Syria_Jordan_Flow.Rmd

---
title: "Syria-Jordan_Flow"
output: html_document
---

## R Markdown



```{r}


# if you chose to pull directly from the site, use the below syntax for your specific country.  
library(maptools)
library(raster)
library(ggplot2)


# grab some of the key shapefile we will need. 
sy_border <- getData("GADM", country="SY", level=0)
sy_map <- getData("GADM", country="SY", level=1)

jo_border <- getData("GADM", country="JO", level=0)
jo_map <- getData("GADM", country="JO", level=1)

# take a look at the shapefiles we just pulled 
plot(jo_map)
plot(sy_map)
```



```{r}
sy_map@data$NAME_1

```



## Read in Key files 


```{r}

# this is how we load in a shapefile from our computer.  This has a little more detail for internal admin borders
syria_border <- readRDS("C:/Users/john.mataya/Desktop/Datasets/Syria Data/spatial_data/SYR_adm2.rds")
 
library(readr)
Jordan <- read_csv("C:/Users/john.mataya/Desktop/Datasets/Syria Data/UNHRC/Custom_Camp/Syria_ref_in_Jordan_Origins.csv", col_types = cols(Lat.x = col_number(), Lat.y = col_number(), Lon.x = col_number(), Lon.y = col_number(), Refugees = col_number()))
#delete that row with nans - it isn't needed 
Jordan <- Jordan[-c(15), ]

head(Jordan)

```



```{r}
# let's plot our data showing to and drom destinations 

# plot the two countries together and use the curved arrows.  
ggplot() + geom_polygon(data = sy_map, aes(long, lat, group=group), fill = 'whitesmoke') + geom_path(data=sy_map, aes(long,lat, group=group), color="grey", size=0.1) + geom_polygon(data = jo_border, aes(long, lat, group=group), fill = 'whitesmoke') + geom_curve(data = Jordan, aes(x = Lon.x, y = Lat.x, xend = Lon.y, yend = Lat.y, size = Refugees), curvature = -0.2, arrow = arrow(length = unit(0.01, 'npc')))


```



```{r}
sy_jordan <- read_csv("C:/Users/john.mataya/Desktop/Datasets/Syria Data/UNHRC/Custom_Camp/Syria_ref_in_Jordan_Origins.csv")

jo_df <- read_csv("C:/Users/john.mataya/Desktop/Datasets/Syria Data/UNHRC/Custom_Camp/Jordan_custom_camp.csv", 
     col_types = cols(Lat = col_number(), 
         Lon = col_number()))

sy_jordan$Destination <- NULL 
sy_jordan <- sy_jordan[, -c(3:6)] # delete columns 5 through 
sy_jordan <- sy_jordan[-c(15), ]

sy_jordan


```



And we can join our Refugee count data to the admin areas so that we can visualise it.

You can use the code below to join data from a csv to a shapefile, based on a common spatial value, here it is administrative boundaries, but it could be anything.

```{r}

sy_map@data$id <- rownames(sy_map@data)

# rename the columns in my sy_jordan dataframe to do the join
colnames(sy_jordan) <- c("NAME_1", "Refugees")

# perform the join 
sy_map@data <- join(sy_map@data, sy_jordan, by="NAME_1")

# this step was necessary because for some reason the join was creating a single NA for the number of refgueess in Al-Hasakah provence.  Here I'm manually putting in the number by selecting the df[row number, col number] = value 
sy_map@data[1, 15] = 5129 

syria_df <- fortify(sy_map)
syria_df <- join(syria_df, sy_map@data, by="id")

syria_df
```

```{r}
ggplot() + geom_polygon(data = syria_df, aes(x = long, y = lat, group = group, fill = Refugees), color = "black", size = 0.25) 

```




```{r}
p <- ggplot() + geom_polygon(data = syria_df, aes(x = long, y = lat, group = group, fill = Refugees), color = "black", size = 0.25) + scale_fill_distiller(name="Refugees", direction = 1, palette = "Reds", breaks = pretty_breaks(n = 5)) + 
  labs(title="Origins of Syrian Refugees in Jordan")
p


```

```{r}

p <- ggplot() + geom_polygon(data = syria_df, aes(x = long, y = lat, group = group, fill = Refugees), color = "black", size = 0.25) + scale_fill_distiller(name="Refugees", direction = 1, palette = "Reds", breaks = pretty_breaks(n = 5)) + 
  labs(title="Origins of Syrian Refugees in Jordan")

p <- ggplot() + geom_polygon(data = syria_df, aes(x = long, y = lat, group = group, fill = Refugees), color = "black", size = 0.25) + 
  scale_fill_distiller(name="Refugees", direction = 1, palette = "Reds", breaks = pretty_breaks(n = 5)) +
  labs(title="Origins of Syrian Refugees in Jordan") + geom_path(data=sy_border, aes(long,lat, group=group), size=1) + 
  geom_path(data=sy_map, aes(long,lat, group=group), color="grey", size=0.1) + 
  geom_polygon(data = jo_map, aes(long, lat, group=group), fill = 'whitesmoke') + 
  geom_path(data=jo_border, aes(long,lat, group=group), size=1) + 
  geom_path(data=jo_map, aes(long,lat, group=group), color="grey", size=0.1) 



```



```{r}

# plot the two countries together and use the curved arrows.  
p <- p + geom_curve(data = Jordan, aes(x = Lon.x, y = Lat.x, xend = Lon.y, yend = Lat.y), curvature = -0.2, arrow = arrow(length = unit(0.01, 'npc')))
```

```{r}

# let's add cities - pull the lat and lon from google maps 

city <- c('Aleppo','Al-Hasaka', 'Homs', 'Damascus', 'Lattakia', 'Amman')
Lat <- c(36.1956095, 36.5044741,  34.7302927, 33.5074706, 35.549496, 31.8360368)
Lon <- c(37.0551996, 40.7085281,  36.6420627, 36.2478761, 35.911248, 35.6674449) 	 	

cities <- data.frame(city, Lat, Lon)

head(cities)
str(cities)
```

```{r}
# add the city names to the map 
p + geom_point(data = cities, aes(x = Lon, y = Lat), size = 2, alpha = 0.5) + geom_text(data=cities, hjust=0.5, vjust=-0.5, aes(x=Lon, y=Lat, label=city), colour="black", size=3, alpha = 0.6)


```
```{r}

# just city points 

p <- p + geom_point(data = cities, aes(x = Lon, y = Lat), size = 2, alpha = 0.5)

p
```

We can use this bit of code to clean up the map so it is ready to be used in publication type format. 
```{r}
theme_opts<-list(theme(panel.grid.minor = element_blank(),
                       panel.grid.major = element_blank(),
                       panel.background = element_blank(),
                       plot.background = element_blank(),
                       axis.line = element_blank(),
                       axis.text.x = element_blank(),
                       axis.text.y = element_blank(),
                       axis.ticks = element_blank(),
                       axis.title.x = element_blank(),
                       axis.title.y = element_blank(),
                       plot.title = element_blank()))
```



```{r}

p + theme_opts
```


Let's create a little bar chart of places in Jordan with Syrian Refugees
```{r}


```