Use the get() function to retrieve required columns from a teradataml DataFrame.
The function takes a key representing a column name as an argument and returns a new DataFrame with the the appropriate columns. The key can be a single column name or a list of column names.
Multicolumn retrieval of the same column such as df.get(['col1', 'col1']) is not supported.
Examples Prerequisite
Assume a teradataml DataFrame is created based on the table "admissions_train".
>>> df = DataFrame("admissions_train")
>>> df
masters gpa stats programming admitted
id
5 no 3.44 novice novice 0
7 yes 2.33 novice novice 1
22 yes 3.46 novice beginner 0
17 no 3.83 advanced advanced 1
13 no 4.00 advanced novice 1
19 yes 1.98 advanced advanced 0
36 no 3.00 advanced novice 0
15 yes 4.00 advanced advanced 1
34 yes 3.85 advanced beginner 0
40 yes 3.95 novice beginner 0
Example 1: Retrieve a single column
This example retrieves a single column "id" from the table "admissions_train". Column "id" is the index column.
>>>df.get("id")
Empty DataFrame
Columns: []
Index: [22, 34, 13, 19, 15, 38, 26, 5, 36, 17]
Example 2: Retrieve multiple columns using a list of columns names
Use a list of columns names for multicolumn retrieval.
>>>df.get(["id", "masters", "gpa"])
masters gpa
id
5 no 3.44
36 no 3.00
15 yes 4.00
17 no 3.83
13 no 4.00
40 yes 3.95
7 yes 2.33
22 yes 3.46
34 yes 3.85
19 yes 1.98
Example 3: Retrieve multiple columns using a list of list of columns names
Use a list of list of columns names for multicolumn retrieval.
>>> df.get([['id', 'masters', 'gpa']])
masters gpa
id
5 no 3.44
34 yes 3.85
13 no 4.00
40 yes 3.95
22 yes 3.46
19 yes 1.98
36 no 3.00
15 yes 4.00
7 yes 2.33
17 no 3.83