Using this sample data frame:
> dput(coun2b)
structure(list(Camden = c(13.9933481152993, 17.5410199556541,
26.0055432372506, 19.1064301552106, 9.05764966740577, 17.5321507760532
), Guilford = c(24.674715261959, 27.5097949886105, 25.4646924829157,
22.2637813211845, 7.60227790432802, 17.9681093394077), years = 2012:2017,
Camden_ymin = c(12.4514939737261, 15.4927722105436, 22.5744436662436,
16.8415649174844, 7.45264839077184, 15.6645677387521), Guilford_ymin = c(23.2136204848819,
26.3627764588421, 23.8076842636931, 20.383805927254, 5.58799564906578,
16.2548749333076), Camden_ymax = c(15.5352022568726, 19.5892677007646,
29.4366428082575, 21.3712953929369, 10.6626509440397, 19.3997338133543
), Guilford_ymax = c(26.1358100390361, 28.6568135183788,
27.1217007021384, 24.143756715115, 9.61656015959026, 19.6813437455079
)), class = "data.frame", row.names = c(NA, -6L))
which looks like this:
coun2b
Camden Guilford Camden_ymin Guilford_ymin Camden_ymax Guilford_ymax
1 13.99335 24.674715 12.451494 23.213620 15.53520 26.13581
2 17.54102 27.509795 15.492772 26.362776 19.58927 28.65681
3 26.00554 25.464692 22.574444 23.807684 29.43664 27.12170
4 19.10643 22.263781 16.841565 20.383806 21.37130 24.14376
5 9.05765 7.602278 7.452648 5.587996 10.66265 9.61656
6 17.53215 17.968109 15.664568 16.254875 19.39973 19.68134
and I use that dataframe with this:
library(tidyverse)
ggplot(coun2b, aes(x=years, Guilford, group=years))
labs(title = "Counts in Guilford, N.C.",
#caption="P. infestans range: 18 - 22 C; P. nicotianae range: 25 - 35 C; \"a\" Year with\nmost N.C. P. infestans reports (n=16); \"aa\" Year with most N.C. P. nicotianae reports (n=23)",
y="Number of Days", x="Year" ) geom_col( position = "dodge")
geom_errorbar(aes(ymin=Guilford_ymin, ymax=Guilford_ymax), position="dodge")
theme(axis.text.x = element_text(face="bold"), axis.title.x = element_text(size=14),
axis.text.y = element_text(face="bold"), axis.title.y = element_text(size=14),
title = element_text(size=12))
scale_x_continuous("Year", labels = plotscalex, breaks=plotscalex)
geom_hline(aes(yintercept = mean(Guilford[years %in% 2012:2016]),
linetype='Mean for 2012-2016'))
scale_linetype_manual(name="Legend", values=c("Mean for 2012-2016"=1) )
I create this barplot:
However, my complete dataset is actually larger and shaped differently, as long version. This is a sample of the long version:
> dput(samp1)
structure(list(years = c(2012L, 2012L, 2012L, 2013L, 2013L, 2013L,
2014L, 2014L, 2014L, 2012L, 2012L, 2012L, 2013L, 2013L, 2013L,
2014L, 2014L, 2014L), valu = c("mean", "ymin", "ymax", "mean",
"ymin", "ymax", "mean", "ymin", "ymax", "mean", "ymin", "ymax",
"mean", "ymin", "ymax", "mean", "ymin", "ymax"), name = c("Camden",
"Camden", "Camden", "Camden", "Camden", "Camden", "Camden", "Camden",
"Camden", "Guilford", "Guilford", "Guilford", "Guilford", "Guilford",
"Guilford", "Guilford", "Guilford", "Guilford"), value = c(13.9933481152993,
12.4514939737261, 15.5352022568726, 17.5410199556541, 15.4927722105436,
19.5892677007646, 26.0055432372506, 22.5744436662436, 29.4366428082575,
24.674715261959, 23.2136204848819, 26.1358100390361, 27.5097949886105,
26.3627764588421, 28.6568135183788, 25.4646924829157, 23.8076842636931,
27.1217007021384), county = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), levels = c("Camden",
"Guilford", "Pasquotank", "Wake"), class = "factor")), row.names = c(NA,
-18L), class = c("tbl_df", "tbl", "data.frame"))
I tried using:
samp1 %>% filter(county == "Camden") %>%
ggplot( aes(x=years, y=value, group=years))
labs(title = "Number of Days in April-August with Suitable Weather for\nLate Blight Sporulation in Camden, N.C.", y="Number of Days", x="Year" )
geom_col(data=samp1 %>% filter(county=="Camden", valu=="mean"), aes(x=years,
y=value), position = "dodge")
geom_errorbar(data=samp1 %>% filter(county=="Camden"),
aes(ymin=samp1 %>% filter(valu=="ymin"), ymax=samp1 %>% filter(valu=="ymax"), position="dodge"))
theme(axis.text.x = element_text(face="bold"), axis.title.x = element_text(size=14),
axis.text.y = element_text(face="bold"), axis.title.y = element_text(size=14),
title = element_text(size=12))
scale_x_continuous("Year", labels = plotscalex, breaks=plotscalex)
geom_hline(aes(yintercept = mean(Camden[years %in% 2012:2016]),
linetype='Mean for 2012-2016'))
scale_linetype_manual(name="Legend", values=c("Mean for 2012-2016"=1) )
as an attempt to create the same plot as above with the data in the long form. I get this error message:
Error in `geom_errorbar()`:
! Problem while computing aesthetics.
