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Oriminkowski/womens-clothing-reviews-eda

Women's Clothing E-Commerce Reviews – EDA Project This project explores customer reviews from a women's clothing e-commerce store. The goal was to clean, analyze, and visualize the data to uncover key insights about customer satisfaction and behavior. Dataset Overview Source: Public dataset of women’s clothing reviews Size: 23,486 reviews and 11 features Target variable: Recommended IND Data Cleaning Removed index column Dropped duplicates Handled… See the full description on the dataset page: https://huggingface.co/datasets/Oriminkowski/womens-clothing-reviews-eda.

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Dataset Card

Women's Clothing E-Commerce Reviews – EDA Project

This project explores customer reviews from a women's clothing e-commerce store. The goal was to clean, analyze, and visualize the data to uncover key insights about customer satisfaction and behavior.

Dataset Overview

Source: Public dataset of women’s clothing reviews Size: 23,486 reviews and 11 features Target variable: Recommended IND

Data Cleaning

—Removed index column
—Dropped duplicates
—Handled missing values
—Capped outliers

Descriptive Statistics

The dataset shows that most reviewers are around age 43, and ratings are strongly skewed toward 4–5 stars. A clear trend emerges: higher ratings almost always lead to product recommendations, as shown by the strong correlation (0.79) between Rating and Recommended IND. Other variables such as age and feedback count show very weak correlations, meaning they have little influence on customer satisfaction. Overall, customer ratings are consistently high across departments, with Bottoms, Intimate, and Jackets receiving the best average scores.

Research Questions

Q1: Do higher ratings receive more positive feedback? → Yes — higher ratings get more feedback votes.

Q2: Which department has the highest ratings? → Intimates, Bottoms, and Jackets.

Q3: Does age affect satisfaction? → No significant impact.

Conclusion

Overall satisfaction is high across all departments. Higher ratings are linked with recommendations and positive feedback. Age has little effect on customer satisfaction.

Visualizations and Insights

1. Rating Distribution

[image] Most customers gave ratings between 4 and 5, showing overall satisfaction with products.

2. Age Distribution

[image] Most reviewers are between ages 35–50, with fewer very young or older customers.

3. Positive Feedback Count by Rating

[image] Higher-rated reviews tend to receive more positive feedback, meaning users agree with positive reviews.

4. Age vs. Rating (Colored by Recommendation)

[image] There is no strong relationship between customer age and product rating — people of all ages rate similarly.

5. Average Rating by Department

[image] Departments like Intimate and Jackets receive the highest average ratings, while Trend is rated slightly lower.

Summary: Overall, the analysis shows that most customers are satisfied, especially in certain departments, and that positive reviews receive strong community support.

Project Video

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Notebook (Full Code)

To view and run the complete analysis, click the link below: