import numpy as np

np.array([5,7,8])

seqArr01 = np.arange(start=5, stop=10) print(seqArr01)

seqArr02 = np.arange(start=5, stop=20, step=2) print(seqArr02)

zeroArr = np.zeros(5) # creates an array with 5 "zeros" print(zeroArr)

onesArr = np.ones(3) # aray with 3 "ones" print(onesArr)

eightArr = np.ones(10) * 8 # first creates a 10 ones array; and them multiplies all values by 8 eightArr

np.array([[1,2,3],[4,5,6],[7,8,9]])

array1D = np.arange(9) array1D

matrix2D = array1D.reshape(3,3) matrix2D

np.random.rand(3) # 3 random numbers between 0 and 1

np.random.randint(low=10,high=20,size=(10,10)) # 100 integers between 10 and 20 (excluding 20) stored in a matrix 10 by 10

np.random.randn(4) # 4 values from a standard normal distribution

np.linspace(start=10,stop=20,num=100) # array with length = 100 with equally spaced values between 10 and 20

arr1 = np.arange(10) arr2 = np.ones(10)*2 arr3 = arr1 + arr2 arr4 = arr1 / arr2 print(arr1) print(arr2) print(arr3) print(arr4)

# Mean arr4.mean()

# Sum arr4.sum()

# standard deviation arr4.std()

# min arr4.min()

# max arr4.max()