squeeze() Method | Teradata Python Package - 17.00 - squeeze() Method - Teradata Package for Python

Teradata® Package for Python User Guide

Product
Teradata Package for Python
Release Number
17.00
Release Date
November 2021
Content Type
User Guide
Publication ID
B700-4006-070K
Language
English (United States)

Use the squeeze() method to squeeze one-dimensional axis objects into a scalar for teradataml DataFrames with a single element, or a Series object for a teradataml DataFrame with a single column.

The teradataml DataFrame is returned unchanged when both dimensions are greater than one.

Arguments:

The axis argument specifies the axis along which the squeeze operation is to be attempted. The possible values are:
  • 1 or 'columns': Return Series object if number of columns equals one.
  • 0 or 'index' : Return the unchanged teradataml DataFrame object.
When axis is not specified and both dimensions equal one, a scalar object is returned which is the only element in the DataFrame.

Examples Prerequisite

Assume the table "admissions_train" exists and its index column is id. And a DataFrame "df" is created based on this table using the command:

>>> df = DataFrame("admissions_train")
>>> df
   masters   gpa     stats programming admitted
id
22     yes  3.46    Novice    Beginner        0
36      no  3.00  Advanced      Novice        0
15     yes  4.00  Advanced    Advanced        1
38     yes  2.65  Advanced    Beginner        1
5       no  3.44    Novice      Novice        0
17      no  3.83  Advanced    Advanced        1
34     yes  3.85  Advanced    Beginner        0
13      no  4.00  Advanced      Novice        1
26     yes  3.57  Advanced    Advanced        1
19     yes  1.98  Advanced    Advanced        0

Example 1: Squeeze a teradataml DataFrame with both dimension greater than one.

>>> df.squeeze()
   masters   gpa     stats programming admitted
id
22     yes  3.46    Novice    Beginner        0
36      no  3.00  Advanced      Novice        0
15     yes  4.00  Advanced    Advanced        1
38     yes  2.65  Advanced    Beginner        1
5       no  3.44    Novice      Novice        0
17      no  3.83  Advanced    Advanced        1
34     yes  3.85  Advanced    Beginner        0
13      no  4.00  Advanced      Novice        1
26     yes  3.57  Advanced    Advanced        1
19     yes  1.98  Advanced    Advanced        0

Example 2: Squeeze a single-column teradataml DataFrame.

>>> gpa = df.select(["gpa"])
>>> gpa.squeeze()
0    4.00
1    2.33
2    3.46
3    3.83
4    4.00
5    2.65
6    3.57
7    3.44
8    3.85
9    3.95
Name: gpa, dtype: float64
>>> gpa.squeeze(axis = 1)
0    3.46
1    3.00
2    4.00
3    2.65
4    3.44
5    3.83
6    3.85
7    4.00
8    3.57
9    1.98
Name: gpa, dtype: float64

>>> gpa.squeeze(axis = 0)
    gpa
0  3.46
1  3.00
2  4.00
3  2.65
4  3.44
5  3.83
6  3.85
7  4.00
8  3.57
9  1.98

Example 3: Squeeze a teradataml DataFrame with multiple columns and a single row.

>>> df = DataFrame.from_query('select gpa, stats from admissions_train where gpa=2.33')

>>> df
    gpa   stats
0  2.33  Novice
>>> s = df.squeeze()
>>> s
    gpa   stats
0  2.33  Novice

Example 4: Squeeze a teradataml DataFrame with a single element.

>>> single_gpa = DataFrame.from_query('select gpa from admissions_train where gpa=2.33')
>>> single_gpa
    gpa
0  2.33
>>> single_gpa.squeeze()
2.33
>>> single_gpa.squeeze(axis = 1)
0    2.33
Name: gpa, dtype: float64
>>> single_gpa.squeeze(axis = 0)
    gpa
0  2.33