我正在嘗試根據值的某些條件重新著色條形圖上的條形。（它們是正面的還是負面的？它們是高于還是低于閾值？）。因為我對很多這些圖都做過，所以我認為最簡單的方法是根據這些條件創建一個列，其中包含我想要的條的顏色。這很容易，只需幾個 ifelse 陳述句。但是現在，問題是 ggplot 不會以正確的順序提取這些顏色。我已經嘗試了幾種不同的方法來做到這一點，但似乎無法做到正確。
這是為我們要繪制的第一個位置過濾的資料框模型，并帶有一些示例資料。我在底部提供了完整的 dput，因此您可以自己復制完整的示例。
species location test_residuals species_order color
1 species2 location1 -2.1121481 1 dodgerblue1
2 species1 location1 -1.4315793 2 lightblue1
3 species8 location1 0.3727298 3 lightgoldenrod1
4 species3 location1 -5.2163387 4 dodgerblue1
5 species6 location1 3.5301076 5 goldenrod1
6 species4 location1 -0.7546595 6 lightblue1
7 species10 location1 -0.1857843 7 lightblue1
8 species12 location1 -0.5199749 8 lightblue1
9 species7 location1 -2.1884659 9 dodgerblue1
10 species13 location1 4.7223194 10 goldenrod1
11 species11 location1 0.3374291 11 lightgoldenrod1
12 species9 location1 0.6245307 12 lightgoldenrod1
13 species5 location1 -0.3676778 13 lightblue1
當我嘗試這個
test.plot.1<- data1 %>%
filter(location == "location1") %>%
ggplot(aes(
reorder(x = species, species_order),
y= test_residuals,
fill = species))
geom_bar( stat= "identity")
ggtitle("Location 1")
theme_pubclean(
base_size = 14 )
theme(plot.title = element_text(hjust = 0.5),
legend.position = "none")
xlab("") ylab("Pearson Residuals")
scale_x_discrete(guide = guide_axis(angle = 45))
geom_abline(intercept = 2, slope = 0, linetype = "dotdash")
geom_abline(intercept = -2, slope = 0, linetype = "dotdash")
scale_fill_manual(values = color)
我收到錯誤“is_missing(values) 中的錯誤：找不到物件‘顏色’”
如果我改為指定資料框：
scale_fill_manual(values = data1$color)
我沒有收到錯誤，顏色托盤甚至是正確的，但是條本身的顏色不正確！
如果我在填充中指定另一個向量（例如顏色），我也會得到顏色錯誤的條形圖：
我想這可能是因為當您必須使用“data1$color”指定資料框時，過濾器功能不再適用，所以我按管道分解并創建了一個預先過濾以呼叫 ggplot 的資料框。但即使這個資料框是按排列順序排列的，條形仍然不是正確的顏色。
test.plot.df2<- data1 %>%
filter(location == "location1") %>%
arrange(species_order)
test.plot.2<- test.plot.df2 %>%
ggplot(aes(
reorder(x = species, species_order),
y= test_residuals,
fill = species))
geom_bar( stat= "identity")
ggtitle("Location 1")
theme_pubclean(
base_size = 14 )
theme(plot.title = element_text(hjust = 0.5),
legend.position = "none")
xlab("") ylab("Pearson Residuals")
scale_x_discrete(guide = guide_axis(angle = 45))
geom_abline(intercept = 2, slope = 0, linetype = "dotdash")
geom_abline(intercept = -2, slope = 0, linetype = "dotdash")
scale_fill_manual(values = test.plot.df2$color)
test.plot.2
產生：
我必須在某處出現語法錯誤，但我似乎無法找到生成的列顏色順序背后的邏輯，因此無法解決如何糾正所述語法錯誤。在我嘗試過的（很多很多）事情中，我創建了一個矢量來呼叫顏色
test.plot.df2<- data1 %>%
filter(location == "location1") %>%
arrange(species_order)
test_color1<- test.plot.df2$color
test.plot.2<- test.plot.df2 %>%
ggplot(aes(
reorder(x = species, species_order),
y= test_residuals,
fill = species))
geom_bar( stat= "identity")
ggtitle("Location 1")
theme_pubclean(
base_size = 14 )
theme(plot.title = element_text(hjust = 0.5),
legend.position = "none")
xlab("") ylab("Pearson Residuals")
scale_x_discrete(guide = guide_axis(angle = 45))
geom_abline(intercept = 2, slope = 0, linetype = "dotdash")
geom_abline(intercept = -2, slope = 0, linetype = "dotdash")
scale_fill_manual(values = test_color1)
test.plot.2
這會產生與上面相同的圖表。我還嘗試創建一個新列，以物種順序作為字符，并將其稱為填充。這再次產生了一個顏色錯誤的圖表：
test.plot.df3<- data1 %>%
filter(location == "location1") %>%
