How to produce a scatter graph and label the axis

import matplotlib.pyplot as plt

plt. scatter(x, y)

plt. xlabel(‘label name’, fontsize = 20)

plt. ylabel(‘label name’, fontsize = 20)

plt. show()

Adding a regression line and seeing its summary (regression table)

import statsmodels.api

x1 = sm.add_constant(x)

result = sm.OLS(y, x1).fit()

result.summary()

Seaborn

This is a library based off matplotlib that can produce better data visualisations - they look a lot better

import seaborn as sns

sns.set()

Analysing the regression table - coefficient table

Constant represents the y intercept

The number below this represents the gradient

These can be used to determine the equation of the regression line so it can be plotted

R - squared

A measure of how close the data is fitted to the regression line

It is a value between 0 and 1 and the closer to one the better