Standardize upon tibble::tibble over dplyr::data_frame calls.

Author: davidski

NAMESPACE

@@ -43,7 +43,6 @@ importFrom(dplyr,arrange)
 importFrom(dplyr,arrange_)
 importFrom(dplyr,bind_rows)
 importFrom(dplyr,case_when)
-importFrom(dplyr,data_frame)
 importFrom(dplyr,filter)
 importFrom(dplyr,filter_)
 importFrom(dplyr,funs)
@@ -100,6 +99,7 @@ importFrom(scales,percent)
 importFrom(stats,quantile)
 importFrom(stats,sd)
 importFrom(stringi,stri_split_fixed)
+importFrom(tibble,add_row)
 importFrom(tibble,as_tibble)
 importFrom(tibble,rownames_to_column)
 importFrom(tibble,tibble)

R/load_data.R

@@ -6,8 +6,8 @@
 #' Preexisting files, if present, will not be overwritten. Also creates an
 #' empty `results` subdirectory as a default location for evaluator output.
 #'
-#' @importFrom dplyr data_frame
 #' @importFrom purrr map_dfr
+#' @importFrom tibble add_row tibble
 #' @param base_directory Parent directory under which to create starter files.
 #' @export
 #' @return A dataframe of the starter filenames, along with a flag on whether a file was copied.
@@ -26,7 +26,7 @@ create_templates <- function(base_directory = "~/evaluator"){
   # copy all the standard CSV files
   res <- c("domains.csv", "qualitative_mappings.csv", "risk_tolerances.csv") %>%
     purrr::map_dfr(
-      ~ dplyr::data_frame(filename = .x,
+      ~ tibble::tibble(filename = .x,
                           copied = file.copy(system.file("extdata", .x,
                                                          package = "evaluator"),
                                              inputs_dir)))

R/utils.R

@@ -13,8 +13,8 @@
 #' }
 check_availability <- function(packages, func) {
   res <- purrr::map_df(packages,
-                       ~ tibble(package = .x,
-                                available = requireNamespace(.x, quietly=TRUE)))
+                       ~ tibble::tibble(package = .x,
+                                        available = requireNamespace(.x, quietly=TRUE)))
   if (sum(res$available) != length(packages)) {
     stop(func, " requires the following packages which are not available: ",
          paste0(res[, ]$package, collapse = ", "), "\n",

inst/rmd/analyze_risk.Rmd

@@ -1,6 +1,6 @@
 ---
-title: "Strategic Information Security Risk Analysis"
-author: "Evaluator toolkit (https://github.com/davidski/evaluator)"
+title: "Strategic Information Risk Analysis"
+author: "Evaluator toolkit (https://evaluator.severski.net)"
 output:
   html_document:
     css: "html-styles.css"
@@ -55,6 +55,7 @@ library(rlang)
 library(psych)
 library(tidyr)
 library(pander)
+library(tibble)
 library(evaluator)
 
 panderOptions('table.split.table', Inf) # allow pander to make pages wide
@@ -145,7 +146,7 @@ mean, and minimum annual losses.
 overall <- simulation_results %>% group_by(simulation) %>% 
                      summarize(ale = sum(ale)) %>% select(ale) %>%
                      ungroup
-data_frame("Value at Risk" = dollar(quantile(overall$ale, c(0.95))),
+tibble::tibble("Value at Risk" = dollar(quantile(overall$ale, c(0.95))),
            "Maximum Loss" = dollar(max(overall$ale)),
            "Mean Loss" = dollar(mean(overall$ale)),
            "Minimum Loss" = dollar(min(overall$ale))

inst/rmd/explore_scenarios.Rmd

@@ -24,6 +24,7 @@ library(scales)
 library(viridis)
 library(ggplot2)
 library(dplyr)
+library(tibble)
 library(evaluator)
 library(extrafont)
 input_directory <- params$input_directory
@@ -59,7 +60,7 @@ custom_percent <- function(x) {
 
 get_loss_table <- function(tid) {
   scenario_data <- simulation_results[simulation_results$scenario_id == tid, ]
-  loss_table <- tibble::data_frame(Category = c("Loss Events / Year", "Loss Magnitude", 
+  loss_table <- tibble::tibble(Category = c("Loss Events / Year", "Loss Magnitude", 
                                                 "Total Loss Exposure"),
                                    Minimum = c(min(scenario_data$loss_events), 
                                                min(scenario_data$sle_min) %>% dollar,