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README.Rmd
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---
output: github_document
---
<!-- README.md is generated from README.Rmd. Please edit that file -->
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>",
fig.path = "README-"
)
```
# stldata <img src="man/figures/logo.png" align="right" />
[](https://www.tidyverse.org/lifecycle/#questioning)
[](https://travis-ci.org/slu-openGIS/stldata)
[](https://ci.appveyor.com/project/chris-prener/stldata)
[](https://codecov.io/github/slu-openGIS/stldata?branch=master)
[](https://zenodo.org/badge/latestdoi/85344799)
[](https://cran.r-project.org/package=stldata)
The `stlData` package contains various data sets representing the City of St. Louis. These data sets are primary designed for teaching statistics, data science, and spatial data analysis using `R`.
## Important Lifecycle Update
As of **June 4, 2019,** this package has been moved to a ["questioning" lifecycle stats](https://www.tidyverse.org/lifecycle/#questioning) - some of its functionality has been shifted to the still-developing [`gateway` package](https://github.com/slu-openGIS/gateway), while other aspects are better handeled by teaching students to import raw data sources. Development has therefore been suspended, with no current plans to return to this package in the future.
## Installation
You can install `stldata` from [Github](https://github.com/chris-prener/stlData) with:
```{r gh-installation, eval = FALSE}
devtools::install_github("slu-openGIS/stlData")
```
## Use with Simple Features
One goal of `stldata` is to provide accessible data for learning how to manipulate and map simple features objects in `R`. However, the installation of [`sf`](https://r-spatial.github.io/sf/) requires a number of dependencies. To make `stldata` as accessible as possible, `sf` is not required. If `sf` is not installed, only the data tables listed below will be fully accessible and functional.
## Current Data
### Data Tables
The package currently contains eight data tables stored as tibbles with quantitative data about the city:
* `stl_tbl_asthma` - current asthma prevalence in 2014 by census tract via [Centers for Disease Control 500 Cities Project](https://www.cdc.gov/500cities/)
* `stl_tbl_income` - 2010 and 2015 median income estimates via the American Community Survey, by census tract
* `stl_tbl_insurance` - lack of health insurance in 2014 by census tract via [Centers for Disease Control 500 Cities Project](https://www.cdc.gov/500cities/)
* `stl_tbl_lead` - blood lead level test result data from 2010-2015 via [Reuters](http://www.reuters.com/investigates/special-report/usa-lead-testing/#interactive-lead) and 2015 5-year estimates for demographics (poverty and race) via the American Community Survey, by census tract
* `stl_tbl_murders` - all murders between 2008 and 2016 via the St. Louis Metropolitan Police Department
* `stl_tbl_sluPlaces` - a small number of locations at Saint Louis University
* `stl_tbl_smoking` - current smoking in 2014 by census tract via [Centers for Disease Control 500 Cities Project](https://www.cdc.gov/500cities/)
* `stl_tbl_water` - rivers and streams listed under the Clean Water Act via the [Missouri Spatial Data Information Service](http://msdis.missouri.edu)
### Simple Features Objects
The package contains four `sf` objects describing the City of St. Louis:
* `stl_sf_boundary` - city boundary
* `stl_sf_historic` - historic districts
* `stl_sf_hydro` - Missouri side of the Mississippi River and the River Des Peres
* `stl_sf_tracts` - 2016 census tracts
### Conversion of Tibbles to `sf` Objects
The following tibbles can be converted to `sf` objects using the `stl_as_sf()` function:
* `stl_tbl_asthma`
* `stl_tbl_income`
* `stl_tbl_insurance`
* `stl_tbl_lead`
* `stl_tbl_smoking`
Input tables should not be quoted when the `stl_as_sf()` function is used:
```r
asthma <- stl_as_sf(stl_tbl_asthma)
```
## Useage
### Basic Usage
Once the package is loaded, the data contained in `stldata` can be assigned to data frames in your global environment and then explored. For example, to load the `stl_tbl_asthma` data:
```r
library("stldata")
asthma <- stl_tbl_asthma
str(asthma)
```
Additional examples and information are available in each table's help file. For example:
```r
?stl_tbl_asthma
```
### Skill Building
The `stl_tbl_murders` and `stl_tbl_water` data have been created for practicing data wrangling. The murder data can be used for working with demographic data specifically, and the water data have both missing and duplicate information. The `stl_tbl_sluPlaces` table is meant for introducing basic mapping wither either `plot()`, `ggplot2`, or `leaflet`. All of the tables excepting `stl_tbl_sluPlaces` contain count or rate data suitable for plotting, and the data measured at the census tract level can be use for practicing joins with demographic data from `tidycensus`.
### Mapping with `sf`
If you have the [development version of `ggplot2`](https://github.com/tidyverse/ggplot2), the `sf` objects in the package can be mapped using the `geom_sf()` function:
```r
ggplot() +
geom_sf(data = stl_sf_boundary, fill = "#5d5d5d", color = "#5d5d5d") +
geom_sf(data = stl_sf_historic, fill = "#d48a72", color = "#d48a72") +
geom_sf(data = stl_sf_hydro, fill = "#72bcd4", color = "#72bcd4") +
labs(title = "Historic Districts", subtitle = "St. Louis, MO")
```
When the tibbles like `stl_tbl_asthma` are converted to `sf` objects, they can be mapped as well:
```r
asthma <- stl_as_sf(stl_tbl_asthma)
ggplot() +
geom_sf(data = asthma, mapping = aes(fill = pctAsthma), color = "#5d5d5d") +
scale_fill_viridis(name = "Percent") +
labs(title = "Crude Asthma Prevalence", subtitle = "St. Louis, MO")
```
## Contributor Code of Conduct
Please note that this project is released with a [Contributor Code of Conduct](.github/CODE_OF_CONDUCT.md).
By participating in this project you agree to abide by its terms.