ChrisBeeley

a <- c("Yes please", "Not this one", "This is also good")

stringr::str_detect(a, "Yes")
#> [1]  TRUE FALSE FALSE

stringr::str_detect(a, "Yes") | stringr::str_detect(a, "good")
#> [1]  TRUE FALSE  TRUE

stringr::str_detect(a, "Yes|good")

ChrisBeeley

library(sparkline)
library(formattable)
library(dplyr)

x = c(0, rep(1000, 5), rep(1000.000001, 5))

res <- mtcars |>
  mutate(summary = as.character(
    htmltools::as.tags(
      sparkline(x, type = "bar", 

ChrisBeeley

# Shiny app with 3 fields that the user can submit data for
ui <- fluidPage(
  DT::dataTableOutput("responses", width = 300), tags$hr(),
  textInput("name", "Name", ""),
  checkboxInput("used_shiny", "I've built a Shiny app in R before", FALSE),
  sliderInput("r_num_years", "Number of years using R",
              0, 25, 2, ticks = FALSE),
  actionButton("submit", "Submit")
)

ChrisBeeley

--- 
title: "Parameterised Reporting" 
author: "Tina Simms" 
date: "03/11/2021" 
output: html_document 
params: 
  month: 
    label: "Month of the Year" 
    value: January 
    input: select 

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."))