# numpy.vander() function | Python

`numpy.vander() ` function is used to generate a Vandermonde matrix.

Syntax : numpy.vander(arr, N = None, increasing = False)
Parameters :
arr : [ array_like] 1-D input array.
N : [int, optional] Number of columns in the output. If N is not specified, a square array is returned (N = len(x)).
increasing : [bool, optional] Order of the powers of the columns. If True, the powers increase from left to right, if False (the default) they are reversed.
Return : [ndarray] dVandermonde matrix. If increasing is False, the first column is x^(N-1), the second x^(N-2) and so forth. If increasing is True, the columns are x^0, x^1, …, x^(N-1).

Code #1 :

 `# Python program explaining ` `# numpy.vander() function ` ` `  `# importing numpy as geek  ` `import` `numpy as geek ` ` `  `arr ``=` `geek.array([``1``, ``2``, ``3``, ``4``, ``5``]) ` ` `  `gfg ``=` `geek.vander(arr) ` ` `  `print` `(gfg) `

Output :

```[[  1   1   1   1   1]
[ 16   8   4   2   1]
[ 81  27   9   3   1]
[256  64  16   4   1]
[625 125  25   5   1]]
```

Code #2 :

 `# Python program explaining ` `# numpy.vander() function ` ` `  `# importing numpy as geek  ` `import` `numpy as geek ` ` `  `arr ``=` `geek.array([``1``, ``2``, ``3``, ``4``, ``5``]) ` `N ``=` `3` ` `  `gfg ``=` `geek.vander(arr, N) ` ` `  `print` `(gfg) `

Output :

```[[ 1  1  1]
[ 4  2  1]
[ 9  3  1]
[16  4  1]
[25  5  1]]
```

Code #3 :

 `# Python program explaining ` `# numpy.vander() function ` ` `  `# importing numpy as geek  ` `import` `numpy as geek ` ` `  `arr ``=` `geek.array([``1``, ``2``, ``3``, ``4``, ``5``]) ` ` `  `gfg ``=` `geek.vander(arr, increasing ``=` `True``) ` ` `  `print` `(gfg) `

Output :

```[[  1   1   1   1   1]
[  1   2   4   8  16]
[  1   3   9  27  81]
[  1   4  16  64 256]
[  1   5  25 125 625]]
```

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