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

data = pd.read_csv('headbrain.csv')
print(data.shape)
data.head()

X = data['Head Size(cm^3)'].values
Y = data['Brain Weight(grams)'].values

#print(X)
print()
#print(Y)

mean_x = np.mean(X)
mean_y = np.mean(Y)

m = len(X)

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(b1, b0)

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

x = np.linspace(min_x, max_x, 1000)
y = b0 + b1 * x

plt.plot(x, y, color='#58b970', label='Regression Line')

plt.scatter(X, Y, c='#ef5423', label='Scatter Plot')

plt.xlabel('Head Size in cm3')
plt.ylabel('Brain Weight in grams')
plt.legend()
plt.show()
