Map for world map.Rmd

---
title: "Map for world map"
author: "Grace Kim"
date: "11/30/2019"
output: html_document
---
This was a practice rmd for the world map leaflet, took many tries to get it fully done but it's here for everyone to enjoy!


```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

# downloaded our various libraries

library(leaflet)
library(readr)
library(nnet)
library(rgdal)
library(janitor)
library(tidyverse)
```


```{r world map data cleaning}

# Read in the world religion data

world<- read_csv("Korea/raw-data/World_Religion_Data.csv", col_types = cols(
  Country = col_character(),
  Christian = col_double(),
  Muslim = col_double(),
  Unaffiliated = col_double(),
  Hindu = col_double(),
  Buddhist = col_double(),
  Folk = col_double(),
  Other = col_double(),
  Jewish = col_double()
)) %>% 
  clean_names()

# added a column to this data that notes which religion is the highest for each country
# saved into a new data set that will have only country names and the religions
world_clean <- world %>% 
  mutate(highest_religion = apply(world[,-(1)],1,which.max)) %>% 
  select(country,highest_religion)

# change column names to join with other data set later
colnames(world)[1]<-"NAME"

# Read this shape file with the rgdal library. 
world_spdf <- readOGR("Korea/raw-data/world_shape_file/TM_WORLD_BORDERS_SIMPL-0.3.shp", stringsAsFactors = F)
world_spdf@data[world_spdf@data$ISO2 == "AX","NAME"] <- "Aland Islands"

world_spdfog <- readOGR("Korea/raw-data/world_shape_file/TM_WORLD_BORDERS_SIMPL-0.3.shp", stringsAsFactors = F)

# joined the various religion data of the world with the shp file

world_spdf@data <- inner_join(world_spdf@data,world,by = "NAME")

```

```{r mappy time}
# created the yellow green blue color palette for the leaflet map

pal <- colorNumeric("YlGnBu", world_spdf@data$christian)

# the text popup labels for every country
# lists the religious percentages and the population and country name

mytext <- paste(
    "Country: ", world_spdf@data$NAME,"<br/>", 
    "Religion: ", world_spdf@data$christian, "<br/>", 
    "Population: ", round(as.numeric(as.character(world_spdf@data$POP2005)), 2), 
    sep="") %>%
  lapply(htmltools::HTML)

# actual leaflet!!!
# added the various nation tiles and the setview to the specific region on the map

leaflet(world_spdf)%>% 
  addTiles()%>%
  setView(lat=10, lng=0 , zoom=2) %>%
  
  # each polygon shape for each nation is noted below
  
  addPolygons(stroke = FALSE, 
              fillOpacity = 0.9, 
              smoothFactor = 0.5, 
              color = ~pal(christian),
              label = mytext,
              labelOptions = labelOptions( 
                style = list("font-weight" = "normal", padding = "3px 8px"), 
                textsize = "13px", 
                direction = "auto"
            )) %>% 
  
  # legend for the various religious scales on the bottom right
  
  addLegend("bottomright", 
            pal = pal, 
            values = ~christian,
            title = "Religion",
            opacity = 1)
```


```{r}
# practice graph for the world v.s. south korea grouped barplot
# use the rds file from the data cleaning rscript

vertical_world =  read_rds("Korea/world.rds")

# not much data wrangling from here, just need to use ggplot and have the groups set
# using geom_bar position dodge and etc.

ggplot(vertical_world, aes(x = key, y=value, fill = country))+ 
            geom_bar(position="dodge", stat="identity")+
            labs(x = "Religion",
                 y = "Percentages of Religious Followers",
                 fill = "",
                 title = "The Religions of the World vs. South Korea")  
```