改变x轴的顺序ggplot2 facet wrap
Changing order of x axis ggplot2 facet wrap
我之前也问过类似的问题，但无法理解我的查询。这是一个完整的可重现示例。数据如下：
Fact<-structure(list(Code = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L,
18L, 18L, 18L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L), .Label = c("i", "m", "R", "T", "TA", "TB", "TS", "TU",
"U", "UJ", "UK", "UO", "UY", "UZ", "w", "X", "XHH", "XSW"), class = "factor"),
Initials = structure(c(7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("AA", "FF", "HH",
"II", "KJ", "KK", "LD", "LL", "TT", "WY"), class = "factor"),
FactorName = structure(c(3L, 11L, 1L, 9L, 8L, 2L, 10L, 7L,
5L, 6L, 4L, 9L, 10L, 11L, 2L, 1L, 8L, 7L, 3L, 6L, 5L, 4L,
1L, 3L, 4L, 2L, 6L, 8L, 5L, 11L, 7L, 9L, 10L, 6L, 9L, 3L,
8L, 7L, 5L, 4L, 2L, 1L, 10L, 11L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 1L, 9L, 1L, 4L, 10L, 11L, 2L, 3L, 5L, 6L,
7L, 8L, 9L, 7L, 1L, 4L, 8L, 6L, 5L, 3L, 10L, 2L, 11L, 11L,
10L, 5L, 1L, 2L, 6L, 9L, 4L, 8L, 3L, 7L, 2L, 1L, 4L, 5L,
3L, 8L, 10L, 11L, 7L, 6L, 9L, 6L, 10L, 11L, 5L, 4L, 9L, 1L,
7L, 8L, 3L, 2L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 3L, 2L, 6L, 5L, 4L, 1L, 11L, 8L, 10L, 7L, 9L, 9L, 2L,
3L, 6L, 7L, 8L, 11L, 4L, 1L, 5L, 10L, 4L, 7L, 8L, 9L, 1L,
2L, 5L, 6L, 10L, 11L, 3L, 11L, 10L, 8L, 3L, 6L, 7L, 9L, 5L,
2L, 1L, 4L, 4L, 5L, 3L, 6L, 1L, 2L, 10L, 8L, 11L, 7L, 9L,
9L, 10L, 11L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 6L, 3L, 4L,
5L, 11L, 7L, 9L, 10L, 1L, 2L, 8L, 4L, 9L, 1L, 5L, 8L, 6L,
10L, 11L, 2L, 3L, 7L), .Label = c("Exchange Rate Sensitivity",
"Growth", "Investment Trusts", "Leverage", "Liquidity", "Market Sensitivity",
"Medium-Term Momentum", "Short-Term Momentum", "Size", "Value",
"Volatility"), class = "factor"), Rating = c(0.982, 0.471,
0.532, 0.49, 0.791, 0.235, 0.0159, 0.425, 0.437, 0.642, 0.937,
0.229, 0.715, 0.537, 0.881, 0.857, 0.687, 0.409, 0.363, 0.567,
0.328, 0.645, 0.305, 0.826, 0.538, 0.381, 0.726, 0.0473,
0.884, 0.847, 0.063, 0.278, 0.452, 0.473, 0.981, 0.4, 0.774,
0.805, 0.982, 0.889, 0.281, 0.288, 0.765, 0.51, 0.784, 0.00634,
0.293, 0.0331, 0.874, 0.0806, 0.253, 0.295, 0.11, 0.775,
0.807, 0.164, 0.695, 0.792, 1, 0.57, 0.691, 0.432, 0.252,
0.318, 0.287, 0.249, 0.997, 0.486, 0.794, 0.228, 0.0345,
0.295, 0.342, 0.684, 0.346, 0.557, 0.929, 0.89, 0.356, 0.507,
0.85, 0.353, 0.171, 0.968, 0.915, 0.564, 0.89, 0.00313, 0.39,
0.274, 0.97, 0.213, 0.0792, 0.549, 0.916, 0.528, 0.248, 0.525,
0.631, 0.27, 0.0294, 0.221, 0.627, 0.628, 0.666, 0.0401,
0.784, 0.605, 0.66, 0.602, 0.094, 0.445, 0.389, 0.494, 0.104,
0.612, 0.834, 0.182, 0.298, 0.464, 0.338, 0.269, 0.843, 0.755,
0.238, 0.794, 0.266, 0.587, 0.653, 0.873, 0.354, 0.54, 0.451,
0.863, 0.611, 0.00506, 0.767, 0.477, 0.56, 0.722, 0.125,
0.667, 0.626, 0.139, 0.364, 0.943, 0.266, 0.223, 0.361, 0.473,
0.624, 0.167, 0.449, 0.148, 0.334, 0.523, 0.666, 0.503, 0.287,
0.193, 0.992, 0.468, 0.678, 0.235, 0.221, 0.566, 0.612, 0.00794,
0.249, 0.329, 0.695, 0.714, 0.236, 0.69, 0.187, 0.721, 0.173,
0.413, 0.833, 0.984, 0.604, 0.0594, 0.798, 0.684, 0.793,
