---
title: "Maps"
output:
  word_document: default
  html_notebook: default
  pdf_document: default
---


```{r}
library(pacman)

p_load(tidyverse, nasaweather)

atmos	                       # Atmospheric data.
borders <- ungroup(borders)	 # Country borders, ungroup fixes a problem with knitting.
elev	                       # Elevation.
glaciers                     # Glacier locations
storms	                     # Storm tracks data

```


```{r}
p <- storms %>% ggplot(aes(y = wind, x = pressure, color = type)) +
  geom_point(alpha = 0.3) 

p

p + geom_smooth()
```


All storms

Determine the part of the map to plot the storm paths on.  Compute the minimum and maximum values of the latitude and longitude.

```{r}
bbox <- storms %>%
  select(lat, long) %>%
  map_df(range)          # using the purrr R package

bbox
```

```{r}
base_map <- map_data("world") %>% ggplot( aes(x = long, y = lat)) +
  geom_path(aes(group = group), color = "black", size = 0.1) +
  lims(x = bbox$long, y = bbox$lat)

storms <- storms %>% 
  unite("the_date", c(year, month, day), sep="-", remove="FALSE") %>%
  mutate(the_date = lubridate::ymd(the_date))

base_map + geom_path(data = storms, aes(color = name, alpha = 0.01, size = wind),
                     arrow = arrow(length = unit(0.005, "inches"))) +
  facet_wrap(~year) +
  theme(legend.position = "none")

```

Only Tropical Storms

```{r}
base_map <- map_data("world") %>% ggplot(aes(x = long, y = lat)) +
  geom_path(aes(group = group), color = "black", size = 0.1) +
  lims(x = bbox$long, y = bbox$lat)

base_map

storms2 <- storms %>% filter(type == "Tropical Storm") 

base_map + geom_path(data = storms2, aes(color = name, alpha = 0.01, size = wind), arrow = arrow(length = unit(0.005, "inches"))) +
  facet_wrap(~year) +
  theme(legend.position = "none")

```


Some futher maps

```{r}
library(maps)

state <- map_data("state")
county <- map_data("county")
usa <- map_data("usa")
world <- map_data("world")
```

states

```{r}
state
```

```{r}
gg <- ggplot()
gg <- gg + geom_map(data=state, map=state,
                     aes(long, lat, map_id=region),
                     color="#2b2b2b", fill=NA, size=0.15)
gg
```


```{r}
gg <- ggplot()
gg <- gg + geom_map(data=county, map=county,
                     aes(long, lat, map_id=region),
                     color="#2b2b2b", fill=NA, size=0.15)
gg

gg <- ggplot()
gg <- gg + geom_map(data=state, map=state,
                     aes(long, lat, map_id=region),
                     color="#2b2b2b", fill=NA, size=0.15)
gg

gg <- ggplot()
gg <- gg + geom_map(data=usa, map=usa,
                     aes(long, lat, map_id=region),
                     color="#2b2b2b", fill=NA, size=0.15)
gg
```

```{r}
ggplot() + borders("county", c("washington", "california","texas"))
```