我希望ggplot2在Ggvis中的外观和感觉。有没有办法在ggvis中实现这个目标?
我有来自ggvis:
注意:
1)不喜欢白色背景(更好的是来自ggplot2的灰色背景
2)如您所见,条形图标有黑线。如何驾驭它?
我的代码:
Visitas_Por_Fuente %>%
ggvis(~Fuentes, ~sessions) %>%
layer_bars(width = 0.8, fill = ~Fuentes)
我的数据:
as.data.frame(structure(list(date = structure(c(1417410000, 1417410000, 1417410000,
1417410000, 1417410000, 1417410000, 1417496400, 1417496400, 1417496400,
1417496400, 1417496400, 1417496400, 1417496400, 1417582800, 1417582800,
1417582800, 1417582800, 1417582800, 1417582800, 1417582800, 1417669200,
1417669200, 1417669200, 1417669200, 1417669200, 1417669200, 1417669200,
1417755600, 1417755600, 1417755600, 1417755600, 1417755600, 1417755600,
1417842000, 1417842000, 1417842000, 1417842000, 1417842000, 1417842000,
1417842000, 1417928400, 1417928400, 1417928400, 1417928400, 1417928400,
1417928400, 1417928400, 1418014800, 1418014800, 1418014800, 1418014800,
1418014800, 1418014800, 1418014800, 1418101200, 1418101200, 1418101200,
1418101200, 1418101200, 1418101200, 1418101200, 1418187600, 1418187600,
1418187600, 1418187600, 1418187600, 1418187600, 1418187600, 1418274000,
1418274000, 1418274000, 1418274000, 1418274000, 1418274000, 1418274000,
1418360400, 1418360400, 1418360400, 1418360400, 1418360400, 1418360400,
1418360400, 1418446800, 1418446800, 1418446800, 1418446800, 1418446800,
1418446800, 1418446800, 1418533200, 1418533200, 1418533200, 1418533200,
1418533200, 1418533200, 1418533200, 1418619600, 1418619600, 1418619600,
1418619600, 1418619600, 1418619600, 1418619600, 1418706000, 1418706000,
1418706000, 1418706000, 1418706000, 1418706000, 1418706000, 1418792400,
1418792400, 1418792400, 1418792400, 1418792400, 1418792400, 1418792400,
1418878800, 1418878800, 1418878800, 1418878800, 1418878800, 1418878800,
1418878800, 1418965200, 1418965200, 1418965200, 1418965200, 1418965200,
1418965200, 1418965200, 1419051600, 1419051600, 1419051600, 1419051600,
1419051600, 1419051600, 1419051600, 1419138000, 1419138000, 1419138000,
1419138000, 1419138000, 1419138000, 1419224400, 1419224400, 1419224400,
1419224400, 1419224400, 1419224400, 1419224400, 1419310800, 1419310800,
1419310800, 1419310800, 1419310800, 1419310800, 1419397200, 1419397200,
1419397200, 1419397200, 1419397200, 1419397200, 1419397200, 1419483600,
1419483600, 1419483600, 1419483600, 1419483600, 1419483600, 1419483600,
1419570000, 1419570000, 1419570000, 1419570000, 1419570000, 1419570000,
1419656400, 1419656400, 1419656400, 1419656400, 1419656400, 1419656400,
1419742800, 1419742800, 1419742800, 1419742800, 1419742800, 1419742800,
1419742800, 1419829200, 1419829200, 1419829200, 1419829200, 1419829200,
1419829200, 1419915600, 1419915600, 1419915600, 1419915600, 1419915600,
1419915600, 1419915600, 1420002000, 1420002000, 1420002000, 1420002000,
1420002000), class = c("POSIXct", "POSIXt"), tzone = "America/Lima"),
Fuentes = c("Adwords", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Adwords",
"Campañas", "Directo", "Email", "Referencias", "SEO", "Social Media",
"Adwords", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Adwords",
"Campañas", "Directo", "Email", "Referencias", "SEO", "Social Media",
"Adwords", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Adwords",
"Campañas", "Directo", "Email", "Referencias", "SEO", "Social Media",
