accuracy_of_data

%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
plt.rcParams ['figure.figsize'] = (20.0,10.0)

#for popularirty
print("WELCOME_TO_BIT_MESRA_PHYSICS_LAB")
print("Created by SHIVAM KUMAR ECE K19 batch")

#collecting X and Y
n = int(input("Enter number of elements : "))  
X = list(map(float,input("\nEnter the X-co ordinates : ").strip().split()))[:n] 
print("\nValues of X are - ", X)

Y = list(map(float,input("\nEnter the Y-co ordinates: ").strip().split()))[:n] 
print("\nValues of Y are - ", Y)

#Mean X and Y
mean_x = np.mean(X)
mean_y = np.mean(Y)

# Total no. of values
m = len(X)

#Using the formula to calculate b1 and b2
numer = 0
denom = 0
for i in range(m):
    numer +=(X[i] - mean_x) * (Y[i] - mean_y)
    denom +=(X[i] - mean_x) **2
b1 = numer / denom
b0 = mean_y - (b1 * mean_x)

#print coefficient
print(b1,b0)
    
#plotting values and regression line

max_x = np.max(X) + 100
min_x = np.min(X) - 100

#Calculating line values x and y
x = np.linspace(min_x, max_x, 1000)
y = b0 + b1 * x

#plotting Line
plt.plot(x, y ,color='#58b970', label='Regression Line')
#Plotting scatter points
plt.scatter(X, Y, c='#ef5423', label='Scatter plot')

#title of graph
s1=str(input("Enter the title: "))
plt.title(s1.upper(), color='r')

x2=str(input("Enter the name of X-axis: "))
plt.xlabel(x2)
y2=str(input("Enter the name of Y-axis: "))
plt.ylabel(y2)
plt.legend()
plt.show()