.0
26 yes 3.57 Advanced Advanced 1 1.0
19 yes 1.98 Advanced Advanced 0 NaN
>>>
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