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Published
20 hours ago •
andrewallenbruce
andrewallenbruce
Visualizations (Interactive)
Code
library(tictoc)
library(provider)
library(tidyverse)
library(highcharter)
tic()
rhc <- providers(specialty_code = "00-17")
#> # A tibble: 5,168 × 7
#> npi pac enid specialty_code specialty_description state organization
#> <chr> <chr> <chr> <chr> <chr> <chr> <chr>
#> 1 15088613… 0941… O200… 00-17 PART A PROVIDER - RU… WA PALOUSE HEA…
#> 2 14978560… 0042… O200… 00-17 PART A PROVIDER - RU… ND WEST RIVER …
#> 3 17605703… 0042… O200… 00-17 PART A PROVIDER - RU… ND WEST RIVER …
#> 4 18019879… 0042… O200… 00-17 PART A PROVIDER - RU… SD WEST RIVER …
#> 5 18312861… 0042… O200… 00-17 PART A PROVIDER - RU… ND WEST RIVER …
#> 6 15583893… 0547… O200… 00-17 PART A PROVIDER - RU… ND CARRINGTON …
#> 7 18018116… 0547… O200… 00-17 PART A PROVIDER - RU… ND CARRINGTON …
#> 8 16694912… 0547… O200… 00-17 PART A PROVIDER - RU… ND ST. JOSEPH'…
#> 9 18816228… 0244… O200… 00-17 PART A PROVIDER - RU… MI PRESCOTT CL…
#> 10 11442076… 0648… O200… 00-17 PART A PROVIDER - RU… CA MEDICAL OFF…
#> # ℹ 5,158 more rows
rhc_count <- rhc |>
count(state,
sort = TRUE,
name = "count") |>
mutate(state = campfin::expand_state(state),
state = stringr::str_to_title(state))
#> # A tibble: 45 × 2
#> state count
#> <chr> <int>
#> 1 Kentucky 370
#> 2 Texas 332
#> 3 Missouri 326
#> 4 Tennessee 263
#> 5 Illinois 262
#> 6 California 252
#> 7 Mississippi 227
#> 8 Michigan 221
#> 9 Louisiana 214
#> 10 Iowa 209
#> # ℹ 35 more rows
hc <- rhc_count |>
hchart("bar",
hcaes(x = state, y = count),
color = "#2980b9",
name = "Rural Health Clinics") |>
hc_yAxis(gridLineWidth = 0,
labels = list(
style = list(color = "#000000")),
title = list(
text = "",
style = list(color = "#000000"))) |>
hc_xAxis(labels = list(style = list(color = "#000000")),
title = list(text= ""),
lineWidth = 0,
tickWidth = 0) |>
hc_tooltip(useHTML = TRUE,
crosshairs = TRUE,
borderWidth = 1,
sort = TRUE) |>
hc_add_theme(hc_theme_bloom()) |>
hc_plotOptions(column = list(
dataLabels = list(enabled = TRUE))) |>
hc_title(
text = "Number of <b>Rural Health Clinics</b> <i>by State</i>",
margin = 10,
align = "left",
style = list(color = "#22A884",
useHTML = TRUE)) |>
hc_size(height = 1000,
width = 800)
toc()
#> 3.56 sec elapsed
Created on 2023-10-18 with reprex v2.0.2
Code
library(tictoc)
library(provider)
library(tidyverse)
library(highcharter)
tic()
rhc_abb <- providers(specialty_code = "00-17") |>
count(state,
sort = TRUE,
name = "count")
#> # A tibble: 45 × 2
#> state count
#> <chr> <int>
#> 1 KY 370
#> 2 TX 332
#> 3 MO 326
#> 4 TN 263
#> 5 IL 262
#> 6 CA 252
#> 7 MS 227
#> 8 MI 221
#> 9 LA 214
#> 10 IA 209
#> # ℹ 35 more rows
rhc_map <- hcmap(
map = "countries/us/us-all",
data = rhc_abb,
value = "count",
joinBy = c("hc-a2", "state"),
name = "Rural Health Clinics",
dataLabels = list(enabled = TRUE, format = "{point.name}"),
borderColor = "#FAFAFA",
borderWidth = 0.1,
tooltip = list(
valueSuffix = " RHCs")) |>
hc_title(
text = "Number of <b>Rural Health Clinics</b> <i>by State</i>",
margin = 20,
align = "left",
style = list(color = "#22A884", useHTML = TRUE)) |>
hc_add_theme(hc_theme_bloom())
toc()
#> 4.14 sec elapsed
Created on 2023-10-18 with reprex v2.0.2
Code
library(highcharter)
library(tidyverse)
library(provider)
ex <- gen_data(2020:2030) |>
change(pay) |>
dplyr::mutate(group = NULL) |>
dplyr::distinct(year, .keep_all = TRUE)
ex |>
hchart("column",
hcaes(x = year,
y = pay_chg),
name = "Change") |>
hc_yAxis(gridLineWidth = 0,
labels = list(
style = list(
color = "#000000")),
title = list(text = "",
style = list(
color = "#000000"))) |>
hc_xAxis(labels = list(
style = list(
color = "#000000")),
title = FALSE,
lineWidth = 0,
tickWidth = 0) |>
hc_title(text = "Yearly Absolute Change") |>
hc_tooltip(useHTML = TRUE,
crosshairs = TRUE,
borderWidth = 1,
sort = TRUE) |>
hc_plotOptions(column = list(
color = "red",
dataLabels = list(
enabled = TRUE))) |>
hc_add_theme(hc_theme_smpl()) |>
hc_size(height = 500, width = 550)
Created on 2023-10-20 with reprex v2.0.2
