R/load_las.R

In moj-analytical-services/las_rap_code_library: Functions used for legal aid statistics publications and R Shiny apps

#' Loads specific CSV from alpha-legal-aid-statistics-team AWS bucket and allows you to pick specific schemes and categories.
#'
#' @description Function to load CSV from alpha-legal-aid-statistics-team AWS bucket and filter by scheme and category. Input for all parameters is case-sensitive.
#'
#' @param file Needs to be either NULL or the name of a CSV that is in the AWS bucket. By default, this function loads the latest CSV.
#' @param choose_scheme Needs to be a valid scheme. By default, this function selects all avaiable schemes.
#' @param choose_cat Needs to be a valid category. By default, this function chooses all available categories depending on the chosen scheme.
#
#' @examples
# load_las(file = NULL) will give you the latest CSV
# load_las(file = "lasq418r_v3.csv") will give you version 3 of the las CSV dated on 2018Q4
# load_las(choose_scheme = "Legal Help") will give you the latest figures on Legal Help
#
# load_las(choose_scheme = "Crime Higher", choose_cat = c("hc - Higher Courts", "hc - Crown Courts")) will give
# you the latest Higher Courts and Crown Courts figures from the Crime Higher scheme
#' 
#' @return Data from las CSVs
#'
#' @export
#' 
library(dplyr)

load_las <- function(file = NULL, fun = read.csv, choose_scheme = all_scheme, choose_cat = all_cat) {
  
  # This collects the name of the latest LAS CSV
  allCSVs <- botor::s3_ls('s3://alpha-legal-aid-statistics-team')$key
  allCSVs <- allCSVs[which(stringr::str_sub(allCSVs,-4) == '.csv' & stringr::str_sub(allCSVs, 1, 4) == 'lasq')]
  
  latest_yr <- max(stringr::str_sub(allCSVs, 6, 7))
  
  latest_CSV <- max(allCSVs[which(stringr::str_sub(allCSVs,6, 7) == latest_yr)])
  
  all_scheme <- c("Crime Higher", "Crime Apps and Grants", "Crime Lower", 
                  "Exceptional Case Funding", "Mediation", "Civil Representation", "Gateway Civil Representation", "Legal Help", 
                  "Central Funds", "Crown Court", "Higher Courts", "Overall Expenditure")
  
  scheme_exists <- is.element(choose_scheme, all_scheme)
  
  if(is.element("FALSE", scheme_exists)){
    stop("Please select valid scheme")
  }
  
  ## Choose latest CSV
  else if(is.null(file))
  {
    ## Read from s3 bucket
    file <- latest_CSV
    file_path <- paste0("s3://alpha-legal-aid-statistics-team/", file)
    output <- botor::s3_read(file_path, fun)
    
    ## Remove excess columns
    output <- output[, 1:20]
    
    ## Changing class of columns
    output <- output %>%
      dplyr::mutate(across(fin_yr:sub_cat6, as.character)) %>%
      dplyr::mutate(across(volume:laa_portion, as.numeric))
    
    ## Filter to chosen scheme
    output <- dplyr::filter(output, scheme %in% choose_scheme)
    
    ## Collect distinct categories
    all_cat <- unique(output$category)
    
    ## Check that chosen categories exist
    cat_exists <- is.element(choose_cat, all_cat)
  }
  
  else if(!file %in% allCSVs)
  {
    stop("Please use a CSV from the alpha-legal-aid-statistics-team AWS bucket")
  }
  
  else if(file %in% allCSVs)
  {
    ## Read from s3 bucket
    file_path <- paste0("s3://alpha-legal-aid-statistics-team/", file)
    output <- botor::s3_read(file_path, fun)
    
    ## Remove excess columns
    output <- output[, 1:20]
    
    ## Changing class of columns
    output <- output %>%
      dplyr::mutate(across(fin_yr:sub_cat6, as.character)) %>%
      dplyr::mutate(across(volume:laa_portion, as.numeric))
    
    ## Filter to chosen scheme
    output <- dplyr::filter(output, scheme %in% choose_scheme)
    
    ## Collect distinct categories
    all_cat <- unique(output$category)
    
    ## Check that chosen categories exist
    cat_exists <- is.element(choose_cat, all_cat)
  }
  
  else 
  {stop("Please enter either NULL or the name of a CSV that is in the AWS bucket")}
  
  ## Gives error message if chosen categories do not exist
  if(is.element("FALSE", cat_exists)){
    stop("Please select correct category")
  }
  else{
   output <- dplyr::filter(output, category %in% choose_cat)
  }
  
  return(output)
}