"Adwords", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Adwords",
"Campañas", "Directo", "Email", "Referencias", "SEO", "Social Media",
"Adwords", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Adwords",
"Campañas", "Directo", "Email", "Referencias", "SEO", "Social Media",
"Adwords", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Adwords",
"Campañas", "Directo", "Email", "Referencias", "SEO", "Social Media",
"Adwords", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Campañas",
"Directo", "Email", "Referencias", "SEO", "Social Media",
"Adwords", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Campañas",
"Directo", "Email", "Referencias", "SEO", "Social Media",
"Campañas", "Directo", "Email", "Referencias", "SEO", "Social Media",
"Adwords", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Campañas", "Directo", "Email", "Referencias",
"SEO", "Social Media", "Adwords", "Campañas", "Directo",
"Email", "Referencias", "SEO", "Social Media", "Directo",
"Email", "Referencias", "SEO", "Social Media"), sessions = c(10L,
326L, 18L, 527L, 999L, 52L, 3L, 7L, 324L, 19L, 498L, 933L,
44L, 5L, 12L, 363L, 15L, 546L, 1206L, 202L, 7L, 12L, 1122L,
27L, 1249L, 5168L, 607L, 17L, 432L, 22L, 527L, 1553L, 637L,
5L, 5L, 356L, 16L, 507L, 1901L, 487L, 4L, 8L, 312L, 30L,
500L, 1622L, 370L, 3L, 11L, 341L, 18L, 504L, 1312L, 352L,
2L, 13L, 1188L, 33L, 682L, 2008L, 1508L, 3L, 15L, 1086L,
36L, 646L, 2124L, 380L, 3L, 11L, 355L, 17L, 383L, 1054L,
236L, 2L, 9L, 321L, 15L, 370L, 1118L, 245L, 7L, 9L, 259L,
13L, 332L, 1261L, 230L, 3L, 7L, 539L, 9L, 626L, 2336L, 256L,
1L, 12L, 292L, 8L, 386L, 1070L, 220L, 1L, 12L, 278L, 9L,
393L, 1129L, 22L, 1L, 16L, 521L, 18L, 665L, 2400L, 20L, 1L,
13L, 204L, 7L, 258L, 789L, 11L, 2L, 12L, 253L, 6L, 277L,
803L, 9L, 1L, 4L, 262L, 8L, 324L, 960L, 9L, 3L, 442L, 15L,
516L, 1890L, 16L, 2L, 14L, 249L, 8L, 240L, 688L, 11L, 15L,
182L, 7L, 200L, 548L, 5L, 2L, 3L, 171L, 7L, 183L, 480L, 5L,
1L, 3L, 176L, 5L, 231L, 506L, 6L, 15L, 283L, 18L, 322L, 786L,
11L, 13L, 210L, 9L, 232L, 649L, 2L, 1L, 2L, 258L, 4L, 306L,
891L, 9L, 4L, 183L, 10L, 293L, 634L, 4L, 1L, 3L, 188L, 9L,
244L, 566L, 11L, 134L, 1L, 176L, 453L, 4L)), .Names = c("date",
"Fuentes", "sessions"), row.names = c(NA, -208L), class = c("grouped_df",
"tbl_df", "tbl", "data.frame"), vars = list(date), drop = TRUE))
答案 0 :(得分:11)
如果您的输出是Shiny应用程序或Shiny文档,则可以使用某些css更改背景颜色。请注意,只有当ggvis显示为svg(而不是canvas)时,这才能正常工作。另请注意,它无法在Rstudio查看器中正确显示。在创建ggvis之前在文档中的某处添加:
<style type="text/css">
rect.background {
fill: #E6E6E6 !important;
}
</style>
然后,要获得白色网格线并删除条形边框,您的代码应如下所示
Visitas_Por_Fuente %>%
ggvis(~Fuentes, ~sessions) %>%
layer_bars(width = 0.8, fill = ~Fuentes, strokeWidth := 0) %>%
add_axis("x", properties = axis_props(grid = list(stroke = "white"))) %>%
add_axis("y", properties = axis_props(grid = list(stroke = "white")))
编辑:这是一个最小的.Rmd文档,显示了该做什么。在Rstudio中打开它,然后单击“运行文档”以查看结果。
---
title: "Untitled"
output: html_document
runtime: shiny
---
<style type="text/css">
rect.background {
fill: #E6E6E6 !important;
}
</style>
```{r, echo=FALSE}
library(ggvis)
mtcars %>%
ggvis(~cyl, ~mpg) %>%
layer_bars(width = 0.8, fill:= "slateblue", strokeWidth := 0) %>%
add_axis("x", properties = axis_props(grid = list(stroke = "white"))) %>%
add_axis("y", properties = axis_props(grid = list(stroke = "white")))
```