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View evaluation.R
# this is old code! I do not advocate doing any of the below :-)
rm(list=ls())
library(psych)
count.NAS=function(x) length(which(is.na(x)))
ASPECT=read.csv("ASPECT.csv")
HONOS=read.csv("HONOS.csv")
ESSENCES=read.csv("ESSENCES.csv")
View loop_penguins.Rmd
---
title: "Loop demo"
author: "Chris Beeley"
date: "21/04/2021"
output: html_document
params:
species: NA
---
```{r setup, include=FALSE}
@ChrisBeeley
ChrisBeeley / app.R
Created Mar 12, 2021
Demo of reactive data and UI
View app.R
library(palmerpenguins)
library(tidyverse)
# Define UI for application that draws a histogram
ui <- fluidPage(
# Application title
titlePanel("Reactive example"),
sidebarLayout(
@ChrisBeeley
ChrisBeeley / app.R
Created Apr 3, 2020
Test to see how app.R behaves the first time it runs and on subsequent runs
View app.R
library(shiny)
library(tidyverse)
library(DT)
load("ae_attendances.RData")
Sys.sleep(10)
# filter to random 10 Trusts with a decent amount of data in
View survey_munge
### Data load
library(tidyverse)
library(RMySQL)
library(readxl)
main <- read_excel("JISC_05-02-20.xlsx", skip = 1) %>%
rename(TeamC = `Team Number`, Date = CompletionDate) %>%
select(-starts_with("1."), -starts_with("2."), -starts_with("3."), -starts_with("4."))
View List of NHS relevant GitHubs
https://github.com/HFAnalyticsLab
https://github.com/codonlibrary
https://github.com/royal-free-london
https://github.com/PublicHealthEngland
https://github.com/nhsuk
View binom_conf.Rmd
---
title: "Binomial confidence intervals"
author: "Chris Beeley"
date: "20/06/2019"
output: html_document
---
```{r setup, include=FALSE}
library(tidyverse)
View server.R
function(input, output) { # define application in here
output$textDisplay <- renderText({ # mark function as reactive
# and assign to output$textDisplay for passing to ui.R
paste0("You said '", input$comment, # from the text
"'. There are ", nchar(input$comment), # input control as
" characters in this.") # defined in ui.R
})
View big_pipe.R
fixedData[, missnum > 2] %>%
gather(L1, value) %>%
filter(!is.na(value)) %>%
left_join(select(questionFrame, code, value), by = c("L1" = "code")) %>%
select(-L1) %>%
group_by(value.y) %>%
count(value.x) %>%
mutate(prop = prop.table(n) * 100) %>%
select(-n) %>%
mutate(value.x = factor(value.x, levels = 1:5)) %>%
View dplyrReprex
library(tidyverse)
#> Warning: package 'tidyverse' was built under R version 3.4.4
#> -- Attaching packages ----------------------------------------------------------------------------------------------- tidyverse 1.2.1 --
#> v ggplot2 3.0.0 v purrr 0.2.4
#> v tibble 1.4.2 v dplyr 0.7.6
#> v tidyr 0.8.1 v stringr 1.3.0
#> v readr 1.1.1 v forcats 0.3.0
#> Warning: package 'ggplot2' was built under R version 3.4.4
#> Warning: package 'tibble' was built under R version 3.4.4
#> Warning: package 'readr' was built under R version 3.4.4