Customer Income Data from a marketing survey.
data(income)A data frame with 14 categorical variables (8993 observations).
Explanation of the variable names:
| 1 | INCOME |
annual income of household | ||
| (Personal income if single) | ordinal | |||
| 2 | SEX |
sex | nominal | |
| 3 | MARITAL.STATUS |
marital status | nominal | |
| 4 | AGE |
age | ordinal | |
| 5 | EDUCATION |
educational grade | ordinal | |
| 6 | OCCUPATION |
type of work | nominal | |
| 7 | AREA |
how long the interviewed person has lived | ||
| in the San Francisco/Oakland/San Jose area | ordinal | |||
| 8 | DUAL.INCOMES |
dual incomes (if married) | nominal | |
| 9 | HOUSEHOLD.SIZE |
persons living in the household | ordinal | |
| 10 | UNDER18 |
persons in household under 18 | ordinal | |
| 11 | HOUSEHOLDER |
householder status | nominal | |
| 12 | HOME.TYPE |
type of home | nominal | |
| 13 | ETHNIC.CLASS |
ethnic classification | nominal | |
| 14 | LANGUAGE |
language most often spoken at home | nominal |
A total of N=9409 questionnaires containing 502 questions were filled out by shopping mall customers in the San Francisco Bay area. The dataset is an extract from this survey. It consists of 14 demographic attributes. The dataset is a mixture of nominal and ordinal variables with a lot of missing data. The goal is to predict the Anual Income of Household from the other 13 demographics attributes.