我有以下data.table
.map{UInt8($0)}
我跑
decomp1 <- data.table(V2 = c("Sp", "Sp", "Su", "Sp", "Su", "Su", "X",
"Su", "X", "Su", "X", "X", "Sp", "Sp", "X", "Su", "X", "Sp",
"X", "Su", "Sp", "Su", "Su", "X", "Sp", "Sp", "Sp", "Su", "Su",
"X", "Sp", "Sp", "X", "Su", "X", "Su", "Sp", "X", "Su", "Sp",
"Sp", "Su"),
V3 = c("Sp", "Sp", "Su_6", "Sp", "Su_6", "Su_6",
"X", "Su_6", "X", "Su_6", "X", "X", "Sp", "Sp", "X", "Su_6",
"X", "Sp", "X", "Su_6", "Sp", "Su_6", "Su_6", "X", "Sp", "Sp",
"Sp", "Su_6", "Su_6", "X", "Sp", "Sp", "X", "Su_6", "X", "Su_6",
"Sp", "X", "Su_6", "Sp", "Sp", "Su_6"),
V4 = c("Va", "Va", "Pr",
"Va", "Pr", "Pr", "Tr", "He", "He", "He", "Tr", "He", "He", "He",
"Tr", "He", "He", "He", "Qu", "Qu", "Qu", "Qu", "NP", "Qu", "Qu",
"NP", "Qu", "NP", "Qu", "Qu", "NP", "NP", "NP", "NP", "NP", "Tr",
"Tr", "NP", "Tr", "Tr", "Tr", "Tr"),
V5 = c("Non", "Long", "Non",
"Ca", "Long", "Ca", "Non", "Non", "Non", "Long", "Long", "Long",
"Non", "Long", "Ca", "Ca", "Ca", "Ca", "Non", "Non", "Non", "Long",
"Non", "Long", "Long", "Non", "Ca", "Long", "Ca", "Ca", "Long",
"Ca", "Non", "Ca", "Long", "Non", "Non", "Ca", "Long", "Long",
"Ca", "Ca"),
V6 = c("Total", "Total", "Total", "Total", "Total",
"Total", "Total", "Total", "Total", "Total", "Total", "Total",
"Total", "Total", "Total", "Total", "Total", "Total", "Total",
"Total", "Total", "Total", "Total", "Total", "Total", "Total",
"Total", "Total", "Total", "Total", "Total", "Total", "Total",
"Total", "Total", "Total", "Total", "Total", "Total", "Total",
"Total", "Total"),
V1 = c("0.072384480,", "0.005913364,", "0.084688599,",
"0.014997295,", "0.010088229,", "0.020780549,", "0.244325980,",
"0.269335944,", "0.282962793,", "0.018655723,", "0.051010924,",
"0.014688654,", "0.298544133,", "0.026934186,", "0.052777085,",
"0.060859581,", "0.051597466,", "0.025747971,", "0.374481663,",
"0.379704887,", "0.390599270,", "0.030278558,", "0.410034427,",
"0.051577777,", "0.035755516,", "0.440449409,", "0.016192095,",
"0.040907457,", "0.050172704,", "0.037228066,", "0.033683551,",
"0.016825497,", "0.493787903,", "0.045299959,", "0.032781898,",
"0.556733851,", "0.577734392,", "0.063572428,", "0.038519396,",
"0.039316251,", "0.017420358,", "0.044930589)"),
V7 = c(0.07238448,
0.07829784, 0.0846886, 0.09329514, 0.09477683, 0.11555738, 0.24432598,
0.26933594, 0.28296279, 0.28799167, 0.2953369, 0.29765145, 0.29854413,
0.32547832, 0.34811399, 0.34885125, 0.34924891, 0.35122629, 0.37448166,
0.37970489, 0.39059927, 0.40998344, 0.41003443, 0.42605944, 0.42635479,
0.44044941, 0.44254688, 0.45094188, 0.46015615, 0.46328751, 0.47413296,
0.49095846, 0.4937879, 0.49624184, 0.5265698, 0.55673385, 0.57773439,
0.59014223, 0.59525325, 0.61705064, 0.634471, 0.64018384))
正如您所看到的,“颜色”的顺序不正确。所以实际上我最想得到的是相同的情节,具有相同的数字,但每行中每列的颜色顺序(从下到上)应为蓝色&gt;黄色&gt;红色,而不是红色&gt;黄色&gt;蓝色。我不知道为什么会发生这种情况
答案 0 :(得分:1)
你在运行什么版本的ggplot2?以下内容:
ggplot(decomp1, aes(x=V4,y=V1,fill=V5, label=paste0(round(V1,3)*100,"%"))) +
geom_bar(stat="identity", width=0.5) +
geom_text(aes(y=V7-V1/2), col="white", size=3) +
geom_text(data=decomp1[,.(V1=sum(V1),V5="Non"), by=.(V4,V3)],
aes(y=V1, vjust=-1), fontface="bold") +
scale_fill_manual(values=c("Non"="#1581A4", "Long"="#FFA600", "Ca"="#B50000")) +
scale_y_continuous(label=scales::percent,limits = c(0,0.7)) +
facet_grid(V3~.) +
theme(legend.title=element_blank(),
axis.title.x=element_blank(),
axis.title.y=element_blank())
生成:
根据最新的ggplot2 pkg。
我们没有theme_pl()
,因此主题美学存在差异。
我 移动了aes()
以外的一些不属于那里的东西并更好地组织了剧情代码(我无法想象以原始格式调试任何东西) )但因子顺序决定了条形段的顺序,它似乎与最新的pkgs一起工作正常。
> session_info()
Session info -------------------------------------------------------------------------
setting value
version R version 3.3.2 (2016-10-31)
system x86_64, darwin13.4.0
ui RStudio (1.0.136)
language (EN)
collate en_US.UTF-8
tz America/New_York
date 2016-12-16
Packages -----------------------------------------------------------------------------
package * version date source
assertthat 0.1 2013-12-06 CRAN (R 3.3.0)
colorspace 1.2-6 2015-03-11 CRAN (R 3.3.0)
data.table * 1.9.8 2016-11-25 cran (@1.9.8)
devtools * 1.12.0 2016-06-24 CRAN (R 3.3.0)
digest 0.6.10 2016-08-02 CRAN (R 3.3.0)
ggplot2 * 2.2.0.9000 2016-12-16 Github (hadley/ggplot2@f6f9f9d)
gtable 0.2.0 2016-02-26 CRAN (R 3.3.0)
labeling 0.3 2014-08-23 CRAN (R 3.3.0)
lazyeval 0.2.0 2016-06-12 CRAN (R 3.3.0)
magrittr 1.5 2014-11-22 CRAN (R 3.3.0)
memoise 1.0.0 2016-01-29 CRAN (R 3.3.0)
munsell 0.4.3 2016-02-13 CRAN (R 3.3.0)
plyr 1.8.4 2016-06-08 CRAN (R 3.3.0)
Rcpp 0.12.8 2016-11-17 CRAN (R 3.3.2)
reshape2 1.4.2 2016-10-22 cran (@1.4.2)
rstudioapi 0.6 2016-06-27 CRAN (R 3.3.0)
scales 0.4.1.9000 2016-12-16 Github (hadley/scales@89c2a2f)
stringi 1.1.2 2016-10-01 CRAN (R 3.3.0)
stringr 1.1.0 2016-08-19 CRAN (R 3.3.0)
tibble 1.2 2016-08-26 CRAN (R 3.3.0)
withr 1.0.2 2016-06-20 CRAN (R 3.3.0)