Analysis of Black Friday Shopping Trends via Machine Learning
Introduction
Wikipedia defines Black Friday as an informal name for the Friday following Thanksgiving Day in the United States, which is celebrated on the fourth Thursday of November. [Black Friday is] regarded as the beginning of America’s Christmas shopping season […].
In this article, we will try to explore different trends from the Black Friday shopping dataset. We will extract useful information that will answer questions such as: what gender shops more on Black Friday? Do the occupations of the people have any impact on sales? Which age group is the highest spender?
In the end, we will create a simple machine learning algorithm that predicts the amount of money that a person is likely to spend on Black Friday depending on features such as gender, age, and occupation.
The dataset that we will use in this article includes 550,000 observations about Black Friday, which are made in a retail store. The file can be downloaded at the following Kaggle link: Black Friday Case Study.
Data Analysis
The first step is to import the libraries that we will need in this section:
import pandas as pd
import numpy as np
import matplotlib as