Add Hex Sticker

README.Rmd

@@ -15,7 +15,11 @@ knitr::opts_chunk$set(
 )
 ```
 
-# NHSRplotthedots <a alt="NHS-R Community's logo" href='https://nhsrcommunity.com/'><img src='https://nhs-r-community.github.io/assets/logo/nhsr-logo.png' align="right" height="80" /></a>
+:::: {style="display: flex; justify-content: space-between; align-items: center; flex-wrap: wrap;"}
+
+::: {style="flex: 1 1 50%;"}
+
+# NHSRplotthedots
 
 <!-- badges: start -->
 [![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)
@@ -25,6 +29,22 @@ knitr::opts_chunk$set(
 [![downloads](https://cranlogs.r-pkg.org/badges/grand-total/NHSRplotthedots)](https://CRAN.R-project.org/package=NHSRplotthedots)
 <!-- badges: end -->
 
+:::
+
+::: {style="flex: 1 1 auto;"}
+
+<a alt="NHS-R Community's logo" href='https://nhsrcommunity.com/'><img src="https://nhs-r-community.github.io/assets/logo/nhsr-logo.png" align="center" height="80"/></a>
+
+:::
+
+::: {style="flex: 1 1 auto;"}
+
+<img src="inst/images/logo.png" align="center" height="160"/>
+
+:::
+
+::::
+
 This package is built by the [NHS-R community][nhsr] to provide tools for drawing statistical process control (SPC)
 charts. This package supports NHS England's ['Making Data Count'][mdc] programme, and allows users to draw XmR charts,
 use change points, and apply rules with summary indicators for when rules are breached.

README.md

@@ -1,6 +1,11 @@
+
 <!-- README.md is generated from README.Rmd. Please edit that file -->
 
-# NHSRplotthedots <a alt="NHS-R Community's logo" href='https://nhsrcommunity.com/'><img src='https://nhs-r-community.github.io/assets/logo/nhsr-logo.png' align="right" height="80" /></a>
+<div style="display: flex; justify-content: space-between; align-items: center; flex-wrap: wrap;">
+
+<div style="flex: 1 1 50%;">
+
+# NHSRplotthedots
 
 <!-- badges: start -->
 
@@ -14,6 +19,22 @@ status](https://www.r-pkg.org/badges/version/NHSRplotthedots)](https://CRAN.R-pr
 [![downloads](https://cranlogs.r-pkg.org/badges/grand-total/NHSRplotthedots)](https://CRAN.R-project.org/package=NHSRplotthedots)
 <!-- badges: end -->
 
+</div>
+
+<div style="flex: 1 1 auto;">
+
+<a alt="NHS-R Community's logo" href='https://nhsrcommunity.com/'><img src="https://nhs-r-community.github.io/assets/logo/nhsr-logo.png" align="center" height="80"/></a>
+
+</div>
+
+<div style="flex: 1 1 auto;">
+
+<img src="inst/images/logo.png" align="center" height="160"/>
+
+</div>
+
+</div>
+
 This package is built by the [NHS-R
 community](https://nhsrcommunity.com) to provide tools for drawing
 statistical process control (SPC) charts. This package supports NHS
@@ -27,12 +48,14 @@ and features may change.
 
 ## Installation
 
-    # install from CRAN
-    install.packages("NHSRplotthedots")
+``` r
+# install from CRAN
+install.packages("NHSRplotthedots")
 
-    # Or install the development version from GitHub using {remotes} package:
-    # install.packages("remotes")
-    remotes::install_github("https://github.com/nhs-r-community/NHSRplotthedots", build_vignettes = TRUE)
+# Or install the development version from GitHub using {remotes} package:
+# install.packages("remotes")
+remotes::install_github("https://github.com/nhs-r-community/NHSRplotthedots", build_vignettes = TRUE)
+```
 
 # Overview
 
@@ -51,99 +74,115 @@ examples of the type of chart the package produces. We will use the
 `ae_attendances` dataset from the `{NHSRdatasets}` package and a bit of
 `{dplyr}` code to select some organisations.
 
-    library(NHSRplotthedots)
-    library(NHSRdatasets)
-    library(dplyr)
+``` r
+library(NHSRplotthedots)
+library(NHSRdatasets)
+library(dplyr)
 
-    sub_set <- ae_attendances |>
-      filter(org_code == "RQM", type == 1, period < as.Date("2018-04-01"))
+sub_set <- ae_attendances |>
+  filter(org_code == "RQM", type == 1, period < as.Date("2018-04-01"))
 
-    sub_set |>
-      ptd_spc(
-        value_field = breaches,
-        date_field = period,
-        improvement_direction = "decrease"
-      )
+sub_set |>
+  ptd_spc(
+    value_field = breaches,
+    date_field = period,
+    improvement_direction = "decrease"
+  )
+```
 
 <img src="man/figures/README-example1-1.png" width="100%" />
 
 This plot is ok on its own, but we can specify more control options if
 we explicitly pass it on to the `plot()` function.
