Let’s see how to calculate the difference between the maximum and the minimum values of a given NumPy array along the second axis. Here, the Second axis means row-wise.
So firstly for finding the row-wise maximum and minimum elements in a NumPy array we are using numpy.amax() and numpy.amin() functions of NumPy library respectively. then After that we simply perform subtraction on it.
numpy.amax(): This function returns maximum of an array or maximum along axis(if mentioned).
Syntax: numpy.amax(arr, axis = None, out = None, keepdims = )
numpy.amin(): This function returns minimum of an array or minimum along axis(if mentioned).
Syntax: numpy.amin(arr, axis = None, out = None, keepdims = )
Now, Let’s see an example:
Example 1:
Python3
# import library import numpy as np # create a numpy 2d-array x = np.array([[100, 20, 305], [ 200, 40, 300]]) print("given array:\n", x) # get maximum element row # wise from numpy array max1 = np.amax(x ,1) # get minimum element row # wise from numpy array min1 = np.amin(x, 1) # print the row-wise max # and min difference print("difference:\n", max1 - min1) |
Output:
given array: [[100 20 305] [200 40 300]] difference: [285 260]
Example 2:
Python3
# import library import numpy as np # list x = [12, 13, 14, 15, 16] y = [17, 18, 19, 20, 21] # create a numpy 2d-array array = np.array([x, y]).reshape((2, 5)) print("original array:\n", array) # find max and min elements # row-wise max1, min1 = np.amax(array, 1), np.amin(array,1) # print the row-wise max # and min difference print("Difference:\n", max1 - min1) |
Output:
original array: [[12 13 14 15 16] [17 18 19 20 21]] Difference: [4 4]