arrange(species_order) %>%
mutate(species_order_character = as.character(species_order))
test.plot.3<- test.plot.df3 %>%
ggplot(aes(
reorder(x = species, species_order),
y= test_residuals,
fill = species_order_character))
geom_bar( stat= "identity")
ggtitle("Location 1")
theme_pubclean(
base_size = 14 )
theme(plot.title = element_text(hjust = 0.5),
legend.position = "none")
xlab("") ylab("Pearson Residuals")
scale_x_discrete(guide = guide_axis(angle = 45))
geom_abline(intercept = 2, slope = 0, linetype = "dotdash")
geom_abline(intercept = -2, slope = 0, linetype = "dotdash")
scale_fill_manual(values = test.plot.df3$color)
test.plot.3
我已經黔驢技窮了。我知道對于每個圖表，我都可以手動輸入顏色，如下所示：
test.plot.4<-data1 %>%
filter(location == "location1") %>%
ggplot(aes(
reorder(x = species, species_order),
y= test_residuals,
fill = color))
geom_bar( stat= "identity")
ggtitle("Location 1")
theme_pubclean(
base_size = 14 )
theme(plot.title = element_text(hjust = 0.5),
legend.position = "none")
xlab("") ylab("Pearson Residuals")
scale_x_discrete(guide = guide_axis(angle = 45))
geom_abline(intercept = 2, slope = 0, linetype = "dotdash")
geom_abline(intercept = -2, slope = 0, linetype = "dotdash")
scale_fill_manual(values = c( "dodgerblue1","goldenrod1", "lightblue1", "lightgoldenrod1"))
test.plot.4
這會產生一個顏色正確的圖表，但是 1）我想避免每次手動執行此操作，因為我必須為不同的位置和不同的資料集重現它，以及 2）即使在這里我也無法計算找出為什么需要以這種方式訂購顏色（即：“goldenrod1”、“dodgerblue1”、“lightgoldenrod1”、“lightblue1”）以對應于正確的級別。
任何人都對這里發生的事情有任何見解，以及我如何能夠更正我的語法以便我可以直接從資料框中呼叫顏色？
非常感謝下面是重現我的資料框的完整代碼：
data1 <- as.data.frame(structure(list(species = c(
"species1", "species1", "species1",
"species1", "species1", "species1", "species2", "species2", "species2",
"species2", "species2", "species2", "species3", "species3", "species3",
"species3", "species3", "species3", "species4", "species4", "species4",
"species4", "species4", "species4", "species5", "species5", "species5",
"species5", "species5", "species5", "species6", "species6", "species6",
"species6", "species6", "species6", "species7", "species7", "species7",
"species7", "species7", "species7", "species8", "species8", "species8",
"species8", "species8", "species8", "species9", "species9", "species9",
"species9", "species9", "species9", "species10", "species10",
"species10", "species10", "species10", "species10", "species11",
"species11", "species11", "species11", "species11", "species11",
"species12", "species12", "species12", "species12", "species12",
"species12", "species13", "species13", "species13", "species13",
"species13", "species13"
), location = c(
"location1", "location2",
"location3", "location4", "location5", "location6", "location1",
"location2", "location3", "location4", "location5", "location6",
"location1", "location2", "location3", "location4", "location5",
"location6", "location1", "location2", "location3", "location4",
"location5", "location6", "location1", "location2", "location3",
"location4", "location5", "location6", "location1", "location2",
"location3", "location4", "location5", "location6", "location1",
"location2", "location3", "location4", "location5", "location6",
"location1", "location2", "location3", "location4", "location5",
"location6", "location1", "location2", "location3", "location4",
