R6 class storing health statistics for a list of gp health units.

Details

This R6 class is designed to store population demography data for multiple GP practices. This class can be used to plot summary statistics and create shiny UI/server objects.

Super class

HealthDataScotland::health_unitgrp -> gp_grp

Methods

Inherited methods

Method `available_plots()`

Get character vector of available plots for gp grp.

Usage

gp_grp$available_plots()

Method `plot()`

Plot gp grp.

Usage

gp_grp$plot(type, ...)

Arguments

type: (character(1))
Character specifying plot type. See available_plots for options.
...: Passed to plot functions.

Examples

x <- example_gp_grp_unit()
x[["plot"]](type = "gp_bar")

Method `plot_data()`

Get plot data for gp grp.

Usage

gp_grp$plot_data(type, ...)

Arguments

type: (character(1))
Character specifying plot type. See available_plots for options.
...: Passed to plot data functions.

Examples

x <- example_gp_grp_unit()
x[["plot_data"]](type = "gp_bar")

Method `plot_info()`

Get plot info for gp grp.

Usage

gp_grp$plot_info(type, ...)

Arguments

type: (character(1))
Character specifying plot type. See available_plots for options.
...: Passed to plot info functions.

Examples

x <- example_gp_grp_unit()
x[["plot_info"]](type = "gp_bar")

Method `ui()`

Create UI for general practice group object.

Usage

gp_grp$ui()

Method `server()`

Create server for general practice group object.

Usage

gp_grp$server()

Method `clone()`

The objects of this class are cloneable with this method.

Usage

gp_grp$clone(deep = FALSE)

Arguments

deep: Whether to make a deep clone.

Examples

gps <- lapply(c("10002", "10017"), example_gp_unit)
sf <- get_sf()[get_sf()[["ID"]] %in% c("10002", "100017"), ]
x <- gp_grp[["new"]](gps, sf, .id = "gp")
x[["ID"]]()
#> [1] "gp"
x[["IDs"]]()
#> [1] "10002" "10017"
x[["titles"]]()
#> [1] "Muirhead Medical Centre" "The Blue Practice"      
x[["metadata"]]()
#> # A tibble: 2 × 16
#>   datasetID      ID    GPPracticeName PracticeListSize AddressLine1 AddressLine2
#>   <chr>          <chr> <chr>                     <dbl> <chr>        <chr>       
#> 1 b3b126d3-3b0c… 10002 Muirhead Medi…             8251 Muirhead Me… Liff Road   
#> 2 b3b126d3-3b0c… 10017 The Blue Prac…             7272 The Blue Pr… Crieff Medi…
#> # ℹ 10 more variables: AddressLine3 <chr>, AddressLine4 <chr>, Postcode <chr>,
#> #   TelephoneNumber <chr>, PracticeType <chr>, Dispensing <lgl>, HBName <chr>,
#> #   HSCP <chr>, DataZone <chr>, GPCluster <chr>
x[["data"]]()
#> [[1]]
#> <gp>
#>   Inherits from: <health_unit>
#>   Public:
#>     .data: tbl_df, tbl, data.frame
#>     .metadata: tbl_df, tbl, data.frame
#>     ID: function () 
#>     address: function () 
#>     available_plots: function () 
#>     clone: function (deep = FALSE) 
#>     combine_data: function () 
#>     data: function () 
#>     health_board: function () 
#>     initialize: function (.metadata, .data) 
#>     metadata: function () 
#>     plot: function (type, ...) 
#>     plot_data: function (type, ...) 
#>     plot_info: function (type, ...) 
#>     popup_modal: function (ns) 
#>     server: function () 
#>     telephone: function () 
#>     title: function () 
#>     ui: function (ns) 
#>     validate: function () 
#>   Private:
#>     population_pyramid: function (...) 
#>     population_pyramid_data: function () 
#>     population_pyramid_info: function () 
#>     population_trend: function (...) 
#>     population_trend_data: function () 
#>     population_trend_info: function () 
#>     population_trend_y_range: function () 
#>     required_data_cols: function () 
#>     required_metadata_cols: function () 
#>     title_col: function () 
#> 
#> [[2]]
#> <gp>
#>   Inherits from: <health_unit>
#>   Public:
#>     .data: tbl_df, tbl, data.frame
#>     .metadata: tbl_df, tbl, data.frame
#>     ID: function () 
#>     address: function () 
#>     available_plots: function () 
#>     clone: function (deep = FALSE) 
#>     combine_data: function () 
#>     data: function () 
#>     health_board: function () 
#>     initialize: function (.metadata, .data) 
#>     metadata: function () 
#>     plot: function (type, ...) 
#>     plot_data: function (type, ...) 
#>     plot_info: function (type, ...) 
#>     popup_modal: function (ns) 
#>     server: function () 
#>     telephone: function () 
#>     title: function () 
#>     ui: function (ns) 
#>     validate: function () 
#>   Private:
#>     population_pyramid: function (...) 
#>     population_pyramid_data: function () 
#>     population_pyramid_info: function () 
#>     population_trend: function (...) 
#>     population_trend_data: function () 
#>     population_trend_info: function () 
#>     population_trend_y_range: function () 
#>     required_data_cols: function () 
#>     required_metadata_cols: function () 
#>     title_col: function () 
#> 
x[["subset"]](id = "10002")
#> <gp_grp>
#>   Inherits from: <health_unitgrp>
#>   Public:
#>     .data: list
#>     .id: gp
#>     .sf: sf, tbl_df, tbl, data.frame
#>     ID: function () 
#>     IDs: function () 
#>     available_plots: function () 
#>     clone: function (deep = FALSE) 
#>     combine_data: function () 
#>     data: function () 
#>     download_handler: function () 
#>     get_download: function () 
#>     health_unit: function (id) 
#>     initialize: function (.data, .sf, .id) 
#>     metadata: function () 
#>     plot: function (type, ...) 
#>     plot_data: function (type, ...) 
#>     plot_info: function (type, ...) 
#>     server: function () 
#>     sf: function () 
#>     subset: function (id) 
#>     titles: function () 
#>     ui: function () 
#>     validate: function () 
#>   Private:
#>     bar_data: function (x, col, ...) 
#>     bar_echart: function (x) 
#>     gender_choices: function () 
#>     gp_bar: function (...) 
#>     gp_bar_data: function (gp = private[["unit_choices"]](), gender = private[["gender_choices"]]()) 
#>     gp_bar_info: function () 
#>     gp_data: function (gp, gender) 
#>     gp_trend: function (...) 
#>     gp_trend_data: function (gp = private[["unit_choices"]](), gender = private[["gender_choices"]]()) 
#>     gp_trend_info: function () 
#>     health_board_bar: function (...) 
#>     health_board_bar_data: function (health_board = private[["health_board_choices"]](), 
#>     health_board_bar_info: function () 
#>     health_board_choices: function () 
#>     health_board_data: function (health_board, gender) 
#>     health_board_trend: function (...) 
#>     health_board_trend_data: function (health_board = private[["health_board_choices"]](), 
#>     health_board_trend_info: function () 
#>     id_name_labels: function (x, name) 
#>     id_name_selection: function () 
#>     map_combine: function (func, nms = self[["IDs"]](), id = "ID", ...) 
#>     national_pyramid: function () 
#>     national_pyramid_data: function () 
#>     national_pyramid_info: function () 
#>     national_trend: function (...) 
#>     national_trend_data: function () 
#>     national_trend_info: function () 
#>     trend_data: function (x, ...) 
#>     trend_echart: function (x) 
#>     unit_choices: function () 
x[["plot"]](type = "national_pyramid")

