auto: Automobile Customer Survey Data
In flexclust: Flexible Cluster Algorithms
auto R Documentation
Automobile Customer Survey Data
Description
A German manufacturer of premium cars asked customers approximately 3
months after a car purchase which characteristics of the car were most
important for the decision to buy the car. The survey was done in 1983
and the data set contains all responses without missing values.
Usage
data(auto)
Format
A data frame with 793 observations on the following 46 variables.
modelA factor with levels A, B,
C, or D; model bought by the customer.
gearA factor with levels 4 gears, 5
econo, 5 sport, or automatic.
leasingA logical vector, was leasing used to finance
the car?
usageA factor with levels private, both, business.
previous_modelA factor describing which type of car
was owned directly before the purchase.
other_considerA factor with levels same manuf,
other manuf, both, or none.
test_driveA logical vector, did you do a test drive?
info_advA logical vector, was advertising an
important source of information?
info_expA logical vector, was experience an
important source of information?
info_recA logical vector, were recommendations an
important source of information?
ch_clarityA logical vector.
ch_economyA logical vector.
ch_driving_propertiesA logical vector.
ch_serviceA logical vector.
ch_interiorA logical vector.
ch_qualityA logical vector.
ch_technologyA logical vector.
ch_model_continuityA logical vector.
ch_comfortA logical vector.
ch_reliabilityA logical vector.
ch_handlingA logical vector.
ch_reputationA logical vector.
ch_conceptA logical vector.
ch_characterA logical vector.
ch_powerA logical vector.
ch_resale_valueA logical vector.
ch_stylingA logical vector.
ch_safetyA logical vector.
ch_sportyA logical vector.
ch_consumptionA logical vector.
ch_spaceA logical vector.
satisfactionA numeric vector describing overall
satisfaction (1=very good, 10=very bad).
good1Conception, styling, dimensions.
good2Auto body.
good3Driving and coupled axles.
good4Engine.
good5Electronics.
good6Financing and customer service.
good7Other.
sportyWhat do you think about the balance of
sportiness and comfort? (good, more sport, more comfort).
drive_charDriving characteristis (gentle < speedy < powerfull < extreme).
tempoWhich average speed do you prefer on German
Autobahn in km/h? (< 130 < 130-150 < 150-180 < > 180)
consumptionAn ordered factor with levels low < ok < high < too high.
genderA factor with levels male and female
occupationA factor with levels self-employed,
freelance, and employee.
householdSize of household, an ordered factor with levels 1-2 < >=3.
Source
The original German data are in the public domain and available
from LMU Munich (doi:10.5282/ubm/data.14). The variable names and
help page were translated to English and converted into Rd format
by Friedrich Leisch.
References
Open Data LMU (1983): Umfrage unter Kunden einer Automobilfirma,
doi:10.5282/ubm/data.14
Examples
data(auto)
summary(auto)
flexclust documentation built on April 8, 2022, 5:09 p.m.
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| auto | R Documentation |
Automobile Customer Survey Data
Description
A German manufacturer of premium cars asked customers approximately 3 months after a car purchase which characteristics of the car were most important for the decision to buy the car. The survey was done in 1983 and the data set contains all responses without missing values.
Usage
data(auto)
Format
A data frame with 793 observations on the following 46 variables.
modelA factor with levels
A,B,C, orD; model bought by the customer.gearA factor with levels
4 gears,5 econo,5 sport, orautomatic.leasingA logical vector, was leasing used to finance the car?
usageA factor with levels
private,both,business.previous_modelA factor describing which type of car was owned directly before the purchase.
other_considerA factor with levels
same manuf,other manuf,both, ornone.test_driveA logical vector, did you do a test drive?
info_advA logical vector, was advertising an important source of information?
info_expA logical vector, was experience an important source of information?
info_recA logical vector, were recommendations an important source of information?
ch_clarityA logical vector.
ch_economyA logical vector.
ch_driving_propertiesA logical vector.
ch_serviceA logical vector.
ch_interiorA logical vector.
ch_qualityA logical vector.
ch_technologyA logical vector.
ch_model_continuityA logical vector.
ch_comfortA logical vector.
ch_reliabilityA logical vector.
ch_handlingA logical vector.
ch_reputationA logical vector.
ch_conceptA logical vector.
ch_characterA logical vector.
ch_powerA logical vector.
ch_resale_valueA logical vector.
ch_stylingA logical vector.
ch_safetyA logical vector.
ch_sportyA logical vector.
ch_consumptionA logical vector.
ch_spaceA logical vector.
satisfactionA numeric vector describing overall satisfaction (1=very good, 10=very bad).
good1Conception, styling, dimensions.
good2Auto body.
good3Driving and coupled axles.
good4Engine.
good5Electronics.
good6Financing and customer service.
good7Other.
sportyWhat do you think about the balance of sportiness and comfort? (
good,more sport,more comfort).drive_charDriving characteristis (
gentle<speedy<powerfull<extreme).tempoWhich average speed do you prefer on German Autobahn in km/h? (
< 130<130-150<150-180<> 180)consumptionAn ordered factor with levels
low<ok<high<too high.genderA factor with levels
maleandfemaleoccupationA factor with levels
self-employed,freelance, andemployee.householdSize of household, an ordered factor with levels
1-2<>=3.
Source
The original German data are in the public domain and available from LMU Munich (doi:10.5282/ubm/data.14). The variable names and help page were translated to English and converted into Rd format by Friedrich Leisch.
References
Open Data LMU (1983): Umfrage unter Kunden einer Automobilfirma, doi:10.5282/ubm/data.14
Examples
data(auto) summary(auto)
R Package Documentation
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