banque {ade4}R Documentation

Table of Factors

Description

banque gives the results of a bank survey onto 810 customers.

Usage

data(banque)

Format

This data frame contains the following columns:

  1. csp: "Socio-professional categories" a factor with levels agric Farmers artis Craftsmen, Shopkeepers, Company directors cadsu Executives and higher intellectual professions inter Intermediate professions emplo Other white-collar workers ouvri Manual workers retra Pensionners inact Non working population etudi Students

  2. duree: "Time relations with the customer" a factor with levels dm2 <2 years d24 [2 years, 4 years[ d48 [4 years, 8 years[ d812 [8 years, 12 years[ dp12 >= 12 years

  3. oppo: "Stopped a check ?" a factor with levels non no oui yes

  4. age: "Customer's age" a factor with levels ai25 [18 years, 25 years[ ai35 [25 years, 35 years[ ai45 [35 years, 45 years[ ai55 [45 years, 55 years[ ai75 [55 years, 75 years[

  5. sexe: "Customer's gender" a factor with levels hom Male fem Female

  6. interdit: "No checkbook allowed" a factor with levels non no oui yes

  7. cableue: "Possess a bank card ?" a factor with levels non no oui yes

  8. assurvi: "Contrat of life insurance ?" a factor with levels non no
    oui yes

  9. soldevu: "Balance of the current accounts" a factor with levels p4 credit balance > 20000 p3 credit balance 12000-20000 p2 credit balance 4000-120000 p1 credit balance >0-4000 n1 debit balance 0-4000 n2 debit balance >4000

  10. eparlog: "Savings and loan association account amount" a factor with levels for > 20000 fai >0 and <20000 nul nulle

  11. eparliv: "Savings bank amount" a factor with levels for > 20000 fai >0 and <20000 nul nulle

  12. credhab: "Home loan owner" a factor with levels non no oui yes

  13. credcon: "Consumer credit amount" a factor with levels nul none fai >0 and <20000 for > 20000

  14. versesp: "Check deposits" a factor with levels oui yes non no

  15. retresp: "Cash withdrawals" a factor with levels fai < 2000 moy 2000-5000 for > 5000

  16. remiche: "Endorsed checks amount" a factor with levels for >10000 moy 10000-5000 fai 1-5000 nul none

  17. preltre: "Treasury Department tax deductions" a factor with levels nul none fai <1000 moy >1000

  18. prelfin: "Financial institution deductions" a factor with levels nul none fai <1000 moy >1000

  19. viredeb: "Debit transfer amount" a factor with levels nul none fai <2500 moy 2500-5000 for >5000

  20. virecre: "Credit transfer amount" a factor with levels for >10000 moy 10000-5000 fai <5000 nul aucun

  21. porttit: "Securities portfolio estimations" a factor with levels nul none fai < 20000 moy 20000-100000 for >100000

Source

anonymous

Examples

data(banque)
banque.acm <- dudi.acm(banque, scann = FALSE, nf = 3)
apply(banque.acm$cr, 2, mean)
banque.acm$eig[1:banque.acm$nf] # the same thing
s.arrow(banque.acm$c1, clab = 0.75)

Worked out examples


> library(ade4)
> ### Name: banque
> ### Title: Table of Factors
> ### Aliases: banque
> ### Keywords: datasets
> 
> ### ** Examples
> 
> data(banque)
> banque.acm <- dudi.acm(banque, scann = FALSE, nf = 3)
> apply(banque.acm$cr, 2, mean)
       RS1        RS2        RS3 
0.17346599 0.11838319 0.09825814 
> banque.acm$eig[1:banque.acm$nf] # the same thing
[1] 0.17346599 0.11838319 0.09825814
> s.arrow(banque.acm$c1, clab = 0.75)
> 
> 
> 
> 

[Package ade4 Index]