0.186, 0.728, 0.923, 0.911, 0.608, 0.634, 0.73, 0.361, 0.0534,
0.251, 0.871, 0.948, 0.306, 0.483, 0.562, 0.205, 0.0798,
0.0288, 0.618, 0.784, 0.0358, 0.949, 0.134, 0.141)), .Names = c("Code",
"Initials", "FactorName", "Rating"), class = "data.frame", row.names = c(NA,
-209L))
还有我的剧情代码。
Exp<-ggplot(Fact)+ aes(x = Code, y = Rating, fill = Initials) + geom_col()
Exp<- Exp+facet_wrap(~FactorName, ncol = 3, drop = TRUE) + theme(axis.text.x = element_text(angle = 90, vjust = 0.5)) + labs(y="Active Rating") + labs(x="")
Exp
现在每个面的 x 轴顺序是按字母顺序排列的。相反，我想将首字母组合在一起，以便为每个因子名称图将条形颜色组合在一起。即所有红色彼此相邻，蓝色彼此相邻等等。任何帮助将不胜感激！
你可以试试
library(tidyverse)
as.tbl(Fact) %>%
arrange(Initials) %>%
mutate(Code2=factor(Code, levels=unique(Code))) %>%
ggplot(aes(x = Code2, y = Rating, fill = Initials)) + geom_col()+
facet_wrap(~FactorName, ncol = 3, drop = TRUE)
想法是根据 Initials 进行排列，然后使用 unique 根据数据框中的出现创建新的因子水平。
我之前也问过类似的问题，但无法理解我的查询。这是一个完整的可重现示例。数据如下：
Fact<-structure(list(Code = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 15L,
15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 15L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 5L, 5L,
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L,
5L, 5L, 5L, 5L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 8L,
8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 9L, 9L, 9L, 9L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L, 13L,
13L, 13L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L, 11L,
10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 10L, 12L, 12L,
12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 14L, 14L, 14L, 14L,
14L, 14L, 14L, 14L, 14L, 14L, 14L, 16L, 16L, 16L, 16L, 16L, 16L,
16L, 16L, 16L, 16L, 16L, 18L, 18L, 18L, 18L, 18L, 18L, 18L, 18L,
18L, 18L, 18L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L, 17L,
17L), .Label = c("i", "m", "R", "T", "TA", "TB", "TS", "TU",
"U", "UJ", "UK", "UO", "UY", "UZ", "w", "X", "XHH", "XSW"), class = "factor"),
Initials = structure(c(7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L, 7L,
7L, 7L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 9L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 6L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
4L, 4L, 4L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 6L, 9L,
9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 9L, 6L, 6L, 6L, 6L, 6L,
6L, 6L, 6L, 6L, 6L, 6L, 10L, 10L, 10L, 10L, 10L, 10L, 10L,
10L, 10L, 10L, 10L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 8L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L), .Label = c("AA", "FF", "HH",
"II", "KJ", "KK", "LD", "LL", "TT", "WY"), class = "factor"),
FactorName = structure(c(3L, 11L, 1L, 9L, 8L, 2L, 10L, 7L,
5L, 6L, 4L, 9L, 10L, 11L, 2L, 1L, 8L, 7L, 3L, 6L, 5L, 4L,
1L, 3L, 4L, 2L, 6L, 8L, 5L, 11L, 7L, 9L, 10L, 6L, 9L, 3L,
8L, 7L, 5L, 4L, 2L, 1L, 10L, 11L, 2L, 3L, 4L, 5L, 6L, 7L,
8L, 9L, 10L, 11L, 1L, 9L, 1L, 4L, 10L, 11L, 2L, 3L, 5L, 6L,
7L, 8L, 9L, 7L, 1L, 4L, 8L, 6L, 5L, 3L, 10L, 2L, 11L, 11L,
