| d.pizza {DescTools} | R Documentation |
Data pizza
Description
An artificial dataset inspired by a similar dataset pizza.sav in Arbeitsbuch zur deskriptiven und induktiven Statistik by Toutenburg et.al.
The dataset contains data of a pizza delivery service in London, delivering pizzas to three areas. Every record defines one order/delivery and the according properties. A pizza is supposed to taste good, if its temperature is high enough, say 45 Celsius. So it might be interesting for the pizza delivery service to minimize the delivery time.
The dataset is designed to be as evil as possible. As far as the description is concerned, it should pose the same difficulties that we have to deal with in everyday life. It contains the most used datatypes as numerics, factors, ordered factors, integers, logicals and a date. NAs are scattered everywhere partly systematically, partly randomly (except in the index).
Usage
data(d.pizza)
Format
A data frame with 1209 observations on the following 17 variables.
indexa numeric vector, indexing the records (no missings here).
dateDate, the delivery date
weekinteger, the weeknumber
weekdayinteger, the weekday
areafactor, the three London districts:
Brent,Camden,Westminstercountinteger, the number of pizzas delivered
rabatelogical,
TRUEif a rabate has been givenpricenumeric, the total price of delivered pizza(s)
operatora factor with levels
AllanahMariaRhondadrivera factor with levels
CarpenterCarterTaylorButcherHunterMillerFarmerdelivery_minnumeric, the delivery time in minutes (decimal)
temperaturenumeric, the temperature of the pizza in degrees Celsius when delivered to the customer
wine_orderedinteger, 1 if wine was ordered, 0 if not
wine_deliveredinteger, 1 if wine was delivered, 0 if not
wrongpizzalogical,
TRUEif a wrong pizza was deliveredqualityordered factor with levels
low<medium<high, defining the quality of the pizza when delivered
Details
The dataset contains NAs randomly scattered.
References
Toutenburg H, Schomaker M, Wissmann M, Heumann C (2009): Arbeitsbuch zur deskriptiven und induktiven Statistik Springer, Berlin Heidelberg
Examples
str(d.pizza)
head(d.pizza)
Desc(d.pizza)