How to plot multiple percentile lines for a time series?

[RuReady]

I want to plot several percentile lines like this

How can I do it quickly? Thank you!

Example data and code

library(dplyr)
library(lubridate)
library(ggplot2)
# install.packages('openair', dependencies = TRUE)
library(openair)

# get Ozone data for London N. Kensington site
dat <- importAURN(site = "kc1", 
                  data_type = "daily",
                  pollutant = "o3",
                  year = 2010:2020) 

# create day in the year column
dat <- dat %>% 
  mutate(jDay = yday(date)) 
dat
#> # A tibble: 4,018 × 5
#>    date                   o3 site                 code   jDay
#>    <dttm>              <dbl> <chr>                <chr> <dbl>
#>  1 2010-01-01 00:00:00 36.4  London N. Kensington KC1       1
#>  2 2010-01-02 00:00:00 19.6  London N. Kensington KC1       2
#>  3 2010-01-03 00:00:00 19.2  London N. Kensington KC1       3
#>  4 2010-01-04 00:00:00 11.1  London N. Kensington KC1       4
#>  5 2010-01-05 00:00:00  9.17 London N. Kensington KC1       5
#>  6 2010-01-06 00:00:00 22.4  London N. Kensington KC1       6
#>  7 2010-01-07 00:00:00 27.8  London N. Kensington KC1       7
#>  8 2010-01-08 00:00:00 25.7  London N. Kensington KC1       8
#>  9 2010-01-09 00:00:00 49.8  London N. Kensington KC1       9
#> 10 2010-01-10 00:00:00 43.9  London N. Kensington KC1      10
#> # … with 4,008 more rows

ggplot(data = dat,
       aes(x = jDay, y = o3, group = jDay)) +
  geom_boxplot() +
  theme_minimal(base_size = 16)
#> Warning: Removed 208 rows containing non-finite values (`stat_boxplot()`).

ggplot(data = dat,
       aes(x = jDay, y = o3)) +
  geom_line(alpha = 0.6) +
  geom_smooth() +
  theme_minimal(base_size = 16)
#> `geom_smooth()` using method = 'gam' and formula = 'y ~ s(x, bs = "cs")'
#> Warning: Removed 208 rows containing non-finite values (`stat_smooth()`).

[jrkrideau]

@RuReady

I want to plot several percentile lines like this

I think wueneed an explanation of the substantive question. I, at least, do not understand what you need.

What those lines are representing? We may have a terminology problem. To me a percentile is a number that can be interpreted along the lines of "A percentile of 60% means that 6o% of the values in the data set are below than number. See Percentiles

If I am reading the code below correctly,

dat <- dat %>% 
  mutate(jDay = yday(date)) 

ggplot(data = dat,
       aes(x = jDay, y = o3, group = jDay)) +
  geom_boxplot() +
  theme_minimal(base_size = 16)

is asking for a boxplot for every day of the year for 10 years so, I think that means you are asking for 366 boxplots . Each will only have 10 data points except for Feb 29 which will have two .

Is this what you intended?

[nirgrahamuk]

library(tidyverse)
library(openair)

# get Ozone data for London N. Kensington site
dat <- importAURN(site = "kc1", 
                  data_type = "daily",
                  pollutant = "o3",
                  year = 2010:2020) 

# create day in the year column
dat <- dat %>% 
  mutate(jDay = yday(date)) 
dat


qs <- c(0,0.05,.25,1)
# the quantile method itself is capable of outputting results for each quantile requested 
(qdf_option_a <- group_by(
  dat,
  jDay
) |>
  summarise(across(
    .cols = o3,
    .fns = \(x)
    as.data.frame(rbind(quantile(x, probs = qs,na.rm=TRUE)))
  ,.unpack = TRUE))|>  pivot_longer(-jDay) |> mutate(name=as_factor(name)))

# Begin alternative to make quantile data frame # 

# if you had to use quantile multiple times each time to get a different quantile 
# you might do ... 
# prep qdf_option_b
qfuncs <- lapply(qs, \(q){
  function(x) {
    quantile(x,
      probs = q, na.rm = TRUE
    )
  }
}) |>
  setNames(paste0("q_", qs))

(qdf_option_b <- group_by(
  dat,
  jDay
) |>
  summarise(across(
    .cols = o3,
    .fns = qfuncs
  )) |>
  pivot_longer(cols = -jDay) |> mutate(name=as_factor(name)))

# END DATA PREP 

ggplot(data = dat,
       aes(x = jDay, y = o3)) +
    # geom_point(alpha=.05)+
  theme_minimal(base_size = 16)+
  geom_line(data=qdf_option_a,
            mapping = aes(y=value,color=name))