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Supermarket Data aggregated by Customer and info from shops pivoted to new columns.
Pennacchioli, D., Coscia, M., Rinzivillo, S., Pedreschi, D. and Giannotti, F., Explaining the Product Range Effect in Purchase Data. In BigData, 2013.
Sample dataset of one year hourly basis machine monitor, with the recorded info about failures.
The data is related with direct marketing campaigns of a Portuguese banking institution. The marketing campaigns were based on phone calls. Often, more than one contact to the same client was required, in order to access if the product (bank term deposit) would be (or not) subscribed.
The classification goal is to predict if the client will subscribe a term deposit.
The Sales Jan 2009 file contains some “sanitized” sales transactions during the month of January. Below is a sample of a report built in just a couple of minutes using the Blank Canvas app. These 998 transactions are easily summarized and filtered by transaction date, payment type, country, city, and geography
- Population (x1000)
New Vehicle Sales ($M)
- Consumer Credit ($B)
New Houses Sales (x1000)
- US Dollar Index
Government Employees (x1000)
- Personal Income ($B)
Avg New House Price ($)
- Industrial Production Index
Civilian Employment-Population ratio
AirBnB rentals in Amsterdam
Source: Inside Airbnb