mapview.Rmd

---
title: "mapview"
author: "Christian Födermayr"
date: "1/27/2019"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```
##Load Packages
```{r, include=FALSE}
library(dplyr)
library(magrittr)
library(ggplot2)
# never knew there was an gdla r package --> but awesome!
library(rgdal)
library(jsonlite)
library(leaflet)
```
## Set Working directory
```{r}
#setwd('stat-prog-2019')
```

## Read provided shapefiles
Thanks for natural erath data to provide good and high quality geodata all over the world (http://naturalearthdata.com/)
```{r}
eustates <- readOGR("shp/world/world_countries.shp",
  layer = "world_countries", GDAL1_integer64_policy = TRUE)
```
## add datat to shapefile

You can take any data you want, if it has at least a isocode column with iso2 values in it (PL, AT,...)

```{r}
data = read.csv(file="data/clean_euro_data/unemployed_persons_data.csv")
# uppercase isocode for matching with geometries
data %<>% 
  mutate(isocode = toupper(isocode))
# use spatial merge
eustates = sp::merge(eustates, data, by="isocode",duplicateGeoms = TRUE)
  
```


## Generate Map

You can easily adapt this tooltip regarding two things:
- Define an html string
- select the correct columns

```{r}
# define labels
labels <- sprintf(
  "<strong>%s</strong><br/>%s: %g",
  eustates$label, eustates$WSTATUS, eustates$Value
) %>% lapply(htmltools::HTML)

leaflet(eustates) %>%
  # set extent for europe
  fitBounds(-15.117188, 32.101190, 39.199219,70.844673) %>%
  addPolygons(color = "#444444", weight = 1, smoothFactor = 0.5,
    opacity = 1.0, fillOpacity = 0.5,
    fillColor =  ~colorQuantile("YlOrRd", Value)(Value),
    highlightOptions = highlightOptions(color = "white", weight = 2,
      bringToFront = TRUE),
    label = labels,
    labelOptions = labelOptions(
      style = list("font-weight" = "normal", padding = "3px 8px"),
      textsize = "15px",
      direction = "auto"))
```