In ecodata1/whpt: Predict WHPT scores

# Don't show R code in output
knitr::opts_chunk$set(echo = FALSE)
# Load useful libraries
library(tidyr)
library(dplyr)
library(purrr)
library(rlang)
library(utils)
library(readr)
library(magrittr)
library(ggplot2)
library(ggmap)
library(ggrepel)
library(leaflet)

---

Location Code: r params$data[, 1]

Sampled date: r format(params$data$date_taken, '%d %B, %Y')

Reason for visit: Vulnerable site

bbox <- c(left = params$data$longitude - 0.02,
          bottom = params$data$latitude - 0.01, 
          right = params$data$longitude + 0.02,
          top = params$data$latitude + 0.01)
 map <- get_stamenmap( bbox = bbox, zoom = 14)
map <- ggmap(map, extent = "normal") +  
  geom_point(aes(x = longitude, y = latitude), 
             data = params$data, colour = "red", size = 2) + theme_nothing()
map

Most Recent RBMP Assessment: r paste(params$consistency_table[, c("Typical ASPT Class","Typical NTAXA Class")], collapse = ", ") (r paste(params$consistency_table[, c("Reported WHPT Class Year")]))

Our Assessment: r paste(params$consistency_table[, c("assessment")])

Proposed Action: r paste(params$consistency_table[, c("action")])

Interpretation

<<< Please delete and enter your interpretation >>>

Sample Details

Reported Date: r format(Sys.time(), '%d %B, %Y')

Report By: <<< Please delete and update >>>

Sampler: <<< Please delete and update >>>

NGR: r params$data[, 8]

Water Body: <<< Please delete and update >>>

ecodata1/whpt documentation built on Sept. 27, 2024, 9:02 p.m.