Numpy : array

 #numpy basic array

import numpy as np

a=np.array([0,1,2,3,4])

type(a)#numpy.ndarray

a.dtype

a.size#5

a.ndim#dimension in the array here one

b=np.array([3.1,4.4,3.6,4.8])

type(b)

b.dtype#float64

#indexing and slicing in arrays

a=np.array([21,23,43,12,5,34,31])

a[0]=100

print(a) #[100 23 12 5 34 31]

b=a[0:4]

print(b) #[100 23 43 12]

#vector addition and subtraction

u=np.array([0,1])

v=np.array([1,0])

z=u+v

print(z)

#aternate method

a=[]

for n,m in zip(u,v):

    a.append(n+m)

print(a)

    #multiplication of numpy array

u=np.array([2,3])

v=np.array([5,6])

z=[]

for n,m in zip(u,v):

    z.append(n*m)

print(z)

#Dot product(a*c+b*d)

d=np.dot(u,v)

print(d) #28

#universal function

x=np.array([3,4,5,2,5])

a=x.mean()

print(a)

x.max()

np.pi #value of pi

c=np.array([0,np.pi/2,np.pi])

y=np.sin(c)

print(y)

np.linspace(-2,2, num=5)#[-2 -1 0 1 2]

z=np.linspace(0,2*np.pi,100)

k=np.sin(z)

print(k)

import matplotlib.pyplot as plt

%matplotlib inline

plt.plot(z,k)

import time

import sys

import numpy as np

A=np.array