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I have data that is collected annually that I am trying to plot together. For each year, data is available for some random subset of days. For example:

library(tidyverse)
library(lubridate)
#> 
#> Attaching package: 'lubridate'
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union

set.seed(123)
year1 <- seq(ymd("2019-03-01"), ymd("2019-10-31"), by = "day")
year2 <- seq(ymd("2020-07-01"), ymd("2020-10-31"), by = "day")
year3 <- seq(ymd("2021-03-01"), ymd("2021-10-31"), by = "day")

dat <- tibble(date = sort(c(sample(year1, 50),
                            sample(year2, 50),
                            sample(year3, 50))),
              value = runif(150)) |> 
  mutate(year = year(date))

dat
#> # A tibble: 150 × 3
#>    date       value  year
#>    <date>     <dbl> <dbl>
#>  1 2019-03-07 0.265  2019
#>  2 2019-03-14 0.565  2019
#>  3 2019-03-23 0.913  2019
#>  4 2019-03-26 0.902  2019
#>  5 2019-04-01 0.274  2019
#>  6 2019-04-12 0.321  2019
#>  7 2019-04-19 0.986  2019
#>  8 2019-04-22 0.620  2019
#>  9 2019-05-11 0.937  2019
#> 10 2019-05-13 0.467  2019
#> # … with 140 more rows

I want to plot the lines such that the x-axis represents 1 year, and there is a separate line for each year. If I just put the date on the x-axis, each year shows up sequentially, as we would expect, but there are basically 3 years on the x-axis.

ggplot(dat, aes(x = date, y = value)) +
  geom_line(aes(color = factor(year))) +
  scale_x_date(breaks = "3 months", date_labels = "%B")

I have tried to use facets as a work around. This one has a similar problem of have three years on the x-axis.

ggplot(dat, aes(x = date, y = value)) +
  facet_wrap(~year, ncol = 1) +
  geom_line(aes(color = factor(year))) +
  scale_x_date(breaks = "3 months", date_labels = "%B")

I can free the scales, but then the axes don’t line up, so it’s hard to compare across years.

ggplot(dat, aes(x = date, y = value)) +
  facet_wrap(~year, ncol = 1, scales = "free_x") +
  geom_line(aes(color = factor(year))) +
  scale_x_date(breaks = "2 months", date_labels = "%B")

To illustrate what I’m looking for, I can force all dates to have the year 2020. This results in the plot I want, but it seems like there must be a better way than changing all of the dates?

year(dat$date) <- 2020

ggplot(dat, aes(x = date, y = value)) +
  facet_wrap(~year, ncol = 1) +
  geom_line(aes(color = factor(year))) +
  scale_x_date(breaks = "2 months", date_labels = "%B")

Created on 2021-08-03 by the reprex package (v2.0.0)

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Jake Thompson
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  • Answers to similar questions (like [here](https://stackoverflow.com/questions/62377404/r-formatting-data-per-month-and-facet-wrapping-per-year) and [here](https://stackoverflow.com/questions/29974535/dates-with-month-and-day-in-time-series-plot-in-ggplot2-with-facet-for-years)) also involve changing to a common x axis scale by setting everything to the same year like you did. – aosmith Aug 04 '21 at 00:16

1 Answers1

3

If the question is how to plot them over each other in the same panel then create the corresponding date in the same year, such as year 2000, and then plot.

library(ggplot2)
library(lubridate)

  ggplot(dat, aes(`year<-`(date, 2000), value, col = factor(year))) +
    geom_line() +
    labs(x = "", col = "year")

screenshot

G. Grothendieck
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