  # numpy.atleast_1d () in Python

Arrays | NumPy | Python Methods and Functions

`numpy.atleast_1d()` is used when we want to convert the input to arrays with at least one dimension. Scalar inputs are converted to one-dimensional arrays, while larger inputs are preserved.

Syntax: numpy.atleast_1d (* arrays)

Parameters:
arrays1, arrays2,…: [array_like] One or more input arrays.

Return: [ndarray] An array, or list of arrays, each with a.ndim & gt; = 1. Copies are made only if necessary.

Code # 1: Work

Output:

` Input number: 10 output 1d array from input number:  `

Code # 2: Work

 ` # Python program explaining ` ` # numpy.atleast_1d () function `   ` import ` ` numpy as geek ` ` in_num ` ` = ` ` 10 ` ` `  ` print ` ` (` `" Input number: "` `, in_num) ` ` `    ` out_arr ` ` = ` ` geek.atleast_1d (in_num) ` ` print ` ` (` ` "output 1d array from input number:" ` `, out_arr) `
 ` # Python program explaining ` ` # numpy.atleast_1d () function ` ` `  ` import ` ` numpy as geek `   ` my_list ` ` = ` ` [[` ` 2 ` `, ` ` 6 ` `, ` ` 10 ` `], ` ` [` ` 8 ` `, ` ` 12 ` `, ` ` 16 ` `]] `   ` print ` ` (` ` "Input list:" ` `, my_list) `   ` out_arr ` ` = geek.atleast_1d (my_list) `` print ( "output array:" , out_arr) `

Output:

` Input list: [[2, 6, 10], [8, 12 , 16]] output array: [[2 6 10] [8 12 16]] `

Code # 3: Work

 ` # Python program explaining ` ` # numpy.atleast_1d () function ` ` # when inputs are in high dimension `   ` import ` ` numpy as geek `   ` in_arr ` ` = ` ` geek.arange ( 9 ). reshape ( 3 , 3 ) `` print ( "Input array:" , in_arr)   out_arr = geek.atleast_1d (in_arr) print ( "output array:" , out_arr) print (in_arr is out_arr) `

Output:

` IInput array: [[ 0 1 2] [3 4 5] [6 7 8]] output array: [[0 1 2] [3 4 5] [6 7 8]] True` `