"location5", "location6", "location1", "location2", "location3",
"location4", "location5", "location6", "location1", "location2",
"location3", "location4", "location5", "location6", "location1",
"location2", "location3", "location4", "location5", "location6",
"location1", "location2", "location3", "location4", "location5",
"location6"
), test_residuals = c(
-1.43157930150306, -0.314316453493008,
-0.695141335636191, -2.50279485833503, 15.9593244074832, -3.33654341630138,
-2.11214812519871, -0.754659543030408, -2.3490433970076, -1.7153639945355,
19.798140868747, -3.92267054433899, -5.21633871800811, -2.78600907892934,
4.13596459214836, -2.35842831236716, -4.34026196885217, 8.57347502255589,
-0.754659543030408, -2.11214812519871, -1.7153639945355, 9.81355206430024,
-0.0987450246067016, -2.3490433970076, -0.367677794665814, -0.298606543279543,
-0.261519516774949, -0.131369364295332, -0.472983769840402, 0.781602686808182,
3.53010760821268, -5.58101185979998, -5.5626379561955, 5.74088803484089,
-12.2995673766017, 10.0851562256946, -2.18846593288851, -0.161746935435626,
-1.76434843091121, -1.28043017699489, 9.27256034587805, -4.25159798465366,
0.372729803108757, -1.46533093179302, 0.229469416155288, 6.81036162101337,
-2.23476643015094, 0.351490912112304, 0.624530722145124, 1.07723113193857,
-0.262738728590663, -0.945967539680804, 3.3007673589212, -1.36569858688998,
-0.18578433666679, -0.519974923799824, -0.422293423319278, 5.03783441267317,
-0.965694731846794, -0.668900062090651, 0.337429125033733, -0.656846821476658,
-0.250681398015413, -0.153477341599593, -1.30759758387474, 0.686219077483926,
-0.519974923799824, -0.18578433666679, -0.668900062090651, -0.422293423319278,
-0.36984444744839, 1.10535312007138, 4.72231943431065, 0.0138571578271046,
5.16352940820454, -4.08311797265573, -1.90430067033424, 0.0153780833066176
), species_order = c(
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 13L,
13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 9L, 9L, 9L,
9L, 9L, 9L, 3L, 3L, 3L, 3L, 3L, 3L, 12L, 12L, 12L, 12L, 12L,
12L, 7L, 7L, 7L, 7L, 7L, 7L, 11L, 11L, 11L, 11L, 11L, 11L, 8L,
8L, 8L, 8L, 8L, 8L, 10L, 10L, 10L, 10L, 10L, 10L
), color = c(
"lightblue1",
"lightblue1", "lightblue1", "dodgerblue1", "goldenrod1", "dodgerblue1",
"dodgerblue1", "lightblue1", "dodgerblue1", "lightblue1", "goldenrod1",
"dodgerblue1", "dodgerblue1", "dodgerblue1", "goldenrod1", "dodgerblue1",
"dodgerblue1", "goldenrod1", "lightblue1", "dodgerblue1", "lightblue1",
"goldenrod1", "lightblue1", "dodgerblue1", "lightblue1", "lightblue1",
"lightblue1", "lightblue1", "lightblue1", "lightgoldenrod1",
"goldenrod1", "dodgerblue1", "dodgerblue1", "goldenrod1", "dodgerblue1",
"goldenrod1", "dodgerblue1", "lightblue1", "lightblue1", "lightblue1",
"goldenrod1", "dodgerblue1", "lightgoldenrod1", "lightblue1",
"lightgoldenrod1", "goldenrod1", "dodgerblue1", "lightgoldenrod1",
"lightgoldenrod1", "lightgoldenrod1", "lightblue1", "lightblue1",
"goldenrod1", "lightblue1", "lightblue1", "lightblue1", "lightblue1",
"goldenrod1", "lightblue1", "lightblue1", "lightgoldenrod1",
"lightblue1", "lightblue1", "lightblue1", "lightblue1", "lightgoldenrod1",
"lightblue1", "lightblue1", "lightblue1", "lightblue1", "lightblue1",
