This repository contains Jupyter notebooks with solutions for analyzing a dataset about a retail network that sells various products in several cities across the USA. The notebooks provide solutions for 10 business questions derived from the dataset.
The dataset contains information about sales transactions, including the products sold, sales values, order dates, cities, states, and segments.
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City with Highest Sales Value of 'Office Supplies' Category: Identify the city with the highest sales value of products in the 'Office Supplies' category.
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Total Sales by Order Date: Calculate the total sales for each order date and visualize the results using a bar chart.
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Total Sales by State: Determine the total sales for each state and visualize the results using a bar chart.
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Top 10 Cities with Highest Total Sales: Identify the top 10 cities with the highest total sales and visualize the results using a bar chart.
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Segment with Highest Total Sales: Determine which segment had the highest total sales and visualize the results using a pie chart.
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Total Sales by Segment and Year: Calculate the total sales for each segment and year.
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Number of Sales Eligible for 15% Discount: Simulate sales eligible for a 15% discount based on specified criteria.
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Average Sales Value Before and After 15% Discount: Calculate the average sales value before and after applying a 15% discount.
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Average Sales by Segment, Year, and Month: Calculate the average sales for each segment, year, and month and visualize the results using a line chart.
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Total Sales by Category and Subcategory (Top 12): Determine the total sales for each category and subcategory, considering only the top 12 subcategories, and visualize the results using a single chart.
To explore the solutions for the business questions, navigate to the respective Jupyter notebook files in this repository. Each notebook provides code implementations and visualizations for answering the corresponding question.