R/pii_geo_table.R

In DevikaNair90/prybar: Toolkit for Identifying Hidden PII in Text Data

#' Creates a summary table of PII geography for a dataset.
#'
#' This function takes a dataframe and searches each column for presence of 
#' any text that appears as PII geography: street address, city/states, zipcodes. 
#'
#' @param df A dataframe with (vector-able) variables.
#' @param writeout TRUE/FALSE indicator of whether or not full detailed results to be written out. An individual table will be written out for each column, with PII results for every row of the table. 
#' @param path destination for tables to be written out
#' @import stringr
#' @import maditr
#' @importFrom data.table data.table
#' @suggest generator
#' @export
#' @examples
#' fakeaddresses_df <- data.frame(Addresses =  c("820 Nut Swamp Ave. Toms River, NJ 08753",
#'                                               "982 Clay Street Lenoir, NC 28645",
#'                                             "4 NW. Mayfield Rd. Springfield Gardens, NY 11413",
#'                                           "20 Elmwood Street Raleigh, NC 27603",
#'                                               "196 E. Green Lake Road Birmingham, AL 35209",
#'                                             "73 Beechwood Dr. La Crosse, WI VA DC 54601") )
#' 
#' pii_geo_table(fakeaddresses_df, writeout= FALSE)
#' 
# devtools::load_all()
# devtools::use_package(package = "stringr", type = "import")
# devtools::use_package(package = "maditr", type = "import")

pii_geo_table <- function(df, path, writeout) {
  print(Sys.time())
  df_name <- deparse(substitute(df))
  df <- maditr::as.data.table(df)
  class_table <- maditr::data.table("Column" = colnames(df)) %>%
    dt_mutate(Reference = paste0(df_name, "$", Column), 
              class = character(length = length(colnames(df))))
  
  for (i in 1:ncol(df)) {
    class_table$class[i] <- class(df[[i]])
  }
  
  # numvars <- class_table %>% filter(class %in% c("numeric", "integer", "double")) 
  # charvars <- class_table %>% filter(class == "character")
  # 
  # df_numbers <- df[, as.character(numvars$Column)]
  
  # if (is.data.frame(df_numbers) == FALSE) {
  #   df_numbers <- data.frame(NUM = df_numbers) 
  # }
  # 
  # columnsummary <- data.frame("Column" = colnames(df_numbers))
  
  df_state <- list(maditr::data.table())
  df_city <- list(maditr::data.table())
  df_zipcode <- list(maditr::data.table())
  df_street <- list(maditr::data.table())
  
  # STATES #####################################################################################
  
  for (i in 1:ncol(df)) {
    var <- as.character(df[[i]])
    df_state[[i]] <- search_state(var, "dt")
    class_table$staterisk[i] <- sum(df_state[[i]]$StatesYN, na.rm = TRUE)
  }
  
  if (missing(writeout)||writeout == TRUE) {
    saveRDS(object = df_state, file = paste0(path, df_name, "_PII_1_STATES_", Sys.Date(), ".RDS"))
  }
  
  rm(df_state)
  print("states completed")
  print(Sys.time())
  
  # CITIES #####################################################################################
  
  for (i in 1:ncol(df)) {
    var <- as.character(df[[i]])
    df_city[[i]] <- search_cities_in_states(var, "dt")
    class_table$cityrisk[i] <- sum(df_city[[i]]$CitiesYN, na.rm = TRUE)
  }
  
  if (missing(writeout)||writeout == TRUE) {
    saveRDS(object = df_city, file = paste0(path, df_name, "_PII_2_CITIES_", Sys.Date(), ".RDS"))
  }
  
  rm(df_city)
  print("cities completed")
  print(Sys.time())
  
  # ZIPCODES #####################################################################################
  
  for (i in 1:ncol(df)) {
    var <- as.character(df[[i]])
    df_zipcode[[i]] <- search_zipcode(var, "dt")
    class_table$zipcoderisk[i] <- sum(df_zipcode[[i]]$ZipCodeYN, na.rm = TRUE)
  }
  
  if (missing(writeout)||writeout == TRUE) {
    saveRDS(object = df_zipcode, file = paste0(path, df_name, "_PII_3_ZIPCODES_", Sys.Date(), ".RDS"))
  }
  
  rm(df_zipcode)
  print("zipcodes completed")
  print(Sys.time())
  
  # STREET #####################################################################################
  
  # for (i in 1:ncol(df)) {
  #   var <- as.character(df[,i])
  #   df_street[[i]] <- search_streets(var, "df")
  #   class_table$streetrisk[i] <- sum(df_street[[i]]$StreetMention, na.rm = TRUE)
  # }
  # 
  # if (missing(writeout)||writeout == TRUE) {
  #   saveRDS(object = df_street, file = paste0(path, df_name, "_PII_4_STREETS_", Sys.Date(), ".RDS"))
  # }
  # 
  # rm(df_street)
  # print("streets completed")
  # print(Sys.time())
  # 
  if (missing(writeout)||writeout == TRUE) {
  saveRDS(object = class_table, file = paste0(path, df_name, "_PII_0_Summary_", Sys.Date(), ".RDS"))
  }

  print("summary completed")
  print(Sys.time())
  
  class_table
  
}