Execute Basic Numpy operations
import numpy as np
print(‘numpy version’, np.__version__)
print(np.zeros(10, dtype='int'))
print(np.ones((3,5), dtype=float))
print(np.full((3,5),1.23))
print('arange]n',np.arange(0, 21, 3))
print(np.linspace(0, 1, 5))
print(np.random.normal(0, 1, (3,3)))
print(np.eye(3))
print(np.random.seed(0))
x1 = np.random.randint(10, size=6) #one dimension
x2 = np.random.randint(10, size=(3,4)) #two dimension
x3 = np.random.randint(10, size=(3,4,5)) #three dimension
print(‘1d array’, x1)
print(‘2d array’, x2)
print(‘3d array’, x3)
print("x3 ndim:", x3.ndim)
print("x3 shape:", x3.shape)
print("x3 size: ", x3.size)
x = np.where(x1 == 4)
print('Find the indexes where the value is 4:',x)
print('after sorting array x1 ',np.sort(x1))
for i in x1:
print(i)
arr = np.concatenate((x2, x2), axis=1)
print('After concatenating x2 and x2 arrays vertically', arr)
newarr = np.array_split(arr, 3, axis=1)
print(newarr)
print('first element',x1[0], 'last element', x1[5])
print(x1[-2])
print(x2[2,-1])
newarr = x1.reshape(2,3)
print(newarr)
print(x1[:5])
print(x1[1:5])
print(x1[::2])
print( x1[::-1])
arr = np.array([1, 2, 3, 4, 5])
x = arr.copy()
arr[0] = 42
print(arr)
print(x)
arr = np.array([1, 2, 3, 4, 5])
x = arr.view()
arr[0] = 42
print(arr)
print(x)
arr = np.array([41, 42, 43, 44])
x = [True, False, True, False]
newarr = arr[x]
print(newarr)
print(x)
arr = np.array([41, 42, 43, 44])
x = [True, False, True, False]
newarr = arr[x]
print(newarr)
Algorithm
Result