test_file.r

library(ggplot2)
library(maps)
library(tidyverse)
library(ggmap)

### Read and clean data
# Load CSV
birdingData <- read_csv("/Users/danielruskin/Downloads/DNSI Transects 2018-2022 (2).csv")

# Cleanup lat/long: remove degree symbols; convert to numbers
birdingData$Latitude <- as.numeric(
  gsub('˚','',birdingData$Latitude)
)
birdingData$Longitude <- as.numeric(
  gsub('˚','',birdingData$Longitude)
)

# Fix up some weird data
birdingData$Longitude[134] = -70.410519

# Rename field for convenience later on
# (it's annoying to deal with spaces in field names, you have to use quotes)
birdingData <- rename(
  birdingData,
  "perVeg" = "Percent Vegetation (avg)",
  "transectID" = "Transect ID"
)

# Add new Year column
birdingData$Year <- rep(0, nrow(birdingData))
for(rowNum in 1:nrow(birdingData)) {
  row <- birdingData[rowNum,]
  date <- str_split_1(row$Date, '/')
  
  if(length(date) == 1) {
    birdingData$Year[rowNum] = as.numeric(date[1])
  } else {
    birdingData$Year[rowNum] = as.numeric(date[3])
  }
}

# Get differentials for each row
birdingData$perVegDiff <- rep(0, nrow(birdingData))
for(rowNum in 1:nrow(birdingData)) {
  currRow <- birdingData[rowNum,]
  
  prevRows <- filter(
    birdingData,
    Year < currRow$Year,
    transectID == currRow$transectID
  )
  
  if(nrow(prevRows) >= 1) {
    if(nrow(prevRows) > 1) {
      prevRows <- prevRows[order(prevRows$Year, decreasing = TRUE),]
      prevRows <- prevRows[1,]
    }
    
    birdingData$perVegDiff[rowNum] = 
      currRow$perVeg -
      prevRows$perVeg
  }
}

### Draw Map
# Fetch Map
localMap <- c(
  left = min(birdingData$Longitude) - 0.02, 
  bottom = min(birdingData$Latitude)  - 0.02, 
  right = max(birdingData$Longitude) + 0.02, 
  top = max(birdingData$Latitude) + 0.02
)
localMap <- get_stamenmap(localMap, zoom = 14, maptype = "terrain")

# Draw map, plus plotted points
ggmap(localMap) +
  geom_point(
    aes(x = Longitude,y = Latitude, colour = 'red', alpha = 1),
    birdingData
  )