R/compute_map_df.R

In HenriMatalon/XHEC-R-GROUP-PROJECT-FDNY:

#' Compute the 2 data frame needed to plot the maps from the filtered one.
#'
#' @param filtered_df a filtered version of the full data
#'
#' @import dplyr
#'
#' @return A list of dataframe `heatmap` containing "Number of Intervention", "Mean Intervention Duration", "Mean Number of Units" per zip code. A list of dataframe `fire_box` containing "Number of Intervention", "Mean Intervention Duration", "Mean Number of Units" per fire box.
#' @export
#' @rdname compute_map_df

compute_map_df <- function(filtered_df) {
  if(dim(filtered_df)[1]>1) {
    output <- list()
    output$heatmap <- filtered_df %>%
      group_by(zip_code) %>%
      summarise(
        n=n(),
        mean_interv_time = as.integer(mean(as.numeric(dep_time) - as.numeric(arr_time), na.rm = TRUE)),
        mean_nb_units = as.integer(mean(units, na.rm = TRUE))
      )
    output$fire_box <- filtered_df %>%
      group_by(fire_box) %>%
      summarise(
        n=n(),
        mean_interv_time = as.integer(mean(as.numeric(dep_time) - as.numeric(arr_time), na.rm = TRUE)),
        mean_nb_units = as.integer(mean(units, na.rm = TRUE))
      )
    names(output$fire_box) <- c("fire_box", "Number of Intervention", "Mean Intervention Duration", "Mean Number of Units")
    names(output$heatmap) <- c("zip_code", "Number of Intervention", "Mean Intervention Duration", "Mean Number of Units")
    return(output)
  } else {
    return(data.frame())
  }
}