Data Visualization

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# Data Visualization
## Making outline maps
### Andrew Irwin, <a href="mailto:a.irwin@dal.ca" class="email">a.irwin@dal.ca</a>
### Math & Stats, Dalhousie University
### 2021-03-15 (updated: 2021-03-06)

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# Plan

* Kinds of maps

* Basic maps

* Adding points

* Shading areas

* Projections

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### Map libraries

* `ggmap` (part of tidyverse)

* Many other libraries 
  * `maps`
  * `mapproj` for making projections of the Earth's surface
  * `mapdata` with maps of China and Japan
  * `leaflet` for drawing raster or tiled maps (next lesson)

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### Kinds of maps

* Coastlines and political boundaries

* Natural features (rivers, water bodies)

* Points and filled regions on maps

* How to represent latitude and longitude from a sphere on a screen?

* Tiled maps

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### A basic map

```r
library(tidyverse)
WorldData <- map_data('world')  
m1 <- ggplot(WorldData, aes(map_id=region)) + 
        geom_map(map = WorldData,
                 aes(x = long, y = lat),
                 fill = "lightgray", colour = "#7f7f7f", 
                 alpha = 0.5, size=0.5) +
  theme_bw()
```

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### A basic map

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### Colour countries

```r
values <- tibble( region = WorldData %>% pull(region) %>% unique())
values <- values %>% mutate(value = runif(nrow(values)))
m2 <- ggplot(values, aes(map_id = region)) + 
        geom_map(aes(fill = value),
                 map = WorldData,
                 colour = "lightgray", 
                 alpha = 1, size=0.5) +
   expand_limits(x = c(-180,180), y = c(-80,80)) +
   theme_bw()
```

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### Colour countries

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### Show only some countries

```r
values <- tibble( region = c("Canada", "China", "Chile"),
                  value  = c(1, 2, 3))
m3 <- ggplot(values, aes(map_id = region)) + 
        geom_map(aes(fill = value),
                 map = WorldData,
                 colour = "lightgray", 
                 alpha = 1, size=0.5) +
   expand_limits(x = c(-180,180), y = c(-80,80))+
  theme_bw()
```

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### Show some countries

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### Colour some countries

```r
values <- tibble( region = c("Canada", "China", "Chile"),
                  value  = c(1, 2, 3))
m4 <- ggplot(WorldData, aes(map_id = region)) + 
        geom_map(map = WorldData,
                 colour = "lightgray", fill = "darkgray",
                 alpha = 1, size=0.5) +
        geom_map(aes(fill = value), 
                 data = values, map = WorldData) + 
   expand_limits(x = c(-180,180), y = c(-80,80))+
  theme_bw()
```

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### Colour some countries

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### Add points

```r
library(rnaturalearth)
library(rnaturalearthdata)
library(ggrepel)
canada <- ne_countries(country = "canada", scale = "large", 
                       returnclass = "sf")
sites <- tibble(longitude = c(-81, -80), latitude = c(44, 45), 
                label = c("A", "B"))
m5 <- ggplot(data = canada) +
      geom_sf() +
      geom_point(data = sites, 
                 aes(x = longitude, y = latitude), 
                 size = 4, shape = 21, fill = "darkred") +
  geom_label_repel(data = sites, 
                   aes(x = longitude, y = latitude, 
                       label = label)) + 
  coord_sf(xlim = c(-140,-50), ylim = c(42,65))
```

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### Add points

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### Projections

```r
library(mapproj)
CanadaData <- map_data('world', 'Canada')  
m6 <- ggplot(CanadaData, aes(map_id=region)) + 
        geom_map(map = CanadaData,
                 aes(x = long, y = lat),
                 fill = "lightgray", colour = "#7f7f7f", 
                 alpha = 0.5, size=0.5) +
  theme_bw() +
  coord_map("lambert", lat0 = 42, lat1 = 50)
```

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### Projections

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### Polar regions

```r
library(mapproj)
m7 <- ggplot(WorldData, aes(map_id=region)) + 
        geom_map(map = WorldData,
                 aes(x = long, y = lat),
                 fill = "lightgray", colour = "#7f7f7f", 
                 alpha = 0.5, size=0.5) +
  theme_bw() +
  coord_map("perspective", 2, orientation=c(-90, -90, 90))
```

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### Polar regions

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### Summary

* Make a basic map

* Select all or some countries

* Fill regions with colour

* Add points and labels

* Use a different projection

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# Further reading

* Course notes

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## Task

* Bonus task - make some simple maps based on course notes