rm(list = ls())
setwd("/home/onyxia/formation-bonnes-pratiques-R")

if (!require('ggplot2')) install.packages('ggplot2')
if (!require('stringr')) install.packages('stringr')
if (!require('dplyr')) install.packages('dplyr')
if (!require('tidyverse')) install.packages('tidyverse')


library(tidyverse)

# j'importe les données avec read_csv2 parce que c'est un csv avec des ; et que read_csv attend comme separateur des , 
df <- readr::read_csv2(
  "individu_reg.csv",
  col_select = c("region", "aemm", "aged", "anai","catl","cs1", "cs2", "cs3", "couple", "na38", "naf08", "pnai12", "sexe", "surf", "tp", "trans", "ur"))

df <- df %>%
  mutate(aged = as.numeric(aged))

summarise(group_by(df, aged), n())

decennie_a_partir_annee    = function(ANNEE){ return(ANNEE - ANNEE %%
                                                       10) }

ggplot(df) + geom_histogram(aes(x = 5*floor(as.numeric(aged)/5)), stat = "count")

# correction (qu'il faudra retirer)
# ggplot(
#   df %>% group_by(aged, sexe) %>% summarise(SH_sexe = n()) %>% group_by(aged) %>% mutate(SH_sexe = SH_sexe/sum(SH_sexe)) %>% filter(sexe==1)
# ) + geom_bar(aes(x = as.numeric(aged), y = SH_sexe), stat="identity") + geom_point(aes(x = as.numeric(aged), y = SH_sexe), stat="identity", color = "red") + coord_cartesian(c(0,100))

# stats trans par statut
df3 = df %>% group_by(couple, trans) %>% summarise(x = n()) %>% group_by(couple) %>% mutate(y = 100*x/sum(x))

p <- # part d'homme dans chaque cohort
  df %>% 
  group_by(aged, sexe) %>% 
  summarise(SH_sexe = n()) %>% 
  group_by(aged) %>% 
  mutate(SH_sexe = SH_sexe/sum(SH_sexe)) %>% 
  filter(sexe==1) %>%
  ggplot() + geom_bar(aes(x = aged, y = SH_sexe), stat="identity") + geom_point(aes(x = aged, y = SH_sexe), stat="identity", color = "red") + coord_cartesian(c(0,100))


ggsave("p.png", p)

library(forcats)
df$sexe <- df$sexe %>%
  as.character() %>%
  fct_recode(Homme = "1", Femme = "2")

#fonction de stat agregee
fonction_de_stat_agregee<-function(a,b="moyenne",...){
  if (b=="moyenne"){
    x=mean(a, na.rm = T,...)
  } else if (b=="ecart-type" | b == "sd"){
    x = sd(a, na.rm = T, ...)
  } else if (b=="variance"){
    x = var(a, na.rm = T, ...)
  }
  return(x)
}

fonction_de_stat_agregee(rnorm(10))
fonction_de_stat_agregee(rnorm(10), "ecart-type")
fonction_de_stat_agregee(rnorm(10), "variance")

fonction_de_stat_agregee(df %>% filter(sexe == "Homme") %>% pull(aged))
fonction_de_stat_agregee(df %>% filter(sexe == "Femme") %>% pull(aged))

api_token <- "trotskitueleski$1917"

# modelisation
# library(MASS)
df3=df%>%select(surf,cs1,ur,couple,aged)%>%filter(surf!="Z")
df3[,1]=factor(df3$surf, ordered = T)
df3[,"cs1"]=factor(df3$cs1)
df3 %>% 
  filter(couple == "2" & aged>40 & aged<60)
polr(surf ~ cs1 + factor(ur), df3)