10L, 5L, 1L, 2L, 6L, 9L, 4L, 8L, 3L, 7L, 2L, 1L, 4L, 5L,
3L, 8L, 10L, 11L, 7L, 6L, 9L, 6L, 10L, 11L, 5L, 4L, 9L, 1L,
7L, 8L, 3L, 2L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L,
11L, 3L, 2L, 6L, 5L, 4L, 1L, 11L, 8L, 10L, 7L, 9L, 9L, 2L,
3L, 6L, 7L, 8L, 11L, 4L, 1L, 5L, 10L, 4L, 7L, 8L, 9L, 1L,
2L, 5L, 6L, 10L, 11L, 3L, 11L, 10L, 8L, 3L, 6L, 7L, 9L, 5L,
2L, 1L, 4L, 4L, 5L, 3L, 6L, 1L, 2L, 10L, 8L, 11L, 7L, 9L,
9L, 10L, 11L, 1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 6L, 3L, 4L,
5L, 11L, 7L, 9L, 10L, 1L, 2L, 8L, 4L, 9L, 1L, 5L, 8L, 6L,
10L, 11L, 2L, 3L, 7L), .Label = c("Exchange Rate Sensitivity",
"Growth", "Investment Trusts", "Leverage", "Liquidity", "Market Sensitivity",
"Medium-Term Momentum", "Short-Term Momentum", "Size", "Value",
"Volatility"), class = "factor"), Rating = c(0.982, 0.471,
0.532, 0.49, 0.791, 0.235, 0.0159, 0.425, 0.437, 0.642, 0.937,
0.229, 0.715, 0.537, 0.881, 0.857, 0.687, 0.409, 0.363, 0.567,
0.328, 0.645, 0.305, 0.826, 0.538, 0.381, 0.726, 0.0473,
0.884, 0.847, 0.063, 0.278, 0.452, 0.473, 0.981, 0.4, 0.774,
0.805, 0.982, 0.889, 0.281, 0.288, 0.765, 0.51, 0.784, 0.00634,
0.293, 0.0331, 0.874, 0.0806, 0.253, 0.295, 0.11, 0.775,
0.807, 0.164, 0.695, 0.792, 1, 0.57, 0.691, 0.432, 0.252,
0.318, 0.287, 0.249, 0.997, 0.486, 0.794, 0.228, 0.0345,
0.295, 0.342, 0.684, 0.346, 0.557, 0.929, 0.89, 0.356, 0.507,
0.85, 0.353, 0.171, 0.968, 0.915, 0.564, 0.89, 0.00313, 0.39,
0.274, 0.97, 0.213, 0.0792, 0.549, 0.916, 0.528, 0.248, 0.525,
0.631, 0.27, 0.0294, 0.221, 0.627, 0.628, 0.666, 0.0401,
0.784, 0.605, 0.66, 0.602, 0.094, 0.445, 0.389, 0.494, 0.104,
0.612, 0.834, 0.182, 0.298, 0.464, 0.338, 0.269, 0.843, 0.755,
0.238, 0.794, 0.266, 0.587, 0.653, 0.873, 0.354, 0.54, 0.451,
0.863, 0.611, 0.00506, 0.767, 0.477, 0.56, 0.722, 0.125,
0.667, 0.626, 0.139, 0.364, 0.943, 0.266, 0.223, 0.361, 0.473,
0.624, 0.167, 0.449, 0.148, 0.334, 0.523, 0.666, 0.503, 0.287,
0.193, 0.992, 0.468, 0.678, 0.235, 0.221, 0.566, 0.612, 0.00794,
0.249, 0.329, 0.695, 0.714, 0.236, 0.69, 0.187, 0.721, 0.173,
0.413, 0.833, 0.984, 0.604, 0.0594, 0.798, 0.684, 0.793,
0.186, 0.728, 0.923, 0.911, 0.608, 0.634, 0.73, 0.361, 0.0534,
0.251, 0.871, 0.948, 0.306, 0.483, 0.562, 0.205, 0.0798,
0.0288, 0.618, 0.784, 0.0358, 0.949, 0.134, 0.141)), .Names = c("Code",
"Initials", "FactorName", "Rating"), class = "data.frame", row.names = c(NA,
-209L))
还有我的剧情代码。
Exp<-ggplot(Fact)+ aes(x = Code, y = Rating, fill = Initials) + geom_col()
Exp<- Exp+facet_wrap(~FactorName, ncol = 3, drop = TRUE) + theme(axis.text.x = element_text(angle = 90, vjust = 0.5)) + labs(y="Active Rating") + labs(x="")
Exp
现在每个面的 x 轴顺序是按字母顺序排列的。相反，我想将首字母组合在一起，以便为每个因子名称图将条形颜色组合在一起。即所有红色彼此相邻，蓝色彼此相邻等等。任何帮助将不胜感激！
你可以试试
library(tidyverse)
as.tbl(Fact) %>%
arrange(Initials) %>%
mutate(Code2=factor(Code, levels=unique(Code))) %>%
ggplot(aes(x = Code2, y = Rating, fill = Initials)) + geom_col()+
facet_wrap(~FactorName, ncol = 3, drop = TRUE)
想法是根据 Initials 进行排列，然后使用 unique 根据数据框中的出现创建新的因子水平。