我想要Ggvis中的ggplot2外观和感觉。有没有办法在ggvis中实现这一点?
我从ggvis那里得到了这个:
注意:
1)不喜欢白色背景(最好是ggplot2的灰色背景
2)如您所见,条形图上有一条黑线。如何摆脱它?
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))
发布于 2015-02-21 02:51:35
如果您的输出是一个闪亮的应用程序或闪亮的文档,您可以使用一些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。还要注意,它不会在Rstudio查看器中正确显示。在创建ggvis之前,将此代码添加到文档中的某个位置:
<style type="text/css">
rect.background {
fill: #E6E6E6 !important;
}
</style>
然后,要获得白色网格线并移除条形图边框,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,展示了要做什么。在Rstudio中打开它,然后单击"Run document“查看结果。
---
title: "Untitled"
output: html_document
runtime: shiny
---
<style type="text/css">
rect.background {
fill: #E6E6E6 !important;
}
</style>
```{r, echo=FALSE}
库(Ggvis)
mtcars %>%
ggvis(~cyl,~mpg) %>%
Layer_bars(宽度= 0.8,fill:=“板蓝”,strokeWidth := 0) %>%
add_axis("x",properties = axis_props(grid =列表( %>% =“白色”)
add_axis("y",属性=axis_props(网格=列表(笔划=“白色”)
https://stackoverflow.com/questions/28523003
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