ℹ Error occurred in the 2nd layer.
Caused by error in `check_aesthetics()`:
! Aesthetics must be either length 1 or the same as the data (9)
✖ Fix the following mappings: `ymin` and `ymax`
Run `rlang::last_error()` to see where the error occurred.
Warning message:
In geom_errorbar(data = samp1 %>% filter(county == "Camden"), aes(ymin = samp1 %>% :
Ignoring unknown aesthetics: position
Because of the long form of this dataframe, I use filter 2x before I get to the geom_errorbar(). I don't think that's the problem, I just don't know how to filter correctly for ymin and ymax. I tried geom_errorbar(data=samp1 %>% filter(county=="Camden"), aes(ymin=samp1 %>% filter(county=="Camden", valu=="ymin"), ymax=samp1 %>% filter(county=="Camden",valu=="ymax"), position="dodge")) as well as what's in the code block above and I can't get it to work. How can I use the long form data, samp1, to create a plot that is the same as the plot created when the data are wide? I'm using the long form because I will have to do a side-by-side barplot for multiple counties, while in this post, I'm just using one county.
CodePudding user response：
You are making this much harder than it needs to be. What's wrong with a simple pivot to get your data into the correct format in the first place? The only wrangling you then need inside the plot code is to get the groupwise hline:
library(tidyverse)
sampl %>%
pivot_wider(names_from = valu, values_from = value) %>%
ggplot(aes(years, mean))
geom_col()
geom_errorbar(aes(ymin = ymin, ymax = ymax), width = 0.25)
geom_hline(data = . %>% group_by(county) %>% summarize(mean = mean(mean)),
aes(yintercept = mean), linetype = 2)
facet_grid(.~county)
theme_gray(base_size = 16)
theme(strip.background = element_blank(),
strip.text = element_text(size = 20, face = 2))
Or, if you want to do one plot at a time:
sampl %>%
pivot_wider(names_from = valu, values_from = value) %>%
filter(county == "Guilford") %>%
ggplot(aes(years, mean))
geom_col()
geom_errorbar(aes(ymin = ymin, ymax = ymax), width = 0.25)
geom_hline(aes(yintercept = mean(mean)), linetype = 2)
theme_gray(base_size = 16)
ggtitle("Guilford")
CodePudding user response：
You get the error because the second data frame is not in the appropriate format: by pivoting we could set ymin and ymax to columns: Then we could filter only once and apply the code:
library(tidyverse)
samp1 %>%
pivot_wider(names_from = valu,
values_from = value) %>%
filter(county == "Camden") %>%
ggplot( aes(x=years, y=mean, group=years))
labs(title = "Number of Days in April-August with Suitable Weather for\nLate Blight Sporulation in Camden, N.C.", y="Number of Days", x="Year" )
geom_col(position = "dodge")
geom_errorbar(aes(ymin=ymin, ymax=ymax), position="dodge")
theme(axis.text.x = element_text(face="bold"), axis.title.x = element_text(size=14),
axis.text.y = element_text(face="bold"), axis.title.y = element_text(size=14),
title = element_text(size=12))
geom_hline(aes(yintercept = mean(mean),
linetype='Mean for 2012-2016'))
scale_linetype_manual(name="Legend", values=c("Mean for 2012-2016"=1) )
