---
output: rmarkdown::github_document
---
```{r pkg-knitr-opts, include=FALSE}
hrbrpkghelpr::global_opts()
```

```{r badges, results='asis', echo=FALSE, cache=FALSE}
hrbrpkghelpr::stinking_badges()
```

```{r description, results='asis', echo=FALSE, cache=FALSE}
hrbrpkghelpr::yank_title_and_description()
```

## What's Inside The Tin

The following functions are implemented:

- `counties_sf`:	Retrieve a U.S. county composite map, optionally with a projection, as a simplefeature
- `usa_sf`:	Retreive a U.S. state composite map, optionally with a projection, as a simplefeature

New ones:

- `points_elided`: Shift points around Alaska and Hawaii to the elided area (by @rdinter)

Some legacy ones:

- `usa_composite`:	Retrieve a U.S. composite map, optionally with a projection
- `counties_composite`:	Retrieve a U.S. county composite map, optionally with a projection

Pre-canned projection strings:

- `us_aeqd_proj`:	Oblique azimuthal equidistant convenience projection
- `us_eqdc_proj`:	Equidistant conic convenience projection
- `us_laea_proj`:	Albers equal-area conic convenience projection
- `us_lcc_proj`:	Lambert conformal conic convenience projection
- `us_longlat_proj`:	Generic long/lat convenience projection

The following data sets are included:

- `system.file("extdata/composite_us_states.geojson.gz", package="albersusa")` 
- `system.file("extdata/composite_us_counties.geojson.gz", package="albersusa")`

Also, the simplefeatures columns and `@data` slot of each `SpatialPolygonsDataFrame` has some handy data you can use (like FIPS codes and state/county population information).

## Installation

```{r install-ex, results='asis', echo=FALSE, cache=FALSE}
hrbrpkghelpr::install_block()
```

## Usage

```{r message=FALSE, fig.retina=2}
library(albersusa)
library(sf)
library(sp)
library(rgeos)
library(maptools)
library(ggplot2)
library(ggalt)
library(ggthemes)
library(viridis)
library(scales)

# current version
packageVersion("albersusa")
```

### Simple features base

```{r message=FALSE, fig.retina=2}
par(mar=c(0,0,1,0))

us_sf <- usa_sf("laea")
plot(us_sf["pop_2012"])

cty_sf <- counties_sf("aeqd")
plot(cty_sf["census_area"])
```

### ggplot2

```{r message=FALSE, warning=FALSE, fig.retina=2}
ggplot() +
  geom_sf(data = us_sf, size = 0.125)

ggplot() +
  geom_sf(data = us_sf, size = 0.125) +
  coord_sf(crs = us_longlat_proj)

ggplot() +
  geom_sf(data = cty_sf, size = 0.0725)

ggplot() +
  geom_sf(data = cty_sf, size = 0.0725) +
  coord_sf(crs = us_longlat_proj)
```

## albersusa Metrics

```{r cloc, echo=FALSE}
cloc::cloc_pkg_md()
```

## Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.