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How to get the minimum and maximum value of a given NumPy array along the second axis?
• Last Updated : 02 Sep, 2020

Let’s see How to get the minimum and maximum value of a given NumPy array along the second axis. Here, the Second axis means row-wise.

We are using  numpy.amax() and numpy.amin() function of NumPy to get the minimum and maximum values of an array along the second axis respectively.

numpy.amax(): This function returns maximum of an array or maximum along axis(if mentioned).

Syntax: numpy.amax(a, axis=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)

numpy.amin(): This function returns minimum of an array or minimum along axis(if mentioned).

Syntax: numpy.amin(a, axis=None, out=None, keepdims=<no value>, initial=<no value>, where=<no value>)

Now, Let’s see an example:

Example 1:

## Python3

 `# Import numpy library``import` `numpy as np`` ` `# Create a numpy array``arr ``=` `np.array([[``0``, ``1``],``                ``[``2``, ``3``]])`` ` `print``(``"Given Array:\n"``,``     ``arr)`` ` `# find row-wise max values ``rslt1 ``=` `np.amax(arr, ``1``)``print``(``"\nMaximum Value:"``,``      ``rslt1)`` ` `# find row-wise min values``rslt2 ``=` `np.amin(arr, ``1``)``print``(``"\nMinimum Value:"``,``      ``rslt2)`

Output:

```Given Array:
[[0 1]
[2 3]]

Maximum Value: [1 3]

Minimum Value: [0 2]```

Example 2:

## Python3

 `# Import numpy library``import` `numpy as np`` ` `# Create a numpy array``arr ``=` `np.array([[``10``, ``34``, ``45``],``                ``[``22``, ``-``3``, ``46``], ``                ``[``33``, ``4``, ``6``]])`` ` `print``(``"Given array:\n"``,``     ``arr)`` ` `# find row-wise max values ``rslt1 ``=` `np.amax(arr, ``1``)``print``(``"\nMaximum value along the second axis:"``,``      ``rslt1)`` ` `# find row-wise min values ``rslt2 ``=` `np.amin(arr, ``1``)``print``(``"\nMinimum value along the second axis:"``,``     ``rslt2)`

Output:

```Given array:
[[10 34 45]
[22 -3 46]
[33  4  6]]

Maximum value: [45 46 33]

Minimum value: [10 -3  4]```

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