英文:
Changing order in x axis with multiple factors
问题
我创建了一个图表，显示不同因子水平的均值，但对于分类因子（Pretreatment），我希望它按顺序显示为None-Mortar-Discs，而不是默认的字母顺序Discs-Motar-None。以下是代码和当前图表的图片：
> dput(scenedesmus)structure(list(Temperature = structure(c(1L, 1L, 1L, 1L, 1L,1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("20","30", "40"), class = "factor"), Time = structure(c(1L, 1L, 2L,2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L), .Label = c("0.5","1", "2"), class = "factor"), Ratio = structure(c(1L, 1L, 2L,2L, 3L, 3L, 2L, 2L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 2L, 2L), .Label = c("3","6", "12"), class = "factor"), Pretreatment = structure(c(1L,1L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 1L,1L), .Label = c("None", "Mortar", "Discs"), class = "factor"),PRY = c(7.10618979550317, 6.99107348052751, 9.81654489395678,10.0937678454159, 15.8872899104855, 16.5147395153748, 15.6085073784574,15.8904572330355, 9.85155639002801, 10.3291566375677, 9.81557388225615,10.1774212169006, 12.0972576247432, 11.1350551614397, 14.7591913822601,14.8846506719242, 9.47697977090569, 10.8328555963545), CRY = c(12.9913707456184,13.2037056981015, 14.6223886369729, 14.4156689100426, 20.8510599220091,21.1334682925674, 20.7517385553227, 20.3784601114164, 13.1903022986714,12.7481614338955, 14.3799945987187, 15.1548695641213, 16.3653561008515,17.3492383422838, 22.4414097199122, 22.4340213280367, 14.0895227253865,16.0388931794408), PCR = c(0.546993072143667, 0.529478135939726,0.671336615218633, 0.700194205929921, 0.761941597689038,0.781449560798454, 0.752154203217537, 0.779767320305684,0.746878742196859, 0.810246770966047, 0.682585366418063,0.671561122571146, 0.739199168670324, 0.641818098394623,0.657676659642481, 0.663485625438106, 0.672626032522028,0.675411668071984)), row.names = c(NA, -18L), class = c("tbl_df","tbl", "data.frame"))
scenedesmus %>%mutate(across(Temperature:Pretreatment, as.character)) %>%pivot_longer(Temperature:Pretreatment) %>%mutate(value = factor(value, levels(factor(value))[c(10:12, 6, 9, 3, 5, 7:8, 1:2, 4)])) %>%ggplot(aes(value, PCR, group = name, color = name)) +geom_point(stat = 'summary', fun = mean) +geom_hline(yintercept = mean(scenedesmus$PCR, na.rm=TRUE), linetype='dotted', col = 'grey', size=1.5) +stat_summary(fun.data="mean_sdl", fun.args = list(mult = 1), geom="errorbar", width = 0.2, size=1, alpha = 0.5) +scale_y_continuous(limits = c(0.5, 0.9)) +geom_line(stat = 'summary', fun = mean, size=1) +facet_grid(~name, scales = 'free_x', switch = 'x') +scale_color_manual(values = c("#0072B2", "#D55E00", "#CC79A7","#009E73")) +coord_cartesian(clip = 'off') +geom_vline(data = data.frame(a = 0.4, name = 'Pretreatment'),aes(xintercept = a)) +theme_classic(base_size = 20) +theme(strip.placement = 'outside',legend.position="none",strip.background = element_blank(),axis.title.x = element_blank(),panel.grid.major.x = element_blank(),panel.spacing.x = unit(0, 'mm'),axis.ticks = element_line(),axis.line.x = element_line(),axis.title.y = element_text(size=20, face="bold"),strip.text = element_text(face = "bold")) +labs(y = "Protein carbohydrate ratio")
英文:
I created a plot with the mean values of different factor levels, but for the categorical factor (Pretreatment) I want it in the order None-Mortar-Discs, instead of the automatically alphabetical order Discs-Motar-None. Here is the code and a picture of the current plot:
