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.
The column used for sorting in sort must have type that supports sorting. Unsupported types include: ‘BLOB’, ‘CLOB’, ‘ARRAY’, ‘VARRAY’.
Examples Prerequisite
Assume a teradataml DataFrame "df" is created from a Vantage table "admissions_train", using command:
>>> df = DataFrame("admissions_train")
Example 1: 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 2: 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 3: 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