@ -3,7 +3,7 @@ output: rmarkdown::github_document
editor_options:
chunk_output_type: console
---
```{r echo=FALSE, message=FALSE, warning=FALSE, error=FALSE, include=FALSE}
```{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)
```
@ -21,7 +21,7 @@ The following functions are implemented:
## Installation
```{r eval=FALSE}
```{r install, eval=FALSE}
devtools::install_github("hrbrmstr/statebins")
```
@ -29,15 +29,17 @@ devtools::install_github("hrbrmstr/statebins")
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}
```{r setup }
library(statebins)
library(tidyverse)
# current verison
packageVersion("statebins")
```
# t he original wapo data
### T he original wapo data
```{r original}
adat <- suppressMessages(read_csv(system.file("extdata", "wapostates.csv", package="statebins")))
mutate(
@ -51,9 +53,11 @@ mutate(
) +
labs(title = "1994-2000") +
theme_statebins()
```
# c ontinuous scale, legend on top
### C ontinuous scale, legend on top
```{r continuous}
statebins(
adat, value_col = "avgshare01_07",
name = "Share of workforce with jobs lost or threatened by trade",
@ -61,16 +65,19 @@ statebins(
) +
labs(x="2001-2007") +
theme_statebins(legend_position="top")
```
### Continuous scale, no legend
# 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)
# 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")))
@ -78,15 +85,19 @@ dat <- suppressMessages(read_csv(system.file("extdata", "deaths.csv", package="s
statebins(dat, value_col = "death_rate", name="Per 100K pop") +
labs(title="Mortality Rate (2010)") +
theme_statebins()
```
# f ertility data
### F ertility data
```{r fert}
statebins(dat, value_col="fertility_rate", name="Per 100K pop", palette="PuBuGn") +
labs(title="Fertility Rate (2010)") +
theme_statebins()
```
# m anual - perhaps good for elections?
### M anual - 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")) %>%
@ -101,7 +112,7 @@ mutate(election_2012, value = ifelse(is.na(Obama), "Romney", "Obama")) %>%
### Rounded rects!
```{r}
```{r rounded }
data(USArrests)
USArrests$state <- rownames(USArrests)
@ -113,7 +124,7 @@ statebins(USArrests, value_col="Assault", name = "Assault", round=TRUE) +
`statebins` now has PR, VI & NYC (by name or abbreviation) so you can use them, too:
```{r}
```{r all }
library(statebins)
library(tidyverse)
library(viridis)
