A simple script to import a quality measurement data set, transform it, and plot qi charts by organization and measure

plot_qi_charts_wales.R

# Load Prerequisites ====
library(tidyverse)
library(lubridate)
library(qicharts)

# Read data frame from csv ----
df <- read.csv("walestest.csv", stringsAsFactors = FALSE)

# Test it once====
# Create one of Organisation dataframes ----
df.Abertawe <- df %>% 
  mutate(Month = ymd(Month)) %>% 
  filter(Organisation == "Abertawe Bro Morgannwg University Local Health Board Total") %>% 
  select(Month, Attendances, lessthan4h) # Replace lessthan4h with measure variable

# Plot the test data ----
qic(y = df.Abertawe$Attendances, chart = 'i', freeze = 24)

# Alternately: ====
# Create a list of dataframes based on the test dataframe df.Abertawe ----
df.list <- df %>% 
  mutate(Month = ymd(Month)) %>% 
  split(f = .$Organisation) 

# Iterate across the list to create named plot objects ----
plot.list <- lapply(df.list, function(k) qic(y = k$Attendances, chart = 'i', freeze = 24)) #change y variable to select measure

# Call the plot by name ----
plot(plot.list$`All Wales - All hospital emergency care facilities`)