x[["plot_data"]](type = "national_pyramid")
#> # A tibble: 24 × 4
#> # Groups:   Date [3]
#>        Date Age        Female  Male
#>       <dbl> <fct>       <dbl> <dbl>
#>  1 20231001 Ages0to4     -283   314
#>  2 20231001 Ages5to14    -752   825
#>  3 20231001 Ages15to24   -860   928
#>  4 20231001 Ages25to44  -1710  1690
#>  5 20231001 Ages45to64  -2199  2146
#>  6 20231001 Ages65to74   -981   916
#>  7 20231001 Ages75to84   -675   605
#>  8 20231001 Ages85plus   -262   201
#>  9 20240101 Ages0to4     -284   316
#> 10 20240101 Ages5to14    -753   841
#> # ℹ 14 more rows
x[["plot_info"]](type = "national_pyramid")
#> [1] "This bar chart shows a population pyramid of the total number of\n        GP registered patients in Scotland (x-axis) across age category\n        (y-axis) for each gender (colour). Specifically, this plot combines data for all available GP practices\n        across Scotland and calculates the total number of GP registered\n        patients per age and gender."
if (FALSE) { # \dontrun{
x[["ui"]]()
x[["server"]]()
} # }

## ------------------------------------------------
## Method `gp_grp$plot`
## ------------------------------------------------

x <- example_gp_grp_unit()
x[["plot"]](type = "gp_bar")


## ------------------------------------------------
## Method `gp_grp$plot_data`
## ------------------------------------------------

x <- example_gp_grp_unit()
x[["plot_data"]](type = "gp_bar")
#> # A tibble: 24 × 4
#> # Groups:   Date [3]
#>        Date Age        `10002 - Muirhead Medical Centre` 10017 - The Blue Prac…¹
#>       <dbl> <fct>                                  <dbl>                   <dbl>
#>  1 20231001 Ages0to4                                 186                     128
#>  2 20231001 Ages5to14                                463                     362
#>  3 20231001 Ages15to24                               419                     509
#>  4 20231001 Ages25to44                               952                     738
#>  5 20231001 Ages45to64                              1170                     976
#>  6 20231001 Ages65to74                               494                     422
#>  7 20231001 Ages75to84                               307                     298
#>  8 20231001 Ages85plus                                94                     107
#>  9 20240101 Ages0to4                                 190                     126
#> 10 20240101 Ages5to14                                456                     385
#> # ℹ 14 more rows
#> # ℹ abbreviated name: ¹`10017 - The Blue Practice`

## ------------------------------------------------
## Method `gp_grp$plot_info`
## ------------------------------------------------

x <- example_gp_grp_unit()
x[["plot_info"]](type = "gp_bar")
#> [1] "This bar chart shows the total number of GP registered patients\n        (y-axis) for each individal GP practice (colour) across\n        age categories (x-axis). Settings can be used to show data for\n        different GP practices and genders."

R6 class storing health statistics for a list of gp health units.

Details

Super class

Methods

Public methods

Method available_plots()

Usage

Method plot()

Usage

Arguments

Examples

Method plot_data()

Usage

Arguments

Examples

Method plot_info()

Usage

Arguments

Examples

Method ui()

Usage

Method server()

Usage

Method clone()

Usage

Arguments

Examples

Method `available_plots()`

Method `plot()`

Method `plot_data()`

Method `plot_info()`

Method `ui()`

Method `server()`

Method `clone()`