Teradata Package for Python Function Reference | 20.00 - nullifzero - Teradata Package for Python - Look here for syntax, methods and examples for the functions included in the Teradata Package for Python.
Teradata® Package for Python Function Reference - 20.00
- Deployment
- VantageCloud
- VantageCore
- Edition
- Enterprise
- IntelliFlex
- VMware
- Product
- Teradata Package for Python
- Release Number
- 20.00.00.03
- Published
- December 2024
- ft:locale
- en-US
- ft:lastEdition
- 2024-12-19
- dita:id
- TeradataPython_FxRef_Enterprise_2000
- lifecycle
- latest
- Product Category
- Teradata Vantage
- teradataml.dataframe.sql.DataFrameColumn.nullifzero = nullifzero()
- DESCRIPTION:
Function converts the values in column from zero to null to avoid problems with division by zero.
NOTES:
1. If the type of the column is not FLOAT, column values are converted to FLOAT
based on implicit type conversion rules. If the value cannot be converted, an
error is reported. For more information on implicit type conversion,
see Teradata Vantage™ Data Types and Literals.
2. Unsupported column types:
a. BYTE or VARBYTE
b. LOBs (BLOB or CLOB)
c. CHARACTER or VARCHAR if the server character set is GRAPHIC
RAISES:
TypeError, ValueError, TeradataMlException
RETURNS:
DataFrameColumn
EXAMPLES:
# Load the data to execute the example.
>>> load_example_data("dataframe", "admissions_train")
# Create a DataFrame on 'admissions_train' table.
>>> df = DataFrame("admissions_train").iloc[:4]
>>> print(df)
masters gpa stats programming admitted
id
3 no 3.70 Novice Beginner 1
4 yes 3.50 Beginner Novice 1
2 yes 3.76 Beginner Beginner 0
1 yes 3.95 Beginner Beginner 0
# Example 1: Convert 0 values in "admitted" column to null using
# nullifzero() function.
>>> res = df.assign(col = df.admitted.nullifzero())
>>> print(res)
masters gpa stats programming admitted col
id
3 no 3.70 Novice Beginner 1 1.0
4 yes 3.50 Beginner Novice 1 1.0
2 yes 3.76 Beginner Beginner 0 NaN
1 yes 3.95 Beginner Beginner 0 NaN
# Example 2: Executed nullifzero() function on "admitted" column and filtered
# computed values which are None.
>>> print(df[df.admitted.nullifzero() == None])
masters gpa stats programming admitted
id
2 yes 3.76 Beginner Beginner 0
1 yes 3.95 Beginner Beginner 0