Teradata Package for Python Function Reference | 17.10 - sort - Teradata Package for Python
Teradata® Package for Python Function Reference
- Product
- Teradata Package for Python
- Release Number
- 17.10
- Published
- April 2022
- Language
- English (United States)
- Last Update
- 2022-08-19
- Product Category
- Teradata Vantage
- teradataml.dataframe.dataframe.DataFrame.sort = sort(self, columns, ascending=True)
- DESCRIPTION:
Get sorted data by one or more columns in either ascending or descending order
for a Dataframe.
Unsupported column types for sorting: ['BLOB', 'CLOB', 'ARRAY', 'VARRAY']
PARAMETERS:
columns:
Required Argument.
Column names as a string or a list of strings to sort on.
Types: str OR list of Strings (str)
ascending:
Optional Argument.
Order ASC or DESC to be applied for each column.
True for ascending order and False for descending order.
Default value: True
Types: bool
RETURNS:
teradataml DataFrame
RAISES:
TeradataMlException
EXAMPLES:
>>> load_example_data("dataframe","admissions_train")
>>> df = DataFrame('admissions_train')
>>> df
masters gpa stats programming admitted
id
22 yes 3.46 Novice Beginner 0
37 no 3.52 Novice Novice 1
35 no 3.68 Novice Beginner 1
12 no 3.65 Novice Novice 1
4 yes 3.50 Beginner Novice 1
38 yes 2.65 Advanced Beginner 1
27 yes 3.96 Advanced Advanced 0
39 yes 3.75 Advanced Beginner 0
7 yes 2.33 Novice Novice 1
40 yes 3.95 Novice Beginner 0
>>> df.sort("id")
masters gpa stats programming admitted
id
1 yes 3.95 Beginner Beginner 0
2 yes 3.76 Beginner Beginner 0
3 no 3.70 Novice Beginner 1
4 yes 3.50 Beginner Novice 1
5 no 3.44 Novice Novice 0
6 yes 3.50 Beginner Advanced 1
7 yes 2.33 Novice Novice 1
8 no 3.60 Beginner Advanced 1
9 no 3.82 Advanced Advanced 1
10 no 3.71 Advanced Advanced 1
>>> df.sort(["id"])
masters gpa stats programming admitted
id
1 yes 3.95 Beginner Beginner 0
2 yes 3.76 Beginner Beginner 0
3 no 3.70 Novice Beginner 1
4 yes 3.50 Beginner Novice 1
5 no 3.44 Novice Novice 0
6 yes 3.50 Beginner Advanced 1
7 yes 2.33 Novice Novice 1
8 no 3.60 Beginner Advanced 1
9 no 3.82 Advanced Advanced 1
10 no 3.71 Advanced Advanced 1
>>> df.sort(["masters","gpa"])
masters gpa stats programming admitted
id
24 no 1.87 Advanced Novice 1
36 no 3.00 Advanced Novice 0
11 no 3.13 Advanced Advanced 1
5 no 3.44 Novice Novice 0
37 no 3.52 Novice Novice 1
33 no 3.55 Novice Novice 1
8 no 3.60 Beginner Advanced 1
12 no 3.65 Novice Novice 1
35 no 3.68 Novice Beginner 1
16 no 3.70 Advanced Advanced 1
>>> # In next example, sort dataframe with masters column in Ascending ('True')
>>> # order and gpa column with Descending (False)
>>> df.sort(["masters","gpa"], ascending=[True,False])
masters gpa stats programming admitted
id
13 no 4.00 Advanced Novice 1
25 no 3.96 Advanced Advanced 1
28 no 3.93 Advanced Advanced 1
21 no 3.87 Novice Beginner 1
17 no 3.83 Advanced Advanced 1
9 no 3.82 Advanced Advanced 1
10 no 3.71 Advanced Advanced 1
3 no 3.70 Novice Beginner 1
16 no 3.70 Advanced Advanced 1
35 no 3.68 Novice Beginner 1
>>>