具有DT和Shiny的R中的Composited Sparkline [英] Composited Sparkline in R with DT and Shiny
问题描述
我有一个leonawicz的参考，它可以完美地组合迷你图和DT(非常感谢他).但是，能否请您帮我做一个合成迷你图?非常感谢！.
这是示例代码
library(data.table)
library(DT)
library(sparkline)
Data <- data.table(Type = c("A", "B", "C"),
Value_1 = c("1,1,2,2", "2,2,3,3", "3,3,4,4"),
Value_2 = c("0,1,2,3", "2,3,4,5", "4,5,6,7"))
r <- c(0, 8)
line_string <- "type: 'line', lineColor: 'black', fillColor: '#ccc',
highlightLineColor: 'orange', highlightSpotColor: 'orange',
width: 80,height: 60"
cb_line = JS(paste0("function (oSettings, json) {
$('.spark:not(:has(canvas))').sparkline('html', { ",
line_string, ", chartRangeMin: ", r[1], ", chartRangeMax: ",
r[2], " }); }"), collapse = "")
cd <- list(list(targets = 1:2, render = JS("function(data, type, full){
return '<span class=spark>' + data + '</span>' }")))
d1 <- datatable(Data, rownames = FALSE, options = list(columnDefs = cd,
fnDrawCallback = cb_line))
d1$dependencies <- append(d1$dependencies,
htmlwidgets:::getDependency("sparkline"))
d1
如何将Value_1和Value_2合成为1个迷你图? 再次谢谢你！
首先，您对自己感到困难.使用功能sparkline给我们的所有JS代码可以轻松地以R的方式轻松复制(如果不添加依赖项，您实际上根本就不使用sparkline包):
数据:
您使用的数据对我来说没有多大意义.它应该以一种整齐的方式进行组织(每列一个变量，每行一个观察值).
所以我转换了它:
dfO <- data.frame(Type = c("A", "B", "C"),
Value_1 = c("1,1,2,2", "2,2,3,3", "3,3,4,4"),
Value_2 = c("0,1,2,3", "2,3,4,5", "4,5,6,7"))
library(tidyr)
library(dplyr)
df <- dfO %>%
separate_rows(Value_1, Value_2) %>%
mutate_at(vars(starts_with('Value')) ,funs(as.integer))
df
#> Type Value_1 Value_2
#> 1 A 1 0
#> 2 A 1 1
#> 3 A 2 2
#> 4 A 2 3
#> 5 B 2 2
#> 6 B 2 3
#> 7 B 3 4
#> 8 B 3 5
#> 9 C 3 4
#> 10 C 3 5
#> 11 C 4 6
#> 12 C 4 7
简单的迷你图
sparkline与dplyr尤其是summarize配合得很好.
函数spk_char将htmlwidget转换为可以在另一个小部件(在本例中为datatable)内使用的字符串.可以直接指定选项，无需使用JS.
library(dplyr)
library(sparkline)
library(DT)
df %>%
group_by(Type) %>%
summarize(l1 = spk_chr(Value_1,
lineColor = 'black',
fillColor = '#ccc',
chartRangeMin = 0,
chartRangeMax = 8,
width = 80,
height = 60,
highlightLineColor = 'orange',
highlightSpotColor = 'orange'),
l2 = spk_chr(Value_2,
lineColor = 'black',
fillColor = '#ccc',
chartRangeMin = 0,
chartRangeMax = 8,
width = 80,
height = 60,
highlightLineColor = 'orange',
highlightSpotColor = 'orange')) %>%
datatable(escape = F,
rownames = F,
options = list(fnDrawCallback = htmlwidgets::JS('function(){
HTMLWidgets.staticRender();
}'))
) %>%
spk_add_deps()
综合迷你图
也就是说，将两个sparklines结合起来比我想象的要困难得多.该解决方案非常简单，但是发现却花了一些时间.
我所做的是:
- 将数据集分成几组
- 为每个组创建迷你图
- 使用
spk_composite组合它们
- 使用
as.character(as.tags(l))转换为
DT内部的可用字符串
最后一步是spk_chr在内部完成的操作.
library(purrr)
df %>%
split(.$Type) %>%
map_df(~{
l1 <- sparkline(.x$Value_1,
lineColor = 'black',
fillColor = '#ccc',
chartRangeMin = 0,
chartRangeMax = 8,
width = 80,
height = 60,
highlightLineColor = 'orange',
highlightSpotColor = 'orange')
l2 <- sparkline(.x$Value_2,
lineColor = 'black',
fillColor = '#ccc',
chartRangeMin = 0,
chartRangeMax = 8,
width = 80,
height = 60,
highlightLineColor = 'orange',
highlightSpotColor = 'orange')
l <- spk_composite(l2,
l1)
data.frame(l1 = as.character(htmltools::as.tags(l1)),
l2 = as.character(htmltools::as.tags(l2)),
l = as.character(htmltools::as.tags(l)))
}, .id = 'Type') %>%
datatable(escape = F,
rownames = F,
options = list(fnDrawCallback = htmlwidgets::JS('function(){
HTMLWidgets.staticRender();
}'))
) %>%
spk_add_deps()
I have got a reference by leonawicz that can combine sparkline and DT perfectly(Many thanks for him). But, could you please give me a help to make a composited sparkline? Thanks a lot!.
