The goal of lbjdata is to provide custom themes and resources for projects related to the LBJ School’s Data Initiatives.
You can install the development version of {lbjdata}
from
Github with:
devtools::install_github("utexas-lbjp-data/lbjdata")
This is a basic example which shows you how to solve a common problem:
library(lbjdata)
library(ggplot2)
library(readr)
library(dplyr)
#>
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#>
#> filter, lag
#> The following objects are masked from 'package:base':
#>
#> intersect, setdiff, setequal, union
library(tidyr)
What is special about using README.Rmd
instead of just README.md
?
You can include R chunks like so:
provider_types <- read_csv("https://genesis.soc.texas.gov/files/accessibility/vaccineprovideraccessibilitydata.csv") %>%
group_by(type = TYPE) %>%
summarise(tot_shipped = sum(Total_Shipped),
tot_avail = sum(VACCINES_AVAILABLE)) %>%
drop_na() %>%
arrange(desc(tot_shipped))
provider_types %>%
ggplot() +
geom_col(aes(x=reorder(type, desc(tot_shipped)),
y = tot_shipped,
fill=type)) +
geom_text(angle=90, color="#2d2d2d", size = 3.1, family = "LibreFranklin-Bold",
aes(y= 0, x=type, label = type), hjust = 0) +
theme_lbj() +
theme(axis.text.x = element_blank()) +
labs(title = "Vaccine Supply, By Type of Provider",
subtitle = "Source: Texas Department of State Health Services")