sort() Method - Teradata Python Package

Use the sort() method to sort data on one or more columns in either ascending or descending order for a teradataml DataFrame.

The method takes a column name or a list of column names to sort on. Use the ascending parameter to specified ascending or descending order. True for ascending order and False for descending order.

Examples Prerequisite

>>> df = DataFrame("admissions_train")

Example: Sort in ascending order

This example sorts in ascending order on the column "id" of "admissions_train":

>>> 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

Example: Sort in descending order

This example sorts in descending order on the column "id" of "admissions_train":

>>> df.sort("id", ascending=False)
   masters   gpa     stats programming admitted
id
40     yes  3.95    novice    beginner        0
39     yes  3.75  advanced    beginner        0
38     yes  2.65  advanced    beginner        1
37      no  3.52    novice      novice        1
36      no  3.00  advanced      novice        0
35      no  3.68    novice    beginner        1
34     yes  3.85  advanced    beginner        0
33      no  3.55    novice      novice        1
32     yes  3.46  advanced    beginner        0
31     yes  3.50  advanced    beginner        1

Example: Sort in ascending order on multiple columns

This example sorts in ascending order on the columns "masters" and "gpa":

>>> display.max_row = 20

>>> 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
3       no  3.70    novice    beginner        1
16      no  3.70  advanced    advanced        1
10      no  3.71  advanced    advanced        1
9       no  3.82  advanced    advanced        1
17      no  3.83  advanced    advanced        1
21      no  3.87    novice    beginner        1
28      no  3.93  advanced    advanced        1
25      no  3.96  advanced    advanced        1
13      no  4.00  advanced      novice        1
19     yes  1.98  advanced    advanced        0
7      yes  2.33    novice      novice        1