#' Score the apartments according to the densities of restaurants,commerce,cinema,schools and stations
#'
#' @param commerce dataframe
#' @param restaurants dataframe
#' @param cinema dataframe
#' @param schools dataframe
#' @param stations dataframe
#'
#' @return dataframe with 1 column for the index of the good, and columns scoring the apartments among categories
#' @export
#' @import dplyr
#'
join_dataframe <- function(commerce,restaurants,cinema,schools,stations){
df_commerce <- get_rank(commerce,200)
df_restaurant <- get_rank(restaurants,500)
df_cinema <- get_rank(cinema,500)
df_schools <- get_rank(schools,500)
df_stations <- get_rank(stations,500)
df <- list(df_restaurant,df_commerce,df_cinema,df_schools,df_stations)
df_scoring <- inner_join(df[1:5], by ="apartment_index")
df_scoring <- df_scoring %>%
mutate(anime_resto_cine = restaurant + cinema) %>%
select(-cinema,-restaurant) %>%
mutate(apartment_index = as.character(apartment_index)) %>%
mutate_if(is.integer,funs(qt = decile)) %>%
mutate(score = anime_resto_cine_qt + commerce_qt + schools_qt + stations_qt) %>%
arrange(score)
return(df_scoring)
}
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