Code gists to the rescue #3

helgasoft · 2021-11-22T03:37:21Z

Several programming questions have been addressed already in our Code Gists.
Gists are searchable by keyword. Example: to search for scatter in all gists - do this.

Here is the complete list of sample code locations:

official ec.examples
Shiny code is in eshiny.R, run with demo(eshiny)
website gallery and tutorials
demos on RPubs
searchable gists
answers to Github issues
command examples in Help, like ?ec.init
code in Github tests

The text was updated successfully, but these errors were encountered:

helgasoft · 2022-08-21T20:10:47Z

endLabel formatting, inquiry by @Tom-Jenkins

tmp <- read.csv('https://github.com/JohnCoene/echarts4r/files/9375371/life_continent.txt', sep='\t')
tmp |> mutate(life_expectancy= round(life_expectancy,2), year= as.factor(year)) |>
	select(year, life_expectancy, country) |>   # order x,y,grp - will be redundant in echarty 1.4.7
	group_by(country) |> 
ec.init(
	ctype='line', 
	yAxis= list(scale= TRUE), 
	grid= list(right= '28%'),
	animation= list(duration= 5000)) |> 
ec.upd({
	series <- lapply(series, function(ss) {
		ss$showSymbol <- FALSE
		ss$emphasis <- list(disable=FALSE, lineStyle= list(width= 3), focus= "self")
		ss$endLabel <- list(show= TRUE, valueAnimation= TRUE, color= 'inherit',
				offset= c(-50,11), 
				formatter= ec.clmn('%@ %L@',3,2))
	ss })
})

if you like this solution, please consider granting a Github star ⭐ to echarty.

helgasoft · 2022-08-24T23:14:47Z

Layout with two pie charts, inquiry by @DavZim.

library(dplyr)
df <- tibble(
	name = rep(c("v1", "v2", "v3"), 2), # pie native 'axes' are name/value
	value = c(20, 40, 40, 50, 30, 20),
	group = rep(c("A", "B"), each = 3)  # echarty currently requires group column to be last
)

library(echarty)   # v.1.4.7.01+
p <- lapply(df |> group_by(group) |> group_split(), function(x) { 
	ec.init(preset= FALSE, height= 250,
			  title= list(text= unique(x$group)), 
			  series= list(list(type= 'pie', data= ec.data(x, 'names'))),
			  legend= list(show=TRUE))
})
ec.util(p, cmd='layout', cols=2)

# try also new tabset command
htmltools::browsable(
	ec.util(cmd='tabset', tab1= p[[1]], tab2= p[[2]])
)

df2 <- tibble(
	group = rep(c("A", "B"), each = 100),
	time = rep(1:100, 2)
) %>% mutate(value = time + rnorm(100) + ifelse(group == "A", 10, 0)) %>% 
	select(time,value,group)

library(echarty)
lapply(df2 |> group_by(group) |> group_split(), function(gd) { 
	tmp <- lm(value ~ time, gd)
	ec.init( 
		height= 300, title= list(text= unique(gd$group)), 
		xAxis= list(show=TRUE), yAxis=list(show=TRUE),
		series= list(
			list(type= 'scatter', data= ec.data(gd[,1:2]), symbolSize=3, name='data'),
			list(type='line', data= ec.data(data.frame(gd$time, tmp$fitted.values)),
				  showSymbol= FALSE, lineStyle= list(width=1, color='red'), name='lm')
		),
		legend= list(show=TRUE))
}) |>
ec.util(cmd='layout', cols= 2)

if you like this solution, please consider granting a Github star ⭐ to echarty.

helgasoft · 2022-09-14T17:44:02Z

Answer question by @kesselhwvan about duplicating a ggplot chart

#  set.seed(?)
data = tibble(time = factor(sort(rep(c(4,8,24), 30)), levels = c(4,8,24)),
	dose = factor(rep(c(1,2,3), 30), levels = c(1,2,3)),
	id = rep(sort(rep(LETTERS[1:10], 3)),3),
	y = rnorm(n = 90, mean = 5, sd = 3))

