As a skincare enthusiast, I wasn't surprised in the recent surge in demand for skincare products with retinoids. Retinoids are vitamin-A derivative compounds that are known to be effective treatments for a wide range of skin problems, including acne. In this repository, I perform an analysis on skincare products that contain different type of retinoids. The objective of this analysis is to provide consumers with a foundation of knowledge on the benefits, side effects and characteristics of various retinoids, allowing the users to select the best option for their individual skincare needs. Additionally, this analysis identifies potential market gaps, and explore various retinoid ingredients that could be valuable for brands looking to develop new retinoid skincare products.
File Name | Data Description |
---|---|
skincare_products_clean.csv | source data |
brand.csv | reference table for brands and country of origin |
df_retinoid.csv | final cleaned dataframe |
- Jupyter notebook with annotations detailing each stage of preprocessing skincare data
- Data exploration process
- Matplotlib, Seaborn and Plotly visualizations
A document with base knowledge on retinoids, along with insights and opportunities for product development derived from analysis.
A user-friendly and interactive dashboard with product information from the skincare dataset.
Features
- Filter Selectors:
- Retinoid(s)
- Product Type(s)
- View the following information based on your selected filters:
- Number of products
- Highest priced product
- Lowest priced product
- Product information chart (hover over points in chart to display product information)
- Brand name
- Product type
- Price in USD
- Full product name
- Country of origin of brand