> dput(scenedesmus)structure(list(Temperature = structure(c(1L, 1L, 1L, 1L, 1L,1L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("20","30", "40"), class = "factor"), Time = structure(c(1L, 1L, 2L,2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L, 1L, 1L, 2L, 2L, 3L, 3L), .Label = c("0.5","1", "2"), class = "factor"), Ratio = structure(c(1L, 1L, 2L,2L, 3L, 3L, 2L, 2L, 3L, 3L, 1L, 1L, 3L, 3L, 1L, 1L, 2L, 2L), .Label = c("3","6", "12"), class = "factor"), Pretreatment = structure(c(1L,1L, 2L, 2L, 3L, 3L, 3L, 3L, 1L, 1L, 2L, 2L, 2L, 2L, 3L, 3L, 1L,1L), .Label = c("None", "Mortar", "Discs"), class = "factor"),PRY = c(7.10618979550317, 6.99107348052751, 9.81654489395678,10.0937678454159, 15.8872899104855, 16.5147395153748, 15.6085073784574,15.8904572330355, 9.85155639002801, 10.3291566375677, 9.81557388225615,10.1774212169006, 12.0972576247432, 11.1350551614397, 14.7591913822601,14.8846506719242, 9.47697977090569, 10.8328555963545), CRY = c(12.9913707456184,13.2037056981015, 14.6223886369729, 14.4156689100426, 20.8510599220091,21.1334682925674, 20.7517385553227, 20.3784601114164, 13.1903022986714,12.7481614338955, 14.3799945987187, 15.1548695641213, 16.3653561008515,17.3492383422838, 22.4414097199122, 22.4340213280367, 14.0895227253865,16.0388931794408), PCR = c(0.546993072143667, 0.529478135939726,0.671336615218633, 0.700194205929921, 0.761941597689038,0.781449560798454, 0.752154203217537, 0.779767320305684,0.746878742196859, 0.810246770966047, 0.682585366418063,0.671561122571146, 0.739199168670324, 0.641818098394623,0.657676659642481, 0.663485625438106, 0.672626032522028,0.675411668071984)), row.names = c(NA, -18L), class = c("tbl_df","tbl", "data.frame"))
scenedesmus %>%mutate(across(Temperature:Pretreatment, as.character)) %>%pivot_longer(Temperature:Pretreatment) %>%mutate(value = factor(value, levels(factor(value))[c(10:12, 6, 9, 3, 5, 7:8, 1:2, 4)])) %>%ggplot(aes(value, PCR, group = name, color = name)) +geom_point(stat = 'summary', fun = mean) +geom_hline(yintercept = mean(scenedesmus$PCR, na.rm=TRUE),linetype='dotted', col = 'grey', size=1.5) +stat_summary(fun.data="mean_sdl", fun.args = list(mult = 1), geom="errorbar", width = 0.2, size=1, alpha = 0.5) +scale_y_continuous(limits = c(0.5, 0.9)) +geom_line(stat = 'summary', fun = mean, size=1) +facet_grid(~name, scales = 'free_x', switch = 'x') +scale_color_manual(values = c("#0072B2", "#D55E00", "#CC79A7","#009E73")) +coord_cartesian(clip = 'off') +geom_vline(data = data.frame(a = 0.4, name = 'Pretreatment'),aes(xintercept = a)) +theme_classic(base_size = 20) +theme(strip.placement = 'outside',legend.position="none",strip.background = element_blank(),axis.title.x = element_blank(),panel.grid.major.x = element_blank(),panel.spacing.x = unit(0, 'mm'),axis.ticks = element_line(),axis.line.x = element_line(),axis.title.y = element_text(size=20, face="bold"),strip.text = element_text(face = "bold")) +labs(y = "Protein carbohydrate ratio")
答案1
得分: 2
你已经在你的 mutate() 中对级别进行了排序，只需按照你实际想要的顺序重新排列它们。
mutate(value = factor(value, levels(factor(value))[c(12:10, 6, 9, 3, 5, 7:8, 1:2, 4)])) %>%# ^ 而不是 10:12
英文:
You are already ordering the levels in your mutate(), just reorder them to the order you actually want
mutate(value = factor(value, levels(factor(value))[c(12:10, 6, 9, 3, 5, 7:8, 1:2, 4)])) %>%# ^ rather than 10:12
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