Explain NumPy array object

Explain NumPy array object

import numpy as np

# Manual construction of arrays

# one dimension array
a = np.array([0,1,2,3])
print(a)

print ('dimension', a.ndim)

print('shape', a.shape)

print('length', len(a))

print('Datatype', a.dtype)

# Functions for creating arrays
# Evenly spaced
a = np.arange(10)
print('0,1,2,.....n-1', a)

b = np.arange(1, 9, 2)
print('start 1, end 9(exclusive), step 2', b)

# number of points
a = np.linspace(0, 1, 6)
print('start, end, num-points', a)

a = np.linspace(0, 1, 5, endpoint=True)
print('start, end, num-points, endpoint = false', a)

# Common arrays:
a = np.ones((3, 3))  # reminder: (3, 3) is a tuple
b = np.zeros((2, 2))
c = np.eye(3)
d = np.diag(np.array([1, 2, 3, 4]))

a = np.random.rand(4)       # uniform in [0, 1]
b = np.random.randn(4)      # Gaussian
np.random.seed(1234)        # Setting the random seed 


# Indexing and slicing
a = np.arange(10)
print('Reverse', a[::-1])

print('Slicing', a[2:9:3]) # [start:end:step] Arrays, like other Python sequences can also be sliced

Source: http://www.scipy-lectures.org/intro/numpy/array_object.html