Chapitre 15 20 Annexes
15.1 Données Eric-ESS
Extraction France
Le fichier est disponible sous format ESS10fr.rds
df<-readRDS("./data/trustFrAll.rds")
write.csv(df, "./data/dfTrust.rds")
df<-read.csv("./data/dfTrust.rds")
#quelques recodages
#on renomme pour plus de clarté
names(df)[names(df)=="trstun"] <- "NationsUnies"
names(df)[names(df)=="trstep"] <- "ParlementEurop"
names(df)[names(df)=="trstlgl"] <- "Justice"
names(df)[names(df)=="trstplc"] <- "Police"
names(df)[names(df)=="trstplt"] <- "Politiques"
names(df)[names(df)=="trstprl"] <-"Parlement"
names(df)[names(df)=="trstprt"] <- "Partis"
names(df)[names(df)=="pplhlp"] <- "help"
names(df)[names(df)=="pplfair"] <- "fair"
names(df)[names(df)=="ppltrst"] <- "trust"
#on construit les scores de confiance
df<-df %>%
mutate(trust_institut=(Partis+Parlement+Politiques+Police+Justice+NationsUnies+ParlementEurop)*10/7,trust_interpersonnel=(help+fair+trust)*10/3)
df$Year<-2000
#recodage des variables independantes
df$Year[df$essround==1]<-2002
df$Year[df$essround==2]<-2004
df$Year[df$essround==3]<-2006
df$Year[df$essround==4]<-2008
df$Year[df$essround==5]<-2010
df$Year[df$essround==6]<-2012
df$Year[df$essround==7]<-2014
df$Year[df$essround==8]<-2016
df$Year[df$essround==9]<-2018
df$Year<-as.factor(df$Year)
df$OP<-" "
#ggplot(df,aes(x=lrscale))+geom_histogram()
df$OP[df$lrscale==0] <- "Extrême gauche"
df$OP[df$lrscale==1] <- "Gauche"
df$OP[df$lrscale==2] <- "Gauche"
df$OP[df$lrscale==3] <- "Centre Gauche"
df$OP[df$lrscale==4] <- "Centre Gauche"
df$OP[df$lrscale==5] <- "Ni G ni D"
df$OP[df$lrscale==6] <- "Centre Droit"
df$OP[df$lrscale==7] <- "Centre Droit"
df$OP[df$lrscale==8] <- "Droite"
df$OP[df$lrscale==9] <- "Droite"
df$OP[df$lrscale==10] <- "Extrême droite"
#la ligne suivante est pour ordonner les modalités de la variables
df$OP<-factor(df$OP,levels=c("Extrême droite","Droite","Centre Droit","Ni G ni D","Centre Gauche","Gauche","Extrême gauche"))
df$revenu<-" "
df$revenu[df$hincfel>4] <- NA
df$revenu[df$hincfel==1] <- "Vie confortable"
df$revenu[df$hincfel==2] <- "Se débrouille avec son revenu"
df$revenu[df$hincfel==3] <- "Revenu insuffisant"
df$revenu[df$hincfel==4] <- "Revenu très insuffisant"
df$revenu<-factor(df$revenu,levels=c("Vie confortable","Se débrouille avec son revenu","Revenu insuffisant","Revenu très insuffisant"))
df$habitat<-" "
df$habitat[df$domicil==1]<- "Big city"
df$habitat[df$domicil==2]<-"Suburbs"
df$habitat[df$domicil==3]<-"Town"
df$habitat[df$domicil==4]<-"Village"
df$habitat[df$domicil==5]<-"Countryside"
df$habitat<-factor(df$habitat,levels=c("Big city","Suburbs","Town","Village","Countryside"))
df$genre<-" "
df$genre[df$gndr==1]<-"H"
df$genre[df$gndr==2]<-"F"
df$age<-" "
df$age[df$agea<26]<-"25<"
df$age[df$agea>25 & df$agea<36]<-"26-35"
df$age[df$agea>35 & df$agea<46]<-"36-45"
df$age[df$agea>45 & df$agea<66]<-"46-65"
df$age[df$agea>65 & df$agea<76]<-"66-75"
df$age[df$agea>75]<-"75>"
df$age<-factor(df$age,levels=c("25<","26-35","36-45","46-65","66-75", "75>"))
saveRDS(df, "./data/dfTrust.rds")
######
##########
df <- read_csv("Data/ESS-Data-Wizard-subset-2022-10-06.csv")
df$Year<-2000
#recodage des variables independantes
df$Year[df$essround==1]<-2002
df$Year[df$essround==2]<-2004
df$Year[df$essround==3]<-2006
df$Year[df$essround==4]<-2008
df$Year[df$essround==5]<-2010
df$Year[df$essround==6]<-2012
