Visualizations (Interactive)

[andrewallenbruce]

Code

``` r 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 #> #> 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 #> #> 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 Rural Health Clinics by State", 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}

[andrewallenbruce]

Code

``` r 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 #> #> 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 Rural Health Clinics by State", 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}

[andrewallenbruce]

Code

``` r 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}