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Shopping cart analysis is a data-only technique that retailers use to better understand shoppers and increase sales. Shopping cart analysis is a powerful tool for retailers because it allows them to understand the purchasing behavior of customers and create strategies to increase sales and customer loyalty.

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Shelly74/Analysis-of-shopping-cart-Data

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Analysis Of Shopping Cart Data

This project seeks to apply Data Analysis skills to a shopping cart dataset and draw several cruicial insights from it.

There are several deductions and analyses that can be drawn from this data which includes the following:

  1. Which products were sold the most in the last month?

  2. How have sales and revenue changed over the past few quarters?

  3. Understanding Customer demographics and their preferences**

Installation

Kindly take note of the following libaries and models below:

  
import warnings
warnings.filterwarnings("ignore")

IMPORT THE FOLLOWING LIBRARIES:

import pandas as pd
import numpy as np
import seaborn as sns
from scipy import stats
from matplotlib import pylab as plt
from statsmodels.graphics.gofplots import qqplot
from IPython.core.interactiveshell import InteractiveShell

STEPS TAKEN IN THIS PROJECT:

  1. Data Collection
  2. Data Preprocessing
  3. Exploratory Data Analysis (EDA)
  4. Feature Engineering
  5. Getting insight from the data

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Shopping cart analysis is a data-only technique that retailers use to better understand shoppers and increase sales. Shopping cart analysis is a powerful tool for retailers because it allows them to understand the purchasing behavior of customers and create strategies to increase sales and customer loyalty.

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