tail() Method | DataFrame | Teradata Package for Python - tail() Method - Teradata Package for Python

Use the tail() method to print the last n rows of a DataFrame.

Optional Parameters

n

Specifies the number of rows to select.

Default value: 10

deterministic

Specifies whether to select the last n rows from the sorted DataFrame or not.

• If True, the last n rows of the sorted DataFrame are selected.

  The DataFrame is sorted on the index column or the first column if there is no index column. The column type must support sorting.

  Unsupported types include: 'BLOB', 'CLOB', 'ARRAY', 'VARRAY'.

• If False, a random sample of n rows is selected.

Default value: True.

Example 1: Print default number of rows

The following example prints the default last 10 rows of "admissions_train" sorted by id.

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

Example 2: Print n rows

The following example prints the last 3 rows of "admissions_train":

>>>df.tail(3)
   masters   gpa     stats programming admitted
id
38     yes  2.65  advanced    beginner        1
39     yes  3.75  advanced    beginner        0
40     yes  3.95    novice    beginner        0

The following example prints the last 15 rows of "admissions_train":

>>>df.tail(15)
   masters   gpa     stats programming admitted
id
38     yes  2.65  advanced    beginner        1
36      no  3.00  advanced      novice        0
35      no  3.68    novice    beginner        1
34     yes  3.85  advanced    beginner        0
32     yes  3.46  advanced    beginner        0
31     yes  3.50  advanced    beginner        1
30     yes  3.79  advanced      novice        0
29     yes  4.00    novice    beginner        0
28      no  3.93  advanced    advanced        1
27     yes  3.96  advanced    advanced        0
26     yes  3.57  advanced    advanced        1
33      no  3.55    novice      novice        1
37      no  3.52    novice      novice        1
39     yes  3.75  advanced    beginner        0
40     yes  3.95    novice    beginner        0

Example 3: Print 3 rows of "admissions_train" with deterministic argument set to False

>>> df.tail(3, deterministic=False)
    masters   gpa     stats programming  admitted
id                                              
33      no  3.55    Novice      Novice         1
37      no  3.52    Novice      Novice         1
20     yes  3.90  Advanced    Advanced         1