RiskDefSummaryEOP.Rmd

---
title: "Risk Definition Summary"
date: "`r Sys.Date()`"
output: word_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, 
                      message = FALSE,
                      warning = FALSE)
library(googledrive)
library(pacman)
p_load(magrittr, gsubfn, stringr, tidyverse)
```

## Full questionaire results

### Open from DATE 2023 to DATE 2023

[This is the survey form.](https://docs.google.com/forms/d/1GBkgRn6prtdQmsBfJ_NDcbK7dOx_A4TyMcy2eXs9qcI/edit)

```{r getsurvey}
#survey link 
#results https://docs.google.com/spreadsheets/d/1ZAsKj3Yw78DTn6F22QY0hBZnnb19Sopt8F_3OYTh010/edit#gid=1300898964

# this code gets from google drive, need to enter oauth token so probably not bulletproof for all users

# resultfile <- drive_get("https://docs.google.com/spreadsheets/d/1ZAsKj3Yw78DTn6F22QY0hBZnnb19Sopt8F_3OYTh010/edit#gid=1300898964")
# responses <- drive_download(resultfile, type = "csv", overwrite = TRUE) %>%
#   {read.csv(.$local_path)} 

# once file has been downloaded use this
responses <- read.csv("EAFM Risk Assessment Review (Responses).csv",header=T)

# separate question number and element name? numbers are duplicates so just use name

names(responses) <- sub("^X.*\\.\\.\\.","",names(responses))

# take only the elements
elements <- responses[,4:46]

currentelements <- elements[,1:24]
newelements <- elements[,25:43]
  

```

We had `r nrow(responses)` responses.

### Summary of responses by Element

Ordered by most frequent answer

#### Current Risk Elements

```{r plotcurrent, fig.height=10, fig.width=7.5}
# barplot for each column of a dataframe from https://stackoverflow.com/questions/52822840/ggplot2-create-a-barplot-for-every-column-of-a-dataframe

# desired workflow:
# make each column just the first portion, original or alternate
# count each category
# summarize in a bar or pie plot
# currently having difficulty with list structure and purrr
# one column
# element <- names(elements)[1]
# 
# test <- elements[1] |>
#   map_df(str_squish) |> # removes whitespace 
#   #separate(Stock.Assessment.Performance, 
#   #         into = c("version", "description"), sep = ":") 
#   ggplot(aes(x = .data[[element]])) +
#   geom_bar() +
#   theme_bw() +
#   scale_x_discrete(labels = function(x) str_wrap(x, width = 20)) +
#   labs(title = element)

plotdef <- function(elements){
  for(i in 1:length(names(elements))){
    n <- names(elements)[i]
    barpl <- elements[i] |>
      map_df(str_squish) |> # removes whitespace
      filter(.data[[n]]!= "") |>
      ggplot(aes(x = reorder(.data[[n]],.data[[n]], function(x)-length(x)))) +
      geom_bar() +
      theme_bw() +
      scale_x_discrete(labels = function(x) str_wrap(x, width = 20)) +
      xlab(NULL) +
      labs(title = n)
    cat("\n")
    print(barpl)
    cat("\n")
  }
  
}

plotdef(currentelements)

```

#### Potentially New Risk Elements

```{r plotnew, fig.height=10, fig.width=7.5}
plotdef(newelements)
```

```{r plotflip, fig.height=10, fig.width=7.5}

plotdefflip <- function(elements){
  for(i in 1:length(names(elements))){
    n <- names(elements)[i]
    barpl <- elements[i] |>
      map_df(str_squish) |> # removes whitespace
      filter(.data[[n]]!= "") |>
      ggplot(aes(x = reorder(.data[[n]],.data[[n]], function(x)+length(x)))) +
      geom_bar() +
      theme_bw() +
      scale_x_discrete(labels = function(x) str_wrap(x, width = 60)) +
      xlab(NULL) +
      coord_flip() +
      labs(title = n)
    cat("\n")
    print(barpl)
    cat("\n")
  }
  
}

longnewelements <- elements[,41:42]

plotdefflip(longnewelements)

```