ggplot2 - 手动将箱线图分面标签指定为 symbol/math 表达式
ggplot2 - Manually specifying boxplot facet labels as symbol/math expressions
我有一个名为 my_data 的 tibble 数据框，它看起来像这样：
> my_data
# A tibble: 60 x 4
SPECIES simulation_id psi_hat p_hat
<chr> <int> <dbl> <dbl>
1 Grey squirrel 74 0.527 0.306
2 Grey squirrel 102 0.526 0.316
3 Grey squirrel 142 0.527 0.309
4 Grey squirrel 121 0.527 0.309
5 Grey squirrel 25 0.526 0.317
6 Grey squirrel 50 0.527 0.309
7 Grey squirrel 67 0.491 0.326
8 Grey squirrel 19 0.527 0.306
9 Grey squirrel 174 0.527 0.302
10 Grey squirrel 46 0.527 0.309
# ... with 50 more rows
my_data中有三个不同的SPECIES。
我想为每个 SPECIES 绘制 psi_hat 和 p_hat 变量的箱线图。我开始像这样准备 tibble：
my_data_plot <- my_data %>%
gather("psi_hat", "p_hat", key = "parameter", value = "estimate")
然后像这样绘制它：
ggplot(data = my_data_plot, mapping = aes(x = SPECIES)) +
geom_boxplot(mapping = aes(y = estimate)) +
facet_grid(. ~ parameter)
这给了我：
我现在要做的是将刻面标记为实际的希腊符号，而不是例如"psi_hat" 这样 "psi_hat" 就会得到等同于 expression(hat(psi)) 的符号。
我知道在 facet_grid 中我可以使用 labeller = label_parse，但这意味着我的变量名必须是实际的表达式，但是当变量名必须是函数调用（即 hat(psi)）。例如，我尝试了 my_data <- my_data %>% rename(hat(psi) = "psi_hat") 这给了我这个错误：
Error: unexpected '=' in:
"my_data <- my_data %>%
rename(hat(psi) ="
我也考虑过 labeller = bquote，但这似乎要求我指定行 和 列，因为我在此图中只有列。
所以，我想知道我是否需要或有办法为这些方面标签手动定义表达式？还是有更多的算法方法来实现这一目标？
谢谢！
这里是 my_data 的 dput():
structure(list(SPECIES = c("Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Red fox", "Red fox", "Red fox",
"Red fox", "Red fox", "Red fox", "Red fox", "Red fox", "Red fox",
"Red fox", "Red fox", "Red fox", "Red fox", "Red fox", "Red fox",
"Red fox", "Red fox", "Red fox", "Red fox", "Red fox", "Roe Deer",
"Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer",
"Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer",
"Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer",
"Roe Deer"), simulation_id = c(74L, 102L, 142L, 121L, 25L, 50L,
67L, 19L, 174L, 46L, 162L, 31L, 199L, 147L, 163L, 18L, 170L,
172L, 106L, 157L, 158L, 200L, 187L, 103L, 144L, 77L, 78L, 139L,
75L, 57L, 171L, 195L, 90L, 136L, 109L, 30L, 152L, 97L, 74L, 8L,
161L, 73L, 130L, 151L, 150L, 184L, 198L, 177L, 97L, 88L, 123L,
190L, 83L, 75L, 143L, 159L, 103L, 16L, 200L, 2L), psi_hat = c(0.526863413764263,
0.525835491514182, 0.526515540307052, 0.526515540305866, 0.525668605170743,
0.526515540309525, 0.491205525300549, 0.526863413760793, 0.527216807861263,
0.526515540305866, 0.526515540306427, 0.526003604543373, 0.526003604547465,
0.527039406294591, 0.491512271725946, 0.526343604414775, 0.526515540311415,
0.490421555053814, 0.526003604541449, 0.526688801109048, 0.79766843868635,
0.801911295111649, 0.797668438685209, 0.79766843868356, 0.736091175845588,
0.801911294988272, 0.797668438684876, 0.797668438686537, 0.764665429923081,
0.806326437262252, 0.769630414385322, 0.806326437300003, 0.733141462334417,
0.801911295128621, 0.777085591061084, 0.801911295171974, 0.703578316906639,
0.777085591642251, 0.793615265014951, 0.806326437459794, 0.662677377511043,
0.701654360968483, 0.704629679152389, 0.70622149033349, 0.663754148939585,
0.704629679094459, 0.705416487515374, 0.677464341430293, 0.707045218951227,
0.662338556587023, 0.674456696561803, 0.701654360967044, 0.639650521202062,
0.625380503760432, 0.704629679094605, 0.664561357366103, 0.704629679143759,
