Data sourse - The dataset is collected by web scraping from the website of Etsy. - Product of research: handmade house paintings - On Etsy: shipping is internationally - Currency: EUR

Description of the features: - weekly sales and total sales are estimated (based on reviews and sales of each store, cannot scrap the exact information because it is private) - Raving: buyers are raving, multiple people gave 5 stars over the last 7 days - Bestseller: high volumn sales over the past 6 months - Release time: the date that a product is listed - Etsy pick: a type of badge for sellers on Etsy

As of October 16, 2024, CaitlynMinimalist was the Etsy seller with the most sales on the platform in the previous year. The store, which sells jewelry, recorded over 680,000 purchases by Etsy buyers in 12 months. Esty’s Overview Etsy, an online marketplace, generates revenue from three primary segments: marketplace revenues, this includes fees for sales transactions and listings of products; seller service revenues; and other revenues which includes third-party payment processor fees. The annual revenue of Etsy has steadily increased over the past years, reaching over *** billion U.S. dollars, which in part is due to a steady increase of investment into their advertising. Usage of Etsy When ranking the leading websites by share of visits in the United States, esty.com was fourth, outranked by amazon.com, ebay.com, and walmart.com. Still, over the past years, the number of active Etsy sellers has increased, reaching over * million in 2023. That year, Etsy's active buyers also grew, reaching over ** million, a new high for the company.

Context

As a part of my "Learn Data Science for Great Good By Yourself" programme, I picked the topic of Etsy shops for Exploratory Analysis. Thanks to my wife for chosing the topic, she started her Etsy shop and we started to discover it together

The analysis itself (as well as info on how it was scraped) can be found here: https://github.com/snowwlex/EtsyAnalysis as well as Kaggle's notebook

Content

It contains info about ~400K Etsy shops, scraped in the end of July of 2019. It is not all etsy shops back then, just a sample, but it should be enough to be able to see some trends / do Exploratory Analysis

Also shop names have been removed, so this dataset would be more like anonymous rather than pointing to actual shops.

Context

As an Etsy shop owner myself, I was interested to see how other Etsy shops are doing and if there are particular attributes of their shops (e.g. location, number of reviews and followers) that may impact their success.

Content

The dataset represents a few chosen attributes of 20k newly created Etsy shops in Nov and Dec 2019. You can find the script used in my GitHub repo here: https://github.com/Sepiafs/etsy_data_collection.

Acknowledgements

The data has been extracted using web scraping techniques and Etsy web API.

Inspiration

What attributes of newly created Etsy shops have positive impact on their success?

This analysis presents a rigorous exploration of financial data, incorporating a diverse range of statistical features. By providing a robust foundation, it facilitates advanced research and innovative modeling techniques within the field of finance.

ETSY's Earnings: A Sign of E-commerce Strength?

Financial data:

• Historical daily stock prices (open, high, low, close, volume)

• Fundamental data (e.g., market capitalization, price to earnings P/E ratio, dividend yield, earnings per share EPS, price to earnings growth, debt-to-equity ratio, price-to-book ratio, current ratio, free cash flow, projected earnings growth, return on equity, dividend payout ratio, price to sales ratio, credit rating)

• Technical indicators (e.g., moving averages, RSI, MACD, average directional index, aroon oscillator, stochastic oscillator, on-balance volume, accumulation/distribution A/D line, parabolic SAR indicator, bollinger bands indicators, fibonacci, williams percent range, commodity channel index)

Machine learning features:

• Feature engineering based on financial data and technical indicators

• Sentiment analysis data from social media and news articles

• Macroeconomic data (e.g., GDP, unemployment rate, interest rates, consumer spending, building permits, consumer confidence, inflation, producer price index, money supply, home sales, retail sales, bond yields)

Potential Applications:

• Stock price prediction

• Portfolio optimization

• Algorithmic trading

• Market sentiment analysis

• Risk management

Use Cases:

• Researchers investigating the effectiveness of machine learning in stock market prediction

• Analysts developing quantitative trading Buy/Sell strategies

• Individuals interested in building their own stock market prediction models

• Students learning about machine learning and financial applications

Additional Notes:

• The dataset may include different levels of granularity (e.g., daily, hourly)

• Data cleaning and preprocessing are essential before model training

• Regular updates are recommended to maintain the accuracy and relevance of the data

Weekly statistics showing how many Etsy coupon codes were verified by the CouponBirds team. This dataset reflects real-time coupon validation activity to ensure coupon accuracy and reliability.