Let's assume we have the following artifical data:
df <- data.frame(Year = c(2015,2016,2017,2018),
GPP_mean = c(1700,1800,1750,1850),
Reco_mean = c(-1700,-1800,-1750,-1850),
GPP_min = c(1600,1700,1650,1750),
GPP_max = c(1800,1900,1850,1950),
Reco_min = c(-1600,-1700,-1650,-1750),
Reco_max = c(-1800,-1900,-1850,-1950))
I'd like to plot bars for each mean value and use the min/max columns for the errorbar. This is what I've achieved so far:
df %>%
pivot_longer(cols = -Year,
names_to = c("variable", "stats"),
names_sep = "_")
Which gives us:
# A tibble: 24 x 4
Year variable stats value
<dbl> <chr> <chr> <dbl>
1 2015 GPP mean 1700
2 2015 Reco mean -1700
3 2015 GPP min 1600
4 2015 GPP max 1800
5 2015 Reco min -1600
6 2015 Reco max -1800
7 2016 GPP mean 1800
8 2016 Reco mean -1800
9 2016 GPP min 1700
10 2016 GPP max 1900
# … with 14 more rows
So far, so good (I guess?). From here on, I have no clue of how I can tell ggplot to plot the mean values as the bars and use min/max for the errorbars. Any help appreciated, thanks.
additional solution using tidyverse
library(tidyverse)
out <- df %>%
pivot_longer(-Year, names_sep = "_", names_to = c("index", ".value"))
ggplot(out, aes(Year, mean, fill = index)) +
geom_col() +
geom_errorbar(aes(ymin = min, ymax = max), width = 0.5)