ChrisBeeley

library(tidyverse)

# produce data

pharmacy_sub <- pharmacy %>% 
  filter(Site1 == "Site C", NSVCode == "Drug A")

daily_data <- phaRmacyForecasting:::make_tsibble(pharmacy_sub, frequency = "Daily")

ChrisBeeley

# 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")

ChrisBeeley

---
title: "Loop demo"
author: "Chris Beeley"
date: "21/04/2021"
output: html_document
params:
  species: NA
---

```{r setup, include=FALSE}

ChrisBeeley

library(palmerpenguins)
library(tidyverse)

# Define UI for application that draws a histogram
ui <- fluidPage(
    
    # Application title
    titlePanel("Reactive example"),
    
    sidebarLayout(

ChrisBeeley

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

ChrisBeeley

### 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."))

ChrisBeeley

https://github.com/HFAnalyticsLab

https://github.com/codonlibrary

https://github.com/royal-free-london

https://github.com/PublicHealthEngland

https://github.com/nhsuk

ChrisBeeley

---
title: "Binomial confidence intervals"
author: "Chris Beeley"
date: "20/06/2019"
output: html_document
---

```{r setup, include=FALSE}

library(tidyverse)

ChrisBeeley

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
    
  })

ChrisBeeley

  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)) %>%