knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" )
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
.
As of June 4, 2019, this package has been moved to a "questioning" lifecycle stats - some of its functionality has been shifted to the still-developing gateway
package, 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.
You can install stldata
from Github with:
devtools::install_github("slu-openGIS/stlData")
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
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.
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 Projectstl_tbl_income
- 2010 and 2015 median income estimates via the American Community Survey, by census tractstl_tbl_insurance
- lack of health insurance in 2014 by census tract via Centers for Disease Control 500 Cities Projectstl_tbl_lead
- blood lead level test result data from 2010-2015 via Reuters and 2015 5-year estimates for demographics (poverty and race) via the American Community Survey, by census tractstl_tbl_murders
- all murders between 2008 and 2016 via the St. Louis Metropolitan Police Departmentstl_tbl_sluPlaces
- a small number of locations at Saint Louis Universitystl_tbl_smoking
- current smoking in 2014 by census tract via Centers for Disease Control 500 Cities Projectstl_tbl_water
- rivers and streams listed under the Clean Water Act via the Missouri Spatial Data Information ServiceThe package contains four sf
objects describing the City of St. Louis:
stl_sf_boundary
- city boundarystl_sf_historic
- historic districtsstl_sf_hydro
- Missouri side of the Mississippi River and the River Des Peresstl_sf_tracts
- 2016 census tractssf
ObjectsThe 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:
asthma <- stl_as_sf(stl_tbl_asthma)
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:
library("stldata") asthma <- stl_tbl_asthma str(asthma)
Additional examples and information are available in each table's help file. For example:
?stl_tbl_asthma
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
.
sf
If you have the development version of ggplot2
, the sf
objects in the package can be mapped using the geom_sf()
function:
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:
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")
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.
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