 
-    sub_set |>
-      ptd_spc(
-        value_field = breaches,
-        date_field = period,
-        improvement_direction = "decrease"
-      ) |>
-      plot(
-        y_axis_label = "4-hour wait breaches",
-        main_title = "SPC of A&E waiting time breaches for RQM"
-      )
+``` r
+sub_set |>
+  ptd_spc(
+    value_field = breaches,
+    date_field = period,
+    improvement_direction = "decrease"
+  ) |>
+  plot(
+    y_axis_label = "4-hour wait breaches",
+    main_title = "SPC of A&E waiting time breaches for RQM"
+  )
+```
 
 <img src="man/figures/README-example2-1.png" width="100%" />
 
 or, equivalently:
 
-    sub_set |>
-      ptd_spc(
-        value_field = breaches,
-        date_field = period,
-        improvement_direction = "decrease"
-      ) |>
-      ptd_create_ggplot(
-        y_axis_label = "4-hour wait breaches",
-        main_title = "SPC of A&E waiting time breaches for RQM"
-      )
+``` r
+sub_set |>
+  ptd_spc(
+    value_field = breaches,
+    date_field = period,
+    improvement_direction = "decrease"
+  ) |>
+  ptd_create_ggplot(
+    y_axis_label = "4-hour wait breaches",
+    main_title = "SPC of A&E waiting time breaches for RQM"
+  )
+```
 
 You can also use the `summary()` function to get some basic statistics
 about your SPC data frame. The function prints the SPC options, and then
 returns the summarised results as a table:
 
-    summary <- sub_set |>
-      ptd_spc(
-        value_field = breaches,
-        date_field = period,
-        improvement_direction = "decrease",
-        target = 1200
-      ) |>
-      summary()
-    #> Plot the Dots SPC options:
-    #> ================================
-    #> value_field:          'breaches'
-    #> date_field:           'period'
-    #> facet_field:          not set
-    #> rebase:               not set
-    #> fix_after_n_points:   not set
-    #> improvement_direction:'decrease'
-    #> target:               '1200'
-    #> trajectory:           not set
-    #> screen_outliers:      'TRUE'
-    #> --------------------------------
+``` r
+summary <- sub_set |>
+  ptd_spc(
+    value_field = breaches,
+    date_field = period,
+    improvement_direction = "decrease",
+    target = 1200
+  ) |>
+  summary()
+#> Plot the Dots SPC options:
+#> ================================
+#> value_field:          'breaches'
+#> date_field:           'period'
+#> facet_field:          not set
+#> rebase:               not set
+#> fix_after_n_points:   not set
+#> improvement_direction:'decrease'
+#> target:               '1200'
+#> trajectory:           not set
+#> screen_outliers:      'TRUE'
+#> --------------------------------
+```
 
 You could assign this summary table to a variable and use it later:
 
-    summary$variation_type
-    #> [1] "common_cause"
-    summary$assurance_type
-    #> [1] "inconsistent"
+``` r
+summary$variation_type
+#> Warning: Unknown or uninitialised column: `variation_type`.
+#> NULL
+```
+
+``` r
+summary$assurance_type
+#> [1] "inconsistent"
+```
 
 ### Interactive plots with Plotly
 
 It’s also possible to generate interactive plots using the `{plotly}`
 package by replacing the call to `plot` with `ptd_create_plotly`. This
 function takes the same arguments as `plot`/`ptd_create_ggplot`.
 
-    sub_set |>
-      ptd_spc(
-        value_field = breaches,
-        date_field = period,
-        improvement_direction = "decrease"
-      ) |>
-      ptd_create_plotly(
-        y_axis_label = "4-hour wait breaches",
-        main_title = "SPC of A&E waiting time breaches for RQM"
-      )
+``` r
+sub_set |>
+  ptd_spc(
+    value_field = breaches,
+    date_field = period,
+    improvement_direction = "decrease"
+  ) |>
+  ptd_create_plotly(
+    y_axis_label = "4-hour wait breaches",
+    main_title = "SPC of A&E waiting time breaches for RQM"
+  )
+```
 
 ### Adding annotations for mean and process limits
 
@@ -153,17 +192,21 @@ axis, if this is helpful for you and your audience.
 
 The way to achieve this is to turn on the `label_limits` option:
 
-    sub_set |>
-      ptd_spc(
-        value_field = breaches,
-        date_field = period,
-        improvement_direction = "decrease"
-      ) |>
-      ptd_create_ggplot(
-        y_axis_label = "4-hour wait breaches",
-        main_title = "SPC of A&E waiting time breaches for RQM",
-        label_limits = TRUE
-      )
+``` r
+sub_set |>
+  ptd_spc(
+    value_field = breaches,
+    date_field = period,
+    improvement_direction = "decrease"
+  ) |>
+  ptd_create_ggplot(
+    y_axis_label = "4-hour wait breaches",
+    main_title = "SPC of A&E waiting time breaches for RQM",
+    label_limits = TRUE
+  )
+#> Warning in ptd_create_ggplot(ptd_spc(sub_set, value_field = breaches, date_field = period, : Unknown arguments provided by plot: label_limits
+#> Check for common spelling mistakes in arguments.
+```
 
 <img src="man/figures/README-limits-example-1.png" width="100%" />
 
@@ -175,17 +218,23 @@ will only show for the most recent section.
 To find out more about the `ptd_spc()` function, you can view the help
 with:
 
-    ?ptd_spc
+``` r
+?ptd_spc
+```
 
 Details on the extra plot controls can be found using:
 
-    ?ptd_create_ggplot
+``` r
+?ptd_create_ggplot
+```
 
 To view the vignette (worked example), use:
 
-    vignette("intro", package = "NHSRplotthedots")
+``` r
+vignette("intro", package = "NHSRplotthedots")
 
-    vignette(package = "NHSRplotthedots")
+vignette(package = "NHSRplotthedots")
+```
 
 # Contributing