Exploratory Data Analysis on Superstore Data

Jul 10, 2024

Exploratory Data Analysis on Superstore Data

Presenter: John

Program: July 2024, Sparx Foundation

Objective

  • Find areas where the company could have made more profit
  • Identify weak areas of performance

Data Sets Used

  1. Original data set
  2. Product loss data set
  3. Location loss data set

Key Findings

Regions Analysis

  • Southern and Central regions had lower profits and quantities compared to other regions.

Location Loss Analysis

  • Eastern Region: 11 states with negative profits
  • Southern Region: 7 states with negative profits
  • Western Region: 7 states with negative profits
  • Central Region: 5 states with negative profits (accounted for over 35% of losses)
    • Texas had the highest loss (36.81k)

Product and Returns Analysis

  • Furniture category did not perform well compared to other categories.
  • Blenders (under Office Supply) had the highest loss.
  • Technology had the greatest overall loss.

Discount Analysis

  • Most discounts were around zero.
  • Few discounts were close to 0.8.
  • Negative correlation between profit and discount: as one increases, the other decreases.

Dashboard

  • Summarizes all findings in a visual format.
  • Highlights key areas of concern and potential improvement.

Conclusion

  • Identified weak regions and product categories.
  • Observed significant loss patterns related to discounts.

Thank you Presenter: John