Play around some more

bird_per_loc_scythe.R

@@ -4,9 +4,10 @@ library(sf)
 library(mapview)
 library(dplyr)
 library(ggrepel)
-
-#Set working directory
-setwd("/Users/mjo-air/Programming/R")
+library(grid)
+library(tidyverse)
+library(shadowtext)
+library(magrittr)
 
 #Choose Scythebird export
 locations <- read.csv(file=file.choose(), stringsAsFactors = F)[,c('Location.1', 'Common', 'Number')]
@@ -15,8 +16,6 @@ locations <- read.csv(file=file.choose(), stringsAsFactors = F)[,c('Location.1',
 locations$Number<-gsub(">","",as.character(locations$Number))
 locations$Number<-gsub("~","",as.character(locations$Number))
 
-
-
 #Do a tibblings
 locations <- as_tibble(locations)
 
@@ -30,6 +29,7 @@ per_location_by_species <- locations %>%
   arrange(desc(sum))
 
 per_location_by_species <- subset(per_location_by_species, Common!="Stockente")
+per_location_by_species$Location.1 <- gsub("\\s*\\[[^\\)]+\\]","",as.character(per_location_by_species$Location.1))
 
 #Bar plot
 ggplot(per_location_by_species, aes(sum, Common, fill = Location.1)) +
@@ -38,10 +38,4 @@ ggplot(per_location_by_species, aes(sum, Common, fill = Location.1)) +
 
 print(per_location_by_species)
 
-# Create mapview map
-locations_sf <- st_as_sf(per_location, coords = c("COORD_LON", "COORD_LAT"), crs = 4326)
-mapview(locations_sf, zcol="sum")
-
-print(locations)
-
 

birding_trip_ornitho.R

@@ -7,15 +7,15 @@ library(ggrepel)
 library(magrittr)
 
 #Google API key
-register_google(key = "")
+#register_google(key = "")
 
 #Google Maps view
-stauteich_3 <- get_googlemap("bielefeld stauteich III", zoom = 14, maptype = "satellite")
+stauteich_3 <- get_googlemap("Obersee Bielefeld", zoom = 14, maptype = "satellite")
 
 #Set working directory
-setwd("/Users/mjo-air/Programming/R")
+#setwd("/Users/mjo-air/Programming/R")
 
-#Choose Ornihto export
+#Choose Ornitho export
 locations <- read.csv(file=file.choose(), sep = "\t")[,c('COORD_LAT', 'COORD_LON', 'TOTAL_COUNT', 'NAME_SPECIES', 'PLACE')]
 
 #Remove first row
@@ -30,22 +30,22 @@ locations$COORD_LAT %<>% as.double
 locations$TOTAL_COUNT %<>% as.integer
 
 #Total number of birds per location
-#per_location <- locations %>% 
- # group_by(PLACE, COORD_LAT, COORD_LON) %>% 
-  #summarise(sum = sum(TOTAL_COUNT)) %>% 
-  #arrange(desc(sum))
-
-#Total number of birds if Psalm is stupid
-per_location <- locations %>%
-  group_by(PLACE) %>%
-  mutate(across(starts_with("COORD_"), last)) %>%
-  ungroup()
-
-per_location <- per_location %>% 
+per_location <- locations %>% 
   group_by(PLACE, COORD_LAT, COORD_LON) %>% 
   summarise(sum = sum(TOTAL_COUNT)) %>% 
   arrange(desc(sum))
 
+#Total number of birds if Psalm is stupid 1
+#per_location <- locations %>%
+#  group_by(PLACE) %>%
+#  mutate(across(starts_with("COORD_"), last)) %>%
+#  ungroup()
+
+#Total number of birds if Psalm is stupid 2
+#per_location <- per_location %>% 
+#  group_by(PLACE, COORD_LAT, COORD_LON) %>% 
+#  summarise(sum = sum(TOTAL_COUNT)) %>% 
+#  arrange(desc(sum))
 
 #Remove text in brackets
 per_location$PLACE <- gsub("\\s*\\[[^\\)]+\\]","",as.character(per_location$PLACE))

birding_unique.R

@@ -8,23 +8,17 @@ library(grid)
 library(tidyverse)
 library(shadowtext)
 
-#Working directory
-setwd("/Users/mjo-air/Programming/R")
-
 #Colours
 BLUE <- "#076fa2"
 
-#API key for Google Maps
-register_google(key = "")
-
 #Map of Bielefeld, centered on Stauteich 3
-stauteich_3 <- get_googlemap("bielefeld stauteich III", zoom = 14, maptype = "satellite")
+bielefeld <- get_googlemap("Tieplatz Heepen Bielefeld", zoom = 13, maptype = "satellite")
 
 #The variable used to get the sum of all birds that were seen at a particular location
 #all_birds_sum_var <- read.csv("birding.csv", stringsAsFactors = F, na.strings="`")[,c('Location.1', 'Longitude', 'Latitude', 'Number', 'Common')]
 
 #The variable used to get the sum of unique birds that were seen at a particular location
-unique_birds_sum_var <- read.csv("birding.csv", stringsAsFactors = F, na.strings="`")[,c('Location.1', 'Longitude', 'Latitude', 'Common')]
+unique_birds_sum_var <- read.csv(file=file.choose(), stringsAsFactors = F, na.strings="`")[,c('Location.1', 'Longitude', 'Latitude', 'Common')]
 
 #Convert to tibble
 locations <- as_tibble(unique_birds_sum_var)
@@ -32,6 +26,9 @@ locations <- as_tibble(unique_birds_sum_var)
 #Find how many unique sightings there are in this location
 per_location_unique <- unique(locations)
 
+#Remove text in brackets
+per_location_unique$Location.1 <- gsub("\\s*\\[[^\\)]+\\]","",as.character(per_location_unique$Location.1))
+
 #Do some grouping
 per_location <- per_location_unique %>% 
   group_by(Location.1, Longitude, Latitude) %>% 
@@ -55,7 +52,7 @@ ggplot(per_location) +
   geom_col(aes(sum, Location.1), fill = BLUE, width = 0.6)
 
 #Google Maps map
-ggmap(bw_map) +
+ggmap(bielefeld) +
 geom_point(data = per_location,
            aes(x = Longitude, y = Latitude, size=sum),
            color = "red", alpha = 0.5) +