# This is the plot i am aiming to recreate:
# ggplot(data = data, mapping = aes(x = time, y = y, group = id)) + geom_point() +
#      geom_line() + facet_wrap(~dose)

remotes::install_github('helgasoft/echarty')      # get latest 1.4.7.02
library(echarty)

df <- data |> select(time,y,id,dose)	# default order for X,Y,group,etc 
lapply(unique(df$dose), function(i) 
	df |> filter(dose==i) |> group_by(id) |> 
	ec.init(ctype='line', title= list(text= i), legend= list(show=FALSE)
               ,yAxis= list(min= floor(min(df$y)), max= ceiling(max(df$y)))
               ,grid= list(containLabel= TRUE)) 
) |>
ec.util(cmd='layout', cols=3)

if you like this solution, please consider granting a Github star ⭐ to echarty.

helgasoft · 2022-10-10T06:07:51Z

@XiangyunHuang, hope that's what you are looking for.
Parameter visualMap.dimension works with ECharts dataset, which is set by default in echarty.

library(echarty)
# enhance symbol size related to magnitude
quakes |> mutate(mage= ifelse(mag<5, 4, ifelse(mag<6, 10, 15))) |> 
ec.init(load='3D',
  xAxis3D= list(name= "Lat", scale=TRUE),
  yAxis3D= list(name = "Long", scale=TRUE),
  zAxis3D= list(name = "Depth"),
  series= list(list(type= 'scatter3D',
    encode= list(x= 'lat', y= 'long', z= 'depth'),
    symbolSize = ec.clmn(6),  # = mage
    name = "Fiji"
  )),
  visualMap= list(
    type = "continuous",
    # inRange = list(color = c('#4B0055', '#009B95', '#FDE333')),
    inRange = list(color = c('green', 'yellow', 'red')),
    dimension = 3, # third dimension x = 0, y = 1, z = 2, mag = 3, station = 4
    max= max(quakes$mag), min= min(quakes$mag), 
    text= c(paste('mag\n',max(quakes$mag)), min(quakes$mag)),
    top = 20, calculable= TRUE, precision= 1,
    textStyle= list(color= '#bbb')
  )
) |> ec.theme('dark-mushroom')

helgasoft · 2022-10-26T18:42:59Z

Numbers locale-based formatting, asked by @oobd
Done with ec.clmn() in echarty. Format %L@ stands for 'localized'.

library(dplyr); library(echarty)
iris %>%
  mutate(Petal.Length = Petal.Length * 1000) %>% 
  group_by(Species) %>% 
  summarise(Petal.Length = sum(Petal.Length)) %>% 
  ec.init(
    grid= list(containLabel= TRUE),
    series= list(list( 
      type= 'bar',
      encode= list(x= 'Petal.Length', y= 'Species'),
      label= list(show= TRUE, position= 'inside', fontSize= 10, offset= c(0, 0.5),
                  formatter= ec.clmn('%L@', 'Petal.Length'))
    ))
  )

helgasoft · 2022-11-22T19:57:57Z

Simple heatmap of weekly hours, inquiry by @avenn98

set.seed(2022)
df <- data.frame(day_of_week= sample(c('Mon','Tue','Wed','Thu','Fri','Sat','Sun'),100, replace=TRUE), 
		hour_of_day= sample(5:23, 100, replace=TRUE), 
		jobs= sample(1:100, 100)) |> 
	dplyr::distinct(hour_of_day, day_of_week, .keep_all= TRUE)
df |> echarty::ec.init(
	title= list(text= "Heatmap of Successful API Requests by Day and Hour"),
	series= list(list(type= 'heatmap')),
	xAxis= list(type= 'category', data= c('Mon','Tue','Wed','Thu','Fri','Sat','Sun')),
	yAxis= list(min= min(df$hour_of_day)-1, name= 'hours', interval= 1),
	visualMap= list(calculable= TRUE, max= 100, 
		orient= 'horizontal', bottom= 'bottom', left='middle', align= 'right', 
		inRange= list(color= c('yellow','red'))),
	tooltip= list(trigger= "item")
)

if you like this solution, please consider granting a Github star ⭐ to echarty.

avenn98 · 2022-11-23T15:06:09Z

That worked perfectly, thank you so much!

