Women's E-Commerce Clothing Data Analysis

This is a Women’s Clothing E-Commerce dataset revolving around the reviews written by customers.

Content

This dataset includes 23486 rows and 10 feature variables. Each row corresponds to a customer review, and includes the variables:

Clothing ID: Integer Categorical variable that refers to the specific piece being reviewed.
Age: Positive Integer variable of the reviewers age.
Title: String variable for the title of the review.
Review Text: String variable for the review body.
Rating: Positive Ordinal Integer variable for the product score granted by the customer from 1 Worst, to 5 Best.
Recommended IND: Binary variable stating where the customer recommends the product where 1 is recommended, 0 is not recommended.
Positive Feedback Count: Positive Integer documenting the number of other customers who found this review positive.
Division Name: Categorical name of the product high level division.
Department Name: Categorical name of the product department name.
Class Name: Categorical name of the product class name.

Please bear in mind that this report is mostly focused on how to use Pythin visualization tools.

Data analysis and report can be found in Women's E-Commerce Clothing .ipynb file

Links

• Trello: Trello
• Presentation: Presentation

Gorkem Guneser
E-mail: [email protected]
25/09/2020