"lightgoldenrod1", "goldenrod1", "lightgoldenrod1", "goldenrod1",
"dodgerblue1", "lightblue1", "lightgoldenrod1"
)), class = "data.frame", row.names = c(
NA,
-78L
)))
uj5u.com熱心網友回復：
當您在資料框中明確計算顏色時，您可以使用scale_fill_identity. 唯一的其他變化是 fill 取自列colornot species。你得到：
test.plot.2<- test.plot.df2 %>%
ggplot(aes(
reorder(x = species, species_order),
y= test_residuals,
fill = color))
geom_bar( stat= "identity")
ggtitle("Location 1")
theme(plot.title = element_text(hjust = 0.5),
legend.position = "none")
xlab("") ylab("Pearson Residuals")
scale_x_discrete(guide = guide_axis(angle = 45))
geom_abline(intercept = 2, slope = 0, linetype = "dotdash")
geom_abline(intercept = -2, slope = 0, linetype = "dotdash")
scale_fill_identity()
test.plot.2
uj5u.com熱心網友回復：
根據您的描述，我認為您想要fill = color而不是fill = species. 然后，您可以scale_fill_manual通過設定名稱來構造該向量的值。
library(tidyverse)
df <- as.data.frame(structure(list(species = c(
"species1", "species1", "species1",
"species1", "species1", "species1", "species2", "species2", "species2",
"species2", "species2", "species2", "species3", "species3", "species3",
"species3", "species3", "species3", "species4", "species4", "species4",
"species4", "species4", "species4", "species5", "species5", "species5",
"species5", "species5", "species5", "species6", "species6", "species6",
"species6", "species6", "species6", "species7", "species7", "species7",
"species7", "species7", "species7", "species8", "species8", "species8",
"species8", "species8", "species8", "species9", "species9", "species9",
"species9", "species9", "species9", "species10", "species10",
"species10", "species10", "species10", "species10", "species11",
"species11", "species11", "species11", "species11", "species11",
"species12", "species12", "species12", "species12", "species12",
"species12", "species13", "species13", "species13", "species13",
"species13", "species13"
), location = c(
"location1", "location2",
"location3", "location4", "location5", "location6", "location1",
"location2", "location3", "location4", "location5", "location6",
"location1", "location2", "location3", "location4", "location5",
"location6", "location1", "location2", "location3", "location4",
"location5", "location6", "location1", "location2", "location3",
"location4", "location5", "location6", "location1", "location2",
"location3", "location4", "location5", "location6", "location1",
"location2", "location3", "location4", "location5", "location6",
"location1", "location2", "location3", "location4", "location5",
"location6", "location1", "location2", "location3", "location4",
"location5", "location6", "location1", "location2", "location3",
"location4", "location5", "location6", "location1", "location2",
"location3", "location4", "location5", "location6", "location1",
"location2", "location3", "location4", "location5", "location6",
"location1", "location2", "location3", "location4", "location5",
"location6"
), test_residuals = c(
-1.43157930150306, -0.314316453493008,
-0.695141335636191, -2.50279485833503, 15.9593244074832, -3.33654341630138,
-2.11214812519871, -0.754659543030408, -2.3490433970076, -1.7153639945355,
19.798140868747, -3.92267054433899, -5.21633871800811, -2.78600907892934,
4.13596459214836, -2.35842831236716, -4.34026196885217, 8.57347502255589,
