Walmart Sales Analysis Project

This project analyzes weekly sales data from Walmart stores to uncover key insights and relationships between variables. The following key areas were addressed:

• Investigate sales performance across various stores over the years.
• Examining the influence of temperature and fuel prices on sales.
• Performing hypothesis testing to assess the impact of promotional campaigns on sales.
• Visualizing trends in sales and other relevant factors to make informed conclusions.

Dataset Description

The Walmart dataset contains the following columns:

Column Name	Description
Store	Identifier for the store.
Date	Date of the weekly sales data.
Weekly_Sales	Total weekly sales for each store.
Temperature	Temperature at the store's location during the week.
Fuel_Price	Fuel price in the region of the store.
CPI	Consumer Price Index (CPI) for the store's region.
Unemployment	Unemployment rate in the region where the store is located.
Holiday_Flag	Indicator (1 if a special holiday occurred during the week, 0 otherwise).

Key Analyses and Results

1. Sales Performance by Store and Year:

   • Significant variations in weekly sales across different stores and years.
   • Some stores showed a consistent increase in sales year-over-year, while others fluctuated.

2. Impact of Temperature on Sales:

   • Weak correlation between temperature and sales, indicating limited influence.
   • Sales appeared relatively stable across various temperature ranges.

3. Hypothesis Testing on Promotional Impact:

   • The t-test revealed a statistically significant difference in sales before and after the promotion.
   • Promotional campaigns led to a noticeable increase in sales for most stores.

4. Relationship Between Fuel Prices and Sales:

   • Sales fluctuated slightly with changes in fuel prices, though no strong correlation was observed.
   • Higher fuel prices did not significantly dampen sales, suggesting consumer resilience.