---
output: rmarkdown::github_document
editor_options: 
  chunk_output_type: console
---
```{r ugh, echo=FALSE, message=FALSE, warning=FALSE, error=FALSE, include=FALSE}
knitr::opts_chunk$set(message=FALSE, warning=FALSE, fig.retina=2)
options(width=120)
```

[![Travis-CI Build Status](https://travis-ci.org/hrbrmstr/statebins.svg?branch=master)](https://travis-ci.org/hrbrmstr/statebins)

# statebins

Create 'U.S.' Uniform Square State Cartogram Heatmaps

## What's in the tin?

The following functions are implemented:

- `statebins`: Creates "statebin" charts in the style of http://bit.ly/statebins 
- `geom_statebins`: A statebins Geom (WIP!)
- `theme_statebins`: Base statebins theme

## Installation

```{r install, eval=FALSE}
devtools::install_github("hrbrmstr/statebins")
```

## NOTE

Due to a number of things, this is dependent on the _development_ version of ggplot2 and now identifies that in the `DESCRIPTION` metadata, _including_ a `Remotes:` field (which will be removed when this & ggplot2 hit CRAN).

## Usage

All of the following examples use the [WaPo data](http://www.washingtonpost.com/wp-srv/special/business/states-most-threatened-by-trade/states.csv?cache=1). It looks like the columns they use are scaled data and I didn't take the time to figure out what they did, so the final figure just mimics their output (including the non-annotated legend).

```{r setup}
library(statebins)
library(cdcfluview)
library(hrbrthemes)
library(tidyverse)

# current verison
packageVersion("statebins")
```

### The original wapo data

```{r original}
adat <- suppressMessages(read_csv(system.file("extdata", "wapostates.csv", package="statebins")))

mutate(
  adat, 
  share = cut(avgshare94_00, breaks = 4, labels = c("0-1", "1-2", "2-3", "3-4"))
) %>% 
  statebins(
    value_col = "share", 
    ggplot2_scale_function = scale_fill_brewer,
    name = "Share of workforce with jobs lost or threatened by trade"
  ) +
  labs(title = "1994-2000") +
  theme_statebins()
```

### Continuous scale, legend on top

```{r continuous}
statebins(
  adat, value_col = "avgshare01_07",
  name = "Share of workforce with jobs lost or threatened by trade",
  palette = "OrRd", direction = 1
) +
  labs(x="2001-2007") +
  theme_statebins(legend_position="top")
```

### Continuous scale, no legend

```{r continuous_noleg}
statebins(adat, value_col = "avgshare08_12", palette = "Purples") +
  labs(x="2008-2010") +
  theme_statebins(legend_position = "none") 
```

### Mortality data (has Puerto Rico)

```{r mort}
# from: http://www.cdc.gov/nchs/fastats/state-and-territorial-data.htm

dat <- suppressMessages(read_csv(system.file("extdata", "deaths.csv", package="statebins")))

statebins(dat, value_col = "death_rate", name="Per 100K pop") +
  labs(title="Mortality Rate (2010)") +
  theme_statebins()
```

### Fertility data

```{r fert}
statebins(dat, value_col="fertility_rate", name="Per 100K pop", palette="PuBuGn") +
  labs(title="Fertility Rate (2010)") +
  theme_statebins()
```

### Manual - perhaps good for elections?

```{r manual}
election_2012 <- suppressMessages(read_csv(system.file("extdata", "election2012.csv", package="statebins")))

mutate(election_2012, value = ifelse(is.na(Obama), "Romney", "Obama")) %>% 
  statebins(
    font_size=4, dark_label = "white", light_label = "white",
    ggplot2_scale_function = scale_fill_manual,
    name = "Winner",
    values = c(Romney = "#2166ac", Obama = "#b2182b")
  ) +
  theme_statebins()
```

### Rounded rects!

You can pass in a `grid::units()` call for the `radius` parameter.

Slight curves:

```{r rounded}
data(USArrests)

USArrests$state <- rownames(USArrests)
statebins(USArrests, value_col="Assault", name = "Assault", round=TRUE) +
  theme_statebins(legend_position="right")
```

Circles!

```{r rounded2} 
statebins(USArrests, value_col="Assault", name = "Assault", round=TRUE, 
          radius=grid::unit(16, "pt"), palette="Reds", direction=1) +
  theme_statebins(legend_position="right")
```

### Geom

```{r sb_facet, fig.width=17, fig.height=10}
flu <- ili_weekly_activity_indicators(2017)

ggplot(flu, aes(state=statename, fill=activity_level)) +
  geom_statebins() +
  coord_equal() +
  viridis::scale_fill_viridis(
    name = "ILI Activity Level  ", limits=c(0,10), breaks=0:10, option = "magma", direction = -1
  ) +
  facet_wrap(~weekend) +
  labs(title="2017-18 Flu Season ILI Activity Level") +
  theme_statebins(base_family = font_ps) +
  theme(plot.title=element_text(size=16, hjust=0)) +
  theme(plot.margin = margin(30,30,30,30))
```

### All the "states"

`statebins` now has PR, VI & NYC (by name or abbreviation) so you can use them, too:

```{r all}
library(statebins)
library(tidyverse)
library(viridis)

data(USArrests)

# make up some data for the example

rownames_to_column(USArrests, "state") %>%
  bind_rows(
    data_frame(
      state = c("Virgin Islands", "Puerto Rico", "New York City"),
      Murder = rep(mean(max(USArrests$Murder),3)),
      Assault = rep(mean(max(USArrests$Assault),3)),
      Rape = rep(mean(max(USArrests$Rape),3)),
      UrbanPop = c(93, 95, 100)
    )
  ) -> us_arrests

statebins(us_arrests, value_col="Assault",
          ggplot2_scale_function = viridis::scale_fill_viridis) +
  labs(title="USArrests + made up data") +
  theme_statebins("right")
```