# numpy.atleast_1d() in Python

`numpy.atleast_1d()`function is used when we want to Convert inputs to arrays with at least one dimension. Scalar inputs are converted to 1-dimensional arrays, whilst higher-dimensional 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 >= 1. Copies are made only if necessary.

Code #1 : Working

 `# 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)  `

Output :

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

Code #2 : Working

 `# 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 : Working

 `# 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 :\n "``, in_arr) ` ` `  `out_arr ``=` `geek.atleast_1d(in_arr) ` `print` `(``"output  array :\n "``, 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'
```

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