Here is the sample code
library(data.table)
library(DT)
library(sparkline)
Data <- data.table(Type = c("A", "B", "C"),
Value_1 = c("1,1,2,2", "2,2,3,3", "3,3,4,4"),
Value_2 = c("0,1,2,3", "2,3,4,5", "4,5,6,7"))
r <- c(0, 8)
line_string <- "type: 'line', lineColor: 'black', fillColor: '#ccc',
highlightLineColor: 'orange', highlightSpotColor: 'orange',
width: 80,height: 60"
cb_line = JS(paste0("function (oSettings, json) {
$('.spark:not(:has(canvas))').sparkline('html', { ",
line_string, ", chartRangeMin: ", r[1], ", chartRangeMax: ",
r[2], " }); }"), collapse = "")
cd <- list(list(targets = 1:2, render = JS("function(data, type, full){
return '<span class=spark>' + data + '</span>' }")))
d1 <- datatable(Data, rownames = FALSE, options = list(columnDefs = cd,
fnDrawCallback = cb_line))
d1$dependencies <- append(d1$dependencies,
htmlwidgets:::getDependency("sparkline"))
d1
How could composite Value_1 and Value_2 into 1 sparkline chart? Thank you again!
First of all you are making it difficult on yourself. What you achieved with all that JS code can be easily reproduced in a more R way using the functions sparkline gives us (you are literally not using the sparkline package at all if not for adding the dependency):
Data:
The data you are using doesn't make much sense to me. It should be organized in a tidier way (one variable per column, one observation per row).
So I converted it:
dfO <- data.frame(Type = c("A", "B", "C"),
Value_1 = c("1,1,2,2", "2,2,3,3", "3,3,4,4"),
Value_2 = c("0,1,2,3", "2,3,4,5", "4,5,6,7"))
library(tidyr)
library(dplyr)
df <- dfO %>%
separate_rows(Value_1, Value_2) %>%
mutate_at(vars(starts_with('Value')) ,funs(as.integer))
df
#> Type Value_1 Value_2
#> 1 A 1 0
#> 2 A 1 1
#> 3 A 2 2
#> 4 A 2 3
#> 5 B 2 2
#> 6 B 2 3
#> 7 B 3 4
#> 8 B 3 5
#> 9 C 3 4
#> 10 C 3 5
#> 11 C 4 6
#> 12 C 4 7
Simple sparklines
sparkline plays nicely with dplyr, and in particular summarize.
The function spk_char convert the htmlwidget to a string that can be used inside another widget, in this case datatable. Options can be specified directly, no need to use JS.
library(dplyr)
library(sparkline)
library(DT)
df %>%
group_by(Type) %>%
summarize(l1 = spk_chr(Value_1,
lineColor = 'black',
fillColor = '#ccc',
chartRangeMin = 0,
chartRangeMax = 8,
width = 80,
height = 60,
highlightLineColor = 'orange',
highlightSpotColor = 'orange'),
l2 = spk_chr(Value_2,
lineColor = 'black',
fillColor = '#ccc',
chartRangeMin = 0,
chartRangeMax = 8,
width = 80,
height = 60,
highlightLineColor = 'orange',
highlightSpotColor = 'orange')) %>%
datatable(escape = F,
rownames = F,
options = list(fnDrawCallback = htmlwidgets::JS('function(){
HTMLWidgets.staticRender();
}'))
) %>%
spk_add_deps()
Composite sparklines
That said, combining the two sparklines has proved more difficult than I thought it would be. The solution is quite easy, but finding it took a bit.
What I did is:
- Split the dataset into groups
- Create the sparklines for each group
- Combine them using
spk_composite - Convert to usable string inside
DTusingas.character(as.tags(l))
The last step is what is done internally by spk_chr.
library(purrr)
df %>%
split(.$Type) %>%
map_df(~{
l1 <- sparkline(.x$Value_1,
lineColor = 'black',
fillColor = '#ccc',
chartRangeMin = 0,
chartRangeMax = 8,
width = 80,
height = 60,
highlightLineColor = 'orange',
highlightSpotColor = 'orange')
l2 <- sparkline(.x$Value_2,
lineColor = 'black',
fillColor = '#ccc',
chartRangeMin = 0,
chartRangeMax = 8,
width = 80,
height = 60,
highlightLineColor = 'orange',
highlightSpotColor = 'orange')
l <- spk_composite(l2,
l1)
data.frame(l1 = as.character(htmltools::as.tags(l1)),
l2 = as.character(htmltools::as.tags(l2)),
l = as.character(htmltools::as.tags(l)))
}, .id = 'Type') %>%
datatable(escape = F,
rownames = F,
options = list(fnDrawCallback = htmlwidgets::JS('function(){
HTMLWidgets.staticRender();
}'))
) %>%
spk_add_deps()
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