-0.754659543030408, -2.11214812519871, -1.7153639945355, 9.81355206430024,
-0.0987450246067016, -2.3490433970076, -0.367677794665814, -0.298606543279543,
-0.261519516774949, -0.131369364295332, -0.472983769840402, 0.781602686808182,
3.53010760821268, -5.58101185979998, -5.5626379561955, 5.74088803484089,
-12.2995673766017, 10.0851562256946, -2.18846593288851, -0.161746935435626,
-1.76434843091121, -1.28043017699489, 9.27256034587805, -4.25159798465366,
0.372729803108757, -1.46533093179302, 0.229469416155288, 6.81036162101337,
-2.23476643015094, 0.351490912112304, 0.624530722145124, 1.07723113193857,
-0.262738728590663, -0.945967539680804, 3.3007673589212, -1.36569858688998,
-0.18578433666679, -0.519974923799824, -0.422293423319278, 5.03783441267317,
-0.965694731846794, -0.668900062090651, 0.337429125033733, -0.656846821476658,
-0.250681398015413, -0.153477341599593, -1.30759758387474, 0.686219077483926,
-0.519974923799824, -0.18578433666679, -0.668900062090651, -0.422293423319278,
-0.36984444744839, 1.10535312007138, 4.72231943431065, 0.0138571578271046,
5.16352940820454, -4.08311797265573, -1.90430067033424, 0.0153780833066176
), species_order = c(
2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L,
1L, 1L, 4L, 4L, 4L, 4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 13L,
13L, 13L, 13L, 13L, 13L, 5L, 5L, 5L, 5L, 5L, 5L, 9L, 9L, 9L,
9L, 9L, 9L, 3L, 3L, 3L, 3L, 3L, 3L, 12L, 12L, 12L, 12L, 12L,
12L, 7L, 7L, 7L, 7L, 7L, 7L, 11L, 11L, 11L, 11L, 11L, 11L, 8L,
8L, 8L, 8L, 8L, 8L, 10L, 10L, 10L, 10L, 10L, 10L
), color = c(
"lightblue1",
"lightblue1", "lightblue1", "dodgerblue1", "goldenrod1", "dodgerblue1",
"dodgerblue1", "lightblue1", "dodgerblue1", "lightblue1", "goldenrod1",
"dodgerblue1", "dodgerblue1", "dodgerblue1", "goldenrod1", "dodgerblue1",
"dodgerblue1", "goldenrod1", "lightblue1", "dodgerblue1", "lightblue1",
"goldenrod1", "lightblue1", "dodgerblue1", "lightblue1", "lightblue1",
"lightblue1", "lightblue1", "lightblue1", "lightgoldenrod1",
"goldenrod1", "dodgerblue1", "dodgerblue1", "goldenrod1", "dodgerblue1",
"goldenrod1", "dodgerblue1", "lightblue1", "lightblue1", "lightblue1",
"goldenrod1", "dodgerblue1", "lightgoldenrod1", "lightblue1",
"lightgoldenrod1", "goldenrod1", "dodgerblue1", "lightgoldenrod1",
"lightgoldenrod1", "lightgoldenrod1", "lightblue1", "lightblue1",
"goldenrod1", "lightblue1", "lightblue1", "lightblue1", "lightblue1",
"goldenrod1", "lightblue1", "lightblue1", "lightgoldenrod1",
"lightblue1", "lightblue1", "lightblue1", "lightblue1", "lightgoldenrod1",
"lightblue1", "lightblue1", "lightblue1", "lightblue1", "lightblue1",
"lightgoldenrod1", "goldenrod1", "lightgoldenrod1", "goldenrod1",
"dodgerblue1", "lightblue1", "lightgoldenrod1"
)), class = "data.frame", row.names = c(
NA,
-78L
))) %>%
as_tibble()
df <- df %>%
mutate(color = str_remove(color, "1"))
df %>%
ggplot()
aes(species, test_residuals, fill = color)
scale_fill_manual(values = set_names(unique(df$color), unique(df$color)))
geom_bar(stat = "identity")
facet_wrap(~location, scales = "free")
theme(axis.text.x = element_text(angle = 45))
使用reprex v2.0.2創建于 2022-11-11
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標籤：rggplot2土工棒