Add support for scale_*(drop = FALSE)
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描述
I am having trouble getting plotly to respect a drop=FALSE argument for a geom_point() plot where I color by factor and only 1 of the factor levels is represented in the dataset. The code below generates 3 simple plots to demonstrate this
- Simple iris plot, color by species, everything works properly
- Same plot as 1, but only include data corresponding to a single species. The legend does not display any of the levels.
- Same plot as 2, but adding the drop=FALSE argument to make the legend display all factor levels, even if they are not displayed in the dataset. The ggplot plot displays all levels in the legend, but the ggplotly version doesnt display any levels.
library(ggplot2)
library(plotly)
# plot all iris data
p <- ggplot(data=iris, aes(x=Petal.Width, y=Petal.Length, color=Species)) +
geom_point()
print(p)
layout(ggplotly(p))
# just plot setosa species
setosa <- subset(iris, Species=="setosa")
p_setosa <- ggplot(data=setosa, aes(x=Petal.Width, y=Petal.Length, color=Species)) +
geom_point()
print(p_setosa)
layout(ggplotly(p_setosa)
, margin = list(r=100))
# setosa only, add drop=FALSE argument
p_setosa_nodrop <- ggplot(data=setosa, aes(x=Petal.Width, y=Petal.Length, color=Species)) +
geom_point() +
scale_color_discrete(drop=FALSE)
print(p_setosa_nodrop)
layout(ggplotly(p_setosa_nodrop)
, margin = list(r=100))
Session info -------------------------------------------------------------
setting value
version R version 3.2.5 (2016-04-14)
system x86_64, mingw32
ui RStudio (0.99.486)
language (EN)
collate English_United States.1252
tz America/New_York
date 2016-04-19
Packages -----------------------------------------------------------------
package * version date source
assertthat 0.1 2013-12-06 CRAN (R 3.2.2)
base64enc 0.1-3 2015-07-28 CRAN (R 3.2.2)
colorspace 1.2-6 2015-03-11 CRAN (R 3.2.2)
DBI 0.3.1 2014-09-24 CRAN (R 3.2.2)
devtools 1.9.1 2015-09-11 CRAN (R 3.2.2)
digest 0.6.9 2016-01-08 CRAN (R 3.2.3)
dplyr 0.4.3 2015-09-01 CRAN (R 3.2.4)
ggplot2 * 2.1.0 2016-03-01 CRAN (R 3.2.4)
gridExtra 2.2.1 2016-02-29 CRAN (R 3.2.5)
gtable 0.2.0 2016-02-26 CRAN (R 3.2.3)
htmltools 0.3.5 2016-03-21 CRAN (R 3.2.5)
htmlwidgets 0.6 2016-02-25 CRAN (R 3.2.5)
httr 1.1.0 2016-01-28 CRAN (R 3.2.5)
jsonlite 0.9.19 2015-11-28 CRAN (R 3.2.5)
labeling 0.3 2014-08-23 CRAN (R 3.2.2)
magrittr 1.5 2014-11-22 CRAN (R 3.2.2)
memoise 0.2.1 2014-04-22 CRAN (R 3.2.2)
munsell 0.4.3 2016-02-13 CRAN (R 3.2.3)
plotly * 3.5.0 2016-04-19 Github (ropensci/plotly@43d882d)
plyr 1.8.3 2015-06-12 CRAN (R 3.2.2)
R6 2.1.2 2016-01-26 CRAN (R 3.2.3)
Rcpp 0.12.4 2016-03-26 CRAN (R 3.2.4)
scales 0.4.0 2016-02-26 CRAN (R 3.2.3)
tidyr 0.4.1 2016-02-05 CRAN (R 3.2.5)
viridis 0.3.4 2016-03-12 CRAN (R 3.2.4)
yaml 2.1.13 2014-06-12 CRAN (R 3.2.2)
贡献指南
从这里开始
- 先读完整个 Issue,再读项目的贡献指南。
- 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
- Fork 仓库,在一个分支上完成修改。
- 提交 Pull Request,并在描述里引用这个 Issue 编号。
调研方向
首先重现 issue 中的三个 iris 和 setosa 示例,比较 ggplot 和 ggplotly 对 scale_color_discrete(drop=FALSE) 的输出。跟踪 ggplotly 的 scale 和 legend 转换路径;当使用 drop=FALSE 时,setosa 图的 legend 保留所有因子级别,并且该行为由回归测试覆盖,即视为完成。
由索引模型根据 Issue 内容生成。
评估
- 技术栈
- r
- 领域
- data-visualization
- Issue 类型
- 缺陷
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 活跃度
- 停滞
- 描述清晰度
- 描述清楚
- 新手友好度
- 35/100