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I am looking for a typical sales data set, which I can use for a time series prediction. I especially want to show how to decompose the seasonal component.

A good example would be a fictional company, or a restaurant that sells much higher volumes in the summer/ or winter.

Best regards, Francisco

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The US Census Bureau provides a good data source:

U.S. Census Bureau's Monthly & Annual Retail Trade

I work at Quandl and here are some databases you might want to check out:

US Census Bureau (free) - Here are the datasets you'll see if you search for "restaurant sales" within this database:

https://www.quandl.com/data/USCENSUS-U-S-Census-Bureau?keyword=restaurant%20sales

Sales Surprises - This is a premium database with sales data for over 5000 companies, including specific restaurants.

https://www.quandl.com/data/ZSS-Sales-Surprises

(Full list of companies covered are listed here: https://www.quandl.com/api/v3/databases/ZSS/codes)

Hope this helps...

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Sales volumes are difficult to find, explicitly broken out would be difficult, however if you look at staples such as soft drink distributors or restaurant's quarterly reports, you can get a basic break out. The first two to look at would be Coca Cola and Pepsi:

Looking on YCharts, this gives you a quick view of seasonality, but you only get ten page views before you must register.

Publicly traded restaurants can give you an idea of additional seasonal variations:

  1. Darden Restaurants
  2. McDonalds
  3. Burger King

Electronics are difficult as there is such variation

You can find the open source versions from their respective Quarterly Earnings Reports:

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