如何自动删除默认分配的部分图例?
How to automatically remove part of the legend that was assigned by default?
我有默认命名的图例(物种)。有没有办法自动删除 "wt" - 在图例中的单词末尾?谢谢!
这是代码
library(ggplot2)
library(tidyr)
library(dplyr)
weedweights<-data%>%
select(-ends_with("No"))%>%
gather(key=species, value=speciesmass, DIGSAWt:UnknownmonocotWt)%>%
mutate(realmass= (10*speciesmass) / samplearea.m.2.)%>%
group_by(Rot.Herb, species)%>%
summarize(avgrealmass=mean(realmass, na.rm=TRUE))%>%
filter(avgrealmass != "NaN")%>%
ungroup()
ww2 <- weedweights %>%
group_by(Rot.Herb) %>%
mutate(totalweedweight=sum(avgrealmass)) %>%
ungroup()
ggplot(weedweights, aes(x=1, y=avgrealmass, fill=species, order=avgrealmass)) +
geom_bar(position = "fill", stat="identity") +
facet_wrap(~ Rot.Herb) +
coord_polar("y") +
ggtitle("Weedbiomass by crop phase and herbicide regime")+
theme(plot.title = element_text(size=20, face="bold", vjust=2))+
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.ticks = element_blank())+
xlab("Weed dry biomass (kg per ha)")+
ylab("Crop phase and herbicide regime")
在这里你可以看到 data
正如 Zé Loff 所指出的,您可以替换 specie 变量
weedweights <- data%>%
select(-ends_with("No"))%>%
gather(key=species, value=speciesmass, DIGSAWt:UnknownmonocotWt)%>%
mutate(realmass= (10*speciesmass) / samplearea.m.2.)%>%
group_by(Rot.Herb, species)%>%
summarize(avgrealmass=mean(realmass, na.rm=TRUE))%>%
filter(avgrealmass != "NaN")%>%
ungroup() %>% mutate(species = gsub("Wt$", "", species))
我有默认命名的图例(物种)。有没有办法自动删除 "wt" - 在图例中的单词末尾?谢谢!
这是代码
library(ggplot2)
library(tidyr)
library(dplyr)
weedweights<-data%>%
select(-ends_with("No"))%>%
gather(key=species, value=speciesmass, DIGSAWt:UnknownmonocotWt)%>%
mutate(realmass= (10*speciesmass) / samplearea.m.2.)%>%
group_by(Rot.Herb, species)%>%
summarize(avgrealmass=mean(realmass, na.rm=TRUE))%>%
filter(avgrealmass != "NaN")%>%
ungroup()
ww2 <- weedweights %>%
group_by(Rot.Herb) %>%
mutate(totalweedweight=sum(avgrealmass)) %>%
ungroup()
ggplot(weedweights, aes(x=1, y=avgrealmass, fill=species, order=avgrealmass)) +
geom_bar(position = "fill", stat="identity") +
facet_wrap(~ Rot.Herb) +
coord_polar("y") +
ggtitle("Weedbiomass by crop phase and herbicide regime")+
theme(plot.title = element_text(size=20, face="bold", vjust=2))+
theme(axis.text.x = element_blank(), axis.text.y = element_blank(), axis.ticks = element_blank())+
xlab("Weed dry biomass (kg per ha)")+
ylab("Crop phase and herbicide regime")
在这里你可以看到 data
正如 Zé Loff 所指出的,您可以替换 specie 变量
weedweights <- data%>%
select(-ends_with("No"))%>%
gather(key=species, value=speciesmass, DIGSAWt:UnknownmonocotWt)%>%
mutate(realmass= (10*speciesmass) / samplearea.m.2.)%>%
group_by(Rot.Herb, species)%>%
summarize(avgrealmass=mean(realmass, na.rm=TRUE))%>%
filter(avgrealmass != "NaN")%>%
ungroup() %>% mutate(species = gsub("Wt$", "", species))