df$Year[df$essround==7]<-2014
df$Year[df$essround==8]<-2016
df$Year[df$essround==9]<-2018
df$Year<-as.factor(df$Year)
df$OP<-" "
#ggplot(df,aes(x=lrscale))+geom_histogram()
df$OP[df$lrscale==0] <- "Extrême gauche"
df$OP[df$lrscale==1] <- "Gauche"
df$OP[df$lrscale==2] <- "Gauche"
df$OP[df$lrscale==3] <- "Centre Gauche"
df$OP[df$lrscale==4] <- "Centre Gauche"
df$OP[df$lrscale==5] <- "Ni G ni D"
df$OP[df$lrscale==6] <- "Centre Droit"
df$OP[df$lrscale==7] <- "Centre Droit"
df$OP[df$lrscale==8] <- "Droite"
df$OP[df$lrscale==9] <- "Droite"
df$OP[df$lrscale==10] <- "Extrême droite"
#la ligne suivante est pour ordonner les modalités de la variables
df$OP<-factor(df$OP,levels=c("Extrême droite","Droite","Centre Droit","Ni G ni D","Centre Gauche","Gauche","Extrême gauche"))
df$genre<-" "
df$genre[df$gndr==1]<-"H"
df$genre[df$gndr==2]<-"F"
df$age<-" "
df$age[df$agea<26]<-"25<"
df$age[df$agea>25 & df$agea<36]<-"26-35"
df$age[df$agea>35 & df$agea<46]<-"36-45"
df$age[df$agea>45 & df$agea<66]<-"46-65"
df$age[df$agea>65 & df$agea<76]<-"66-75"
df$age[df$agea>75]<-"75>"
df$age<-factor(df$age,levels=c("25<","26-35","36-45","46-65","66-75", "75>"))
df_confiance<-df%>%
dplyr::select(trstep, trstlgl,trstplc,trstplt,trstprl,trstprt,trstun,pplfair,pplhlp, ppltrst) %>%
mutate(trstep=ifelse(trstep==77 |trstep==88| trstep==66,NA,trstep),
trstlgl=ifelse(trstlgl==77 |trstlgl==88| trstlgl==66,NA,trstlgl),
trstplc=ifelse(trstplc==77 |trstplc==88| trstplc==66,NA,trstplc),
trstplt=ifelse(trstplt==77 |trstplt==88| trstplt==66,NA,trstplt),
trstprt=ifelse(trstprt==77 |trstprt==88| trstprt==66,NA,trstprt),
trstun=ifelse(trstun==77 |trstun==88| trstun==66,NA,trstun),
trstprl=ifelse(trstprl==77 |trstprl==88| trstprl==66,NA,trstprl),
pplfair=ifelse(pplfair==77 |pplfair==88| pplfair==66,NA,pplfair),
pplhlp=ifelse(pplhlp==77 |pplhlp==88| pplhlp==66,NA,pplhlp),
ppltrst=ifelse(ppltrst==77 |ppltrst==88| ppltrst==66,NA,ppltrst),
trust_institution= (trstep+trstlgl+trstplc+trstplt+trstprl+trstprt+trstun)/7,
trust_personne= (pplfair+pplhlp+ppltrst)/7
)
df_satisfaction<-df%>%
dplyr::select(stfeco,stfedu,stfgov, stfhlth, stflife,stfmjob, happy) %>%
mutate(stfeco=ifelse(stfeco==77 |stfeco==88| stfeco==66,NA,stfeco),
stfedu=ifelse(stfedu==77 |stfedu==88 | stfedu==66,NA,stfedu),
stfgov=ifelse(stfgov==77 |stfgov==88 | stfgov==66, NA, stfgov),
stfhlth=ifelse(stfhlth==77 |stfhlth==88|stfhlth==66,NA,stfhlth),
stflife=ifelse(stflife==77 |stflife==88|stflife==66,NA,stflife),
happy=ifelse(happy==77 |happy==88|happy==66,NA,happy),
stfmjob=ifelse(stfmjob==77 |stfmjob==88|stfmjob==66,NA,stfmjob),
satisfaction_vie=(stflife+happy)/2, #à examiner
satisfaction_institution=(stfeco+stfgov)/2,
satisfaction_care=(stfhlth+stfedu)/2
)
df_sample<-df%>%
dplyr::select(Year, age, OP, genre)
df<-cbind(df_sample, df_satisfaction, df_confiance)
saveRDS(df, "./data/ESS10fr.rds")15.3
Schwartz, Shalom H. 2006. “Les Valeurs de Base de La Personne : Théorie, Mesures Et Applications:” Revue Française de Sociologie Vol. 47 (4): 929–68. https://doi.org/10.3917/rfs.474.0929.
Sneath, P. H. A., and Robert R. Sokal. 1973. Numerical Taxonomy: The Principles and Practice of Numerical Classification. A Series of Books in Biology. San Francisco: W. H. Freeman.
Thurstone, L. L. 1931. “Multiple Factor Analysis.” Psychological Review 38 (5): 406–27. https://doi.org/10.1037/h0069792.