Plotting percentiles see: https://tonyladson.wordpress.com/2016/02/22/plotting-percentiles/

PercentilePlot.R

library(quantreg)
library(dplyr)
library(lubridate)
library(stringr)
library(readr)
library(ggplot2)
library(devtools)
library(splines)


# Source my preferred ggplot Theme see
# see https://gist.github.com/TonyLadson/cc60bbb3cbadf0e72619
devtools::source_gist('cc60bbb3cbadf0e72619')

# Load sample data

id <- "1uIPrjRq-qghTbBIzBXcvDfxbzJ250i6M" 
wq <- read_csv(sprintf("https://docs.google.com/uc?id=%s&export=download", id))




  

# parse and sort
wq <- wq %>%
  mutate(xdatetime = stringr::str_c(Date, Time, sep = ' ')) %>% 
  mutate(xdatetime = lubridate::ymd_hms(xdatetime))  %>% # set up dates
  arrange(xdatetime) # sort by date

# Check for missing values
colSums(is.na(wq))



# remove them
wq <- wq[complete.cases(wq), ]

# Add quantile fits

# create 75th and 25th quantile models
fit.75 <- quantreg::rq(Total.N ~ splines::bs(xdatetime, df=15), tau=0.75, data=wq)
fit.50 <- quantreg::rq(Total.N ~ splines::bs(xdatetime, df=15), tau=0.50, data=wq)
fit.25 <- quantreg::rq(Total.N ~ splines::bs(xdatetime, df=15), tau=0.25, data=wq)

# Add quantiles to data frame

wq <- wq %>%
  mutate(pc.75 = predict(fit.75)) %>%
  mutate(pc.50 = predict(fit.50)) %>%
  mutate(pc.25 = predict(fit.25)) 


# plot
wq %>%
  ggplot(aes(x = xdatetime)) + 
  geom_point(aes(y = Total.N)) + 
  geom_line(aes(y = pc.75, colour = '75th percentile')) + 
  geom_line(aes(y = pc.50, colour = 'Median')) + 
  geom_line(aes(y = pc.25, colour = '25th percentile')) + 
  scale_color_manual('', values = c('75th percentile' = 'red', '25th percentile' = 'green', 'Median' = 'blue'), 
                     breaks = c('75th percentile', 'Median', '25th percentile')) +
  BwTheme +
  xlab('Date') +
  ylab('Total Nitrogen mg/L')

Hi Tony, the csv file is no longer available.

Peter

Hi Tony, the csv file is no longer available.

Peter

Should now work ok. Dropbox changed their rules around the public folder. I've move the data to google drive