Teradata Package for Python Function Reference on VantageCloud Lake - concat - 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 on VantageCloud Lake
- Deployment
- VantageCloud
- Edition
- Lake
- 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_Lake_2000
- Product Category
- Teradata Vantage
- teradataml.dataframe.sql.DataFrameColumn.concat = concat(self, separator, *columns)
- DESCRIPTION:
Function to concatenate the columns with a separator.
PARAMETERS:
separator:
Required Argument.
Specifies the string to be used as a separator between two concatenated columns.
Note:
This argument is ignored when no column is specified.
Types: str
columns:
Optional Argument.
Specifies the name(s) of the columns or ColumnExpression(s) to concat on.
Types: str OR ColumnExpression OR ColumnExpressions
Returns:
ColumnExpression
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
>>>
# Example 1: Concatenate the columns "stats" and "programming" with out any seperator.
>>> df = admissions_train.assign(concat_gpa_=admissions_train.stats.concat("", admissions_train.programming))
>>> print(df)
masters gpa stats programming admitted new_column
id
34 yes 3.85 Advanced Beginner 0 AdvancedBeginner
32 yes 3.46 Advanced Beginner 0 AdvancedBeginner
11 no 3.13 Advanced Advanced 1 AdvancedAdvanced
40 yes 3.95 Novice Beginner 0 NoviceBeginner
38 yes 2.65 Advanced Beginner 1 AdvancedBeginner
36 no 3.00 Advanced Novice 0 AdvancedNovice
7 yes 2.33 Novice Novice 1 NoviceNovice
26 yes 3.57 Advanced Advanced 1 AdvancedAdvanced
19 yes 1.98 Advanced Advanced 0 AdvancedAdvanced
13 no 4.00 Advanced Novice 1 AdvancedNovice
>>>
# Example 2: Concatenate the columns "programming", "gpa" and "masters" with '_'.
>>> df = admissions_train.assign(new_column=admissions_train.programming.concat("_", admissions_train.gpa, "masters"))
>>> print(df)
masters gpa stats programming admitted new_column
id
34 yes 3.85 Advanced Beginner 0 Beginner_ 3.85000000000000E 000_yes
32 yes 3.46 Advanced Beginner 0 Beginner_ 3.46000000000000E 000_yes
11 no 3.13 Advanced Advanced 1 Advanced_ 3.13000000000000E 000_no
40 yes 3.95 Novice Beginner 0 Beginner_ 3.95000000000000E 000_yes
38 yes 2.65 Advanced Beginner 1 Beginner_ 2.65000000000000E 000_yes
36 no 3.00 Advanced Novice 0 Novice_ 3.00000000000000E 000_no
7 yes 2.33 Novice Novice 1 Novice_ 2.33000000000000E 000_yes
26 yes 3.57 Advanced Advanced 1 Advanced_ 3.57000000000000E 000_yes
19 yes 1.98 Advanced Advanced 0 Advanced_ 1.98000000000000E 000_yes
13 no 4.00 Advanced Novice 1 Novice_ 4.00000000000000E 000_no