# Pourcentage sur chaque base de donnees

# Transformation de la table logement
logement = read.csv("logement.csv",header=T,sep=";")
logement2 = logement[,-1]
logement3 = apply(logement2,1,function(x) x/max(x))
logement4 = t(logement3)
logement5 = logement4[,-1]
logement_fin = data.frame(logement5)

# Transformation de la table sur les residences principales
res_princ = read.csv("res_princ.csv",header=T,sep=";")
res_princ2 = res_princ[,-1]
res_princ3 = apply(res_princ2,1,function(x) x/max(x))
res_princ4 = t(res_princ3)
res_princ5 = res_princ4[,-1]
res_princ_fin = data.frame(res_princ5)

# Transformation de la table emploi
emploi = read.csv("emploi.csv",header=T,sep=";",dec = ',')
emploi2 = emploi[,-1]
emploi3 = apply(emploi2,1,function(x) x/max(x))
emploi3[is.na(emploi3)] <- 0
emploi4 = t(emploi3)
emploi5 = emploi4[,-1]
emploi_fin = data.frame(emploi5)

# Transformation de la table formation
formation = read.csv("formation.csv",header=T,sep=";")
formation2 = formation[,-1]
formation3 = apply(formation2,1,function(x) x/max(x))
formation4 = t(formation3)
formation5 = formation4[,-1]
formation_fin = data.frame(formation5)

# Transformation de la table sur les etablissements actifs
etablissement = read.csv("etablissement.csv",header=T,sep=";")
etablissement2 = etablissement[,-1]
etablissement3 = apply(etablissement2,1,function(x) x/max(x))
etablissement4 = t(etablissement3)
etablissement5 = etablissement4[,-1]
etablissement5[is.na(etablissement5)] <- 0
etablissement_fin = data.frame(etablissement5)

# Transformation de la table sur les postes
poste = read.csv("poste.csv",header=T,sep=";")
poste2 = poste[,-1]
poste3 = apply(poste2,1,function(x) x/max(x))
poste4 = t(poste3)
poste5 = poste4[,-1]
poste5[is.na(poste5)] <- 0
poste_fin = data.frame(poste5)

# Transformation de la table sur les etablissements par secteur
etablissement2_ = read.csv("etablissement2_.csv",header=T,sep=";")
etablissement2_2 = etablissement2_[,-1]
etablissement2_3 = apply(etablissement2_2,1,function(x) x/max(x))
etablissement2_4 = t(etablissement2_3)
etablissement2_5 = etablissement2_4[,-1]
etablissement2_5[is.na(etablissement2_5)] <- 0
etablissement2_fin = data.frame(etablissement2_5)

# Transformation de la table sur les tailles des entreprises
etablissement3_ = read.csv("etablissement3_.csv",header=T,sep=";")
etablissement3_2 = etablissement3_[,-1]
etablissement3_3 = apply(etablissement3_2,1,function(x) x/max(x))
etablissement3_4 = t(etablissement3_3)
etablissement3_5 = etablissement3_4[,-1]
etablissement3_5[is.na(etablissement3_5)] <- 0
etablissement3_fin = data.frame(etablissement3_5)

# Transformation de la table population
pop = read.csv("pop.csv",header=T,sep=";")
pop2 = pop[,-1]
pop3 = apply(pop2,1,function(x) x/max(x))
pop4 = t(pop3)
pop5 = pop4[,-1]
pop_fin = data.frame(pop5)

# Transformation de la table sur les menages
menages = read.csv("menages.csv",header=T,sep=";")
menages2 = menages[,-1]
menages3 = apply(menages2,1,function(x) x/max(x))
menages4 = t(menages3)
menages5 = menages4[,-1]
menages_fin = data.frame(menages5)

# Transformation de la table sur la population des menages
pop_menages = read.csv("pop_menages.csv",header=T,sep=";")
pop_menages2 = pop_menages[,-1]
pop_menages3 = apply(pop_menages2,1,function(x) x/max(x))
pop_menages4 = t(pop_menages3)
pop_menages5 = pop_menages4[,-1]
pop_menages_fin = data.frame(pop_menages5)

pop_menages2_ = read.csv("pop_menages2_.csv",header=T,sep=";")
pop_menages2_2 = pop_menages2_[,-1]
pop_menages2_3 = apply(pop_menages2_2,1,function(x) x/max(x))
pop_menages2_4 = t(pop_menages2_3)
pop_menages2_5 = pop_menages2_4[,-1]
pop_menages_2_fin = data.frame(pop_menages2_5)

# Transformation de la table sur la population active
pop_active = read.csv("pop_active.csv",header=T,sep=";")
pop_active2 = pop_active[,-1]
pop_active3 = apply(pop_active2,1,function(x) x/max(x))
pop_active4 = t(pop_active3)
pop_active5 = pop_active4[,-1]
pop_active_fin = data.frame(pop_active5)

# Transformation de la table sur les caracteristiques de l'emploi
caract_emploi = read.csv("caract_emploi.csv",header=T,sep=";")
caract_emploi2 = caract_emploi[,-1]
caract_emploi2[is.na(caract_emploi2)] <- 0
caract_emploi3 = apply(caract_emploi2,1,function(x) x/max(x))
caract_emploi4 = t(caract_emploi3)
caract_emploi5 = caract_emploi4[,-1]
caract_emploi_fin = data.frame(caract_emploi5)