File	Date	Author	Commit
R	2018-06-01	boB Rudis	[16f1e0] initial commit
README_files	2018-06-01	boB Rudis	[16f1e0] initial commit
inst	2018-06-01	boB Rudis	[16f1e0] initial commit
man	2018-06-01	boB Rudis	[16f1e0] initial commit
tests	2018-06-01	boB Rudis	[16f1e0] initial commit
.Rbuildignore	2018-06-01	boB Rudis	[16f1e0] initial commit
.codecov.yml	2018-06-01	boB Rudis	[16f1e0] initial commit
.gitignore	2018-06-01	boB Rudis	[16f1e0] initial commit
.travis.yml	2018-06-01	boB Rudis	[16f1e0] initial commit
DESCRIPTION	2018-06-02	boB Rudis	[00773b] Fixed DESCRIPTION
LICENSE	2018-06-01	boB Rudis	[16f1e0] initial commit
NAMESPACE	2018-06-01	boB Rudis	[16f1e0] initial commit
NEWS.md	2018-06-01	boB Rudis	[16f1e0] initial commit
README.Rmd	2018-06-01	boB Rudis	[16f1e0] initial commit
README.md	2018-06-01	boB Rudis	[16f1e0] initial commit
spdorling.Rproj	2018-06-01	boB Rudis	[16f1e0] initial commit

Read Me

---
output: rmarkdown::github_document
---

# spdorling

Create Dorling Cartograms from Contiguous Region Shapefiles

## Description

Create Dorling Cartograms from Contiguous Region Shapefiles

## What's Inside The Tin

- `dorling_from_sp`:	Compute center coordinates, circle radii and Dorling polygons from input polygons and values

The following functions are implemented:

## Installation

```{r eval=FALSE}
devtools::install_github("hrbrmstr/spdorling")
```

```{r message=FALSE, warning=FALSE, error=FALSE, include=FALSE}
options(width=120)
knitr::opts_chunk$set(fig.retina=2)
```

## Usage

```{r message=FALSE, warning=FALSE, error=FALSE}
library(spdorling)

# current verison
packageVersion("spdorling")

```

### Lower 48 U.S.A.

```{r message = FALSE}
library(albersusa) # hrbrmstr/albersusa
library(hrbrthemes)
library(tidyverse)

usa <- albersusa::usa_composite(proj = "laea")
usa <- subset(usa, !(name %in% c("Alaska", "Hawaii", "District of Columbia")))

set.seed(2018)
usa$val <- sample(10000, 48)

dor <- dorling_from_sp(usa, value=usa$val, quiet=FALSE)

discs_df <- fortify(dor$discs)

as_data_frame(dor$xy) %>% 
  set_names(c("lng", "lat")) %>% 
  mutate(iso2c = usa$iso_3166_2) -> usa_labs

ggplot() +
  geom_polygon(
    data = discs_df, aes(long, lat, group=group), 
    size=0.125, color="#2b2b2b", fill="#00000000"
  ) +
  geom_text(data = usa_labs, aes(lng, lat, label=iso2c), size=2) +
  coord_fixed() +
  labs(x=NULL, y=NULL) +
  theme_ipsum_rc(grid="") +
  theme(axis.text=element_blank())
```

### Swiss Cantons

```{r}
library(sp)
library(rgdal)

readOGR(
  system.file("extdat", "swiss-cantons.json", package="spdorling"),
  verbose = FALSE,
  stringsAsFactors = FALSE
) -> cantons

# convert it to equal area
SpatialPolygonsDataFrame(
  spTransform(cantons, CRS("+proj=aea +lat_1=45.96 +lat_2=47.50 +lon_0=8.34")),
  data = cantons@data
) -> cantons

set.seed(2018)
cantons$val <- sample(10000, nrow(cantons@data))

dor <- dorling_from_sp(cantons, value=cantons$val, quiet=FALSE)

discs_df <- fortify(dor$discs)

as_data_frame(dor$xy) %>% 
  set_names(c("lng", "lat")) %>% 
  mutate(name = cantons$name) -> cantons_labs

ggplot() +
  geom_polygon(
    data = discs_df, aes(long, lat, group=group), 
    size=0.125, color="#2b2b2b", fill="#00000000"
  ) +
  geom_text(data = cantons_labs, aes(lng, lat, label=name), size=2) +
  coord_fixed() +
  labs(x=NULL, y=NULL) +
  theme_ipsum_rc(grid="") +
  theme(axis.text=element_blank())
```