import pandas as pd
import seaborn as sb
from matplotlib import pyplot as plt
path = '../data/insurance.csv'
df = pd.read_csv(path)

Simple Linear Regression

A regression model that estimates the relationship between one independent (predictor/ xs) variable and one dependant (response/ ys) variable

\(y = \alpha + \beta x \)

• \(\beta\) = slope

• \(\alpha\) = y-intercept

• \(y\) = y- coordinate

• \(x\) = x-coordinate

number_columns = df.select_dtypes(include='number').drop('charges', axis=1)
for column in number_columns:
    sb.regplot(x = column, y = "charges", data = df)
    plt.show()