0.636859548660175, 0.66375414894085, 0.707045219029558), p_hat = c(0.305763297214646,
0.315819064091298, 0.309115591855344, 0.309115591855175, 0.317494717397372,
0.309115591855145, 0.326303719905328, 0.305763297214592, 0.302410595448716,
0.309115591855175, 0.309115591855139, 0.314143327866378, 0.314143327866402,
0.304086998925611, 0.322825888575185, 0.310791594807592, 0.309115591855151,
0.335654773573103, 0.314143327866529, 0.307439493743849, 0.0690109229482788,
0.0677020110780009, 0.0690109229483345, 0.0690109229474338, 0.0744703724155286,
0.0677020110840996, 0.0690109229257095, 0.0690109229256593, 0.0704604468308165,
0.0663903378649822, 0.0691283355131073, 0.0663903378091044, 0.0737444081467713,
0.0677020110873479, 0.0665479524846632, 0.0677020110750217, 0.073966658329169,
0.0665479525245426, 0.0703192747621257, 0.0663903375835434, 0.166196509352831,
0.157146399287494, 0.152026850762839, 0.14946227707946, 0.163675003941755,
0.152026850344473, 0.150744974403108, 0.15740696035152, 0.148178744896067,
0.167783160277052, 0.162569260757996, 0.157146399287514, 0.162501076719809,
0.177160578693552, 0.152026850344548, 0.162149934290892, 0.152026850679299,
0.168221557280052, 0.163675003941561, 0.148178745461308)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -60L))
你可以试试这个。因为你的数据是长格式的，所以我使用 case_when 来重命名带有表达式的变量，以便标记器读取
library(tidyverse)
df %>%
gather(key = "parameter", value = "estimate", -SPECIES, -simulation_id) %>%
mutate(parameter = case_when(
parameter == "psi_hat" ~ "hat(psi)",
parameter == "p_hat" ~ "hat(p)"
)) %>%
ggplot(aes(x = SPECIES)) +
geom_boxplot(mapping = aes(y = estimate)) +
facet_grid(. ~ parameter, labeller = label_parsed)
由 reprex 创建于 2018-08-18
包 (v0.2.0).
我有一个名为 my_data 的 tibble 数据框，它看起来像这样：
> my_data
# A tibble: 60 x 4
SPECIES simulation_id psi_hat p_hat
<chr> <int> <dbl> <dbl>
1 Grey squirrel 74 0.527 0.306
2 Grey squirrel 102 0.526 0.316
3 Grey squirrel 142 0.527 0.309
4 Grey squirrel 121 0.527 0.309
5 Grey squirrel 25 0.526 0.317
6 Grey squirrel 50 0.527 0.309
7 Grey squirrel 67 0.491 0.326
8 Grey squirrel 19 0.527 0.306
9 Grey squirrel 174 0.527 0.302
10 Grey squirrel 46 0.527 0.309
# ... with 50 more rows
my_data中有三个不同的SPECIES。
我想为每个 SPECIES 绘制 psi_hat 和 p_hat 变量的箱线图。我开始像这样准备 tibble：
my_data_plot <- my_data %>%
gather("psi_hat", "p_hat", key = "parameter", value = "estimate")
然后像这样绘制它：
ggplot(data = my_data_plot, mapping = aes(x = SPECIES)) +
geom_boxplot(mapping = aes(y = estimate)) +
facet_grid(. ~ parameter)
这给了我：
我现在要做的是将刻面标记为实际的希腊符号，而不是例如"psi_hat" 这样 "psi_hat" 就会得到等同于 expression(hat(psi)) 的符号。
我知道在 facet_grid 中我可以使用 labeller = label_parse，但这意味着我的变量名必须是实际的表达式，但是当变量名必须是函数调用（即 hat(psi)）。例如，我尝试了 my_data <- my_data %>% rename(hat(psi) = "psi_hat") 这给了我这个错误：
Error: unexpected '=' in:
"my_data <- my_data %>%
rename(hat(psi) ="
我也考虑过 labeller = bquote，但这似乎要求我指定行 和 列，因为我在此图中只有列。
所以，我想知道我是否需要或有办法为这些方面标签手动定义表达式？还是有更多的算法方法来实现这一目标？
谢谢！
这里是 my_data 的 dput():
structure(list(SPECIES = c("Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Grey squirrel", "Grey squirrel",
"Grey squirrel", "Grey squirrel", "Red fox", "Red fox", "Red fox",
"Red fox", "Red fox", "Red fox", "Red fox", "Red fox", "Red fox",
"Red fox", "Red fox", "Red fox", "Red fox", "Red fox", "Red fox",
"Red fox", "Red fox", "Red fox", "Red fox", "Red fox", "Roe Deer",
"Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer",
"Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer",
"Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer", "Roe Deer",
"Roe Deer"), simulation_id = c(74L, 102L, 142L, 121L, 25L, 50L,
67L, 19L, 174L, 46L, 162L, 31L, 199L, 147L, 163L, 18L, 170L,
172L, 106L, 157L, 158L, 200L, 187L, 103L, 144L, 77L, 78L, 139L,
75L, 57L, 171L, 195L, 90L, 136L, 109L, 30L, 152L, 97L, 74L, 8L,
161L, 73L, 130L, 151L, 150L, 184L, 198L, 177L, 97L, 88L, 123L,
190L, 83L, 75L, 143L, 159L, 103L, 16L, 200L, 2L), psi_hat = c(0.526863413764263,
0.525835491514182, 0.526515540307052, 0.526515540305866, 0.525668605170743,
0.526515540309525, 0.491205525300549, 0.526863413760793, 0.527216807861263,
0.526515540305866, 0.526515540306427, 0.526003604543373, 0.526003604547465,
0.527039406294591, 0.491512271725946, 0.526343604414775, 0.526515540311415,
0.490421555053814, 0.526003604541449, 0.526688801109048, 0.79766843868635,
0.801911295111649, 0.797668438685209, 0.79766843868356, 0.736091175845588,
0.801911294988272, 0.797668438684876, 0.797668438686537, 0.764665429923081,
0.806326437262252, 0.769630414385322, 0.806326437300003, 0.733141462334417,
0.801911295128621, 0.777085591061084, 0.801911295171974, 0.703578316906639,
0.777085591642251, 0.793615265014951, 0.806326437459794, 0.662677377511043,
0.701654360968483, 0.704629679152389, 0.70622149033349, 0.663754148939585,
0.704629679094459, 0.705416487515374, 0.677464341430293, 0.707045218951227,
0.662338556587023, 0.674456696561803, 0.701654360967044, 0.639650521202062,
0.625380503760432, 0.704629679094605, 0.664561357366103, 0.704629679143759,
0.636859548660175, 0.66375414894085, 0.707045219029558), p_hat = c(0.305763297214646,
0.315819064091298, 0.309115591855344, 0.309115591855175, 0.317494717397372,
0.309115591855145, 0.326303719905328, 0.305763297214592, 0.302410595448716,
0.309115591855175, 0.309115591855139, 0.314143327866378, 0.314143327866402,
0.304086998925611, 0.322825888575185, 0.310791594807592, 0.309115591855151,
0.335654773573103, 0.314143327866529, 0.307439493743849, 0.0690109229482788,
0.0677020110780009, 0.0690109229483345, 0.0690109229474338, 0.0744703724155286,
0.0677020110840996, 0.0690109229257095, 0.0690109229256593, 0.0704604468308165,
0.0663903378649822, 0.0691283355131073, 0.0663903378091044, 0.0737444081467713,
0.0677020110873479, 0.0665479524846632, 0.0677020110750217, 0.073966658329169,
0.0665479525245426, 0.0703192747621257, 0.0663903375835434, 0.166196509352831,
0.157146399287494, 0.152026850762839, 0.14946227707946, 0.163675003941755,
0.152026850344473, 0.150744974403108, 0.15740696035152, 0.148178744896067,
0.167783160277052, 0.162569260757996, 0.157146399287514, 0.162501076719809,
0.177160578693552, 0.152026850344548, 0.162149934290892, 0.152026850679299,
0.168221557280052, 0.163675003941561, 0.148178745461308)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -60L))
你可以试试这个。因为你的数据是长格式的，所以我使用 case_when 来重命名带有表达式的变量，以便标记器读取
library(tidyverse)
df %>%
gather(key = "parameter", value = "estimate", -SPECIES, -simulation_id) %>%
mutate(parameter = case_when(
parameter == "psi_hat" ~ "hat(psi)",
parameter == "p_hat" ~ "hat(p)"
)) %>%
ggplot(aes(x = SPECIES)) +
geom_boxplot(mapping = aes(y = estimate)) +
facet_grid(. ~ parameter, labeller = label_parsed)
由 reprex 创建于 2018-08-18 包 (v0.2.0).