helgasoft · 2022-12-11T08:28:20Z

Stacked bar chart with factor categories + colors, sample by @mmfc

library(dplyr)
ccv <- "project_id	sum	count	status
100	35	20	Accepted
100	35	14	Proposal
100	35	1	QA
107	33	8	Accepted
107	33	9	In Progress
107	33	12	Proposal
107	33	4	QA
83	20	10	Accepted
83	20	3	In Progress
83	20	7	Proposal
11	18	6	Accepted
11	18	3	In Progress
11	18	5	Proposal
11	18	4	QA
91	17	11	Accepted
91	17	4	In Progress
91	17	2	Proposal
8	15	7	Accepted
8	15	3	Аbandoned
8	15	1	Blocked"
df <- read.csv(text=ccv, sep='\t', header=T) 
df$status <- factor(df$status, levels= c('Accepted','Proposal','QA','In Progress','Blocked','Аbandoned','Reference'))

library(echarty)
df |> mutate(project_id= as.character(project_id)) |> arrange(desc(sum)) |> 
  relocate(sum, .after=last_col()) |> group_by(status) |> 
ec.init(ctype= 'bar', 
  series.param= list(stack= "stak"), tooltip= list(show=T),
  xAxis= list(type= 'category', 
              data= unique(unname(unlist(df$project_id)))),
  # 'status' colors in same (factor) order
  color= c("#FEF2C0","#BFE5BF","#D4C5F9","#a10b0b","#000000","#7F8C8D","green")
) |> ec.theme('dark-mushroom')

helgasoft · 2022-12-21T03:46:14Z

A solution for boxplot + data chart using helper function echarty::ec.data(format='boxplot',...)
for @lhabegger and @varunrd

library(echarty)      # use v.1.5.1+
# prepare data
ds <- iris |> dplyr::relocate(Species) |>
	ec.data(format= 'boxplot', jitter= 0.1, layout= 'v', 
	        symbolSize= 6, tooltip= list(formatter= ec.clmn('%@',2)))
# display
ec.init(
  dataset= ds$dataset, series= ds$series,xAxis= ds$xAxis, yAxis= ds$yAxis,
  legend= list(show= T), tooltip= list(show= T)
)

if you like this solution, please consider granting a Github star ⭐ to echarty.

helgasoft · 2023-01-26T20:56:11Z

Make data.tree acme dataset show as sunburst chart, for @GillesSanMartin.
See also various hierarchical structures for echarty explained.

library(data.tree)
tmp <- acme
tmp$Do(function(x) x$value <- x$cost)  # add 'value' for sunburst
lst <- tmp |> ToListExplicit(unname = TRUE)

library(echarty)
p1 <- ec.init(
	series= list(list(
           # data=list(lst) is ok too, but children are not colored
           #type= 'treemap', data= lst$children) 
            type= 'sunburst', data= lst$children, 
               radius= list(0, '90%'), label= list(rotate='radial')))
)
p2 <- ec.init(width=300, series= list(list(type= 'tree', data= list(lst))))
ec.util(list(p1,p2), cmd='layout', cols=2)

helgasoft · 2023-09-20T17:13:36Z

New in version 1.6.0 - save complete chart to file, show local or remote charts.
@rdatasculptor will like it

remotes::install_github('helgasoft/echarty')    # get latest v.1.6.0
library(echarty)

# build a chart with custom Javascript handlers
js = "chart.getZr().on('contextmenu', x => {chart.setOption({title:{text:'right-clicked'}}) })"
p <- cars |> ec.init(js= js, dataZoom= list(type='inside'))
p$x$on = list(
    list(event= 'datazoom', 
         handler= ec.clmn("function() {this.setOption({title:{text:'zoomed'}});}") )
)

# save chart to local file
p |> ec.inspect(target='full', file='c:/temp/tcar.txt')
# file could now be uploaded to net

# read local file and show chart
con <- file('c:/temp/tcar.txt','rb')
ec.fromJson(con); close(con)

# show a remote chart
echarty::ec.fromJson('https://helgasoft.github.io/echarty/test/pfull.json')

helgasoft · 2023-12-15T19:52:03Z

@pizifan, an complex example indeed from ECharts.
But echarty can handle it. Currently tl.series supports a single serie, but more can be added thru ec.upd().
Notice that list attributes are straight from ECharts API.

remotes::install_github('helgasoft/echarty')  # get latest!
library(echarty)

tmp <- as.data.frame(jsonlite::fromJSON('https://echarts.apache.org/examples/data/asset/data/life-expectancy-table.json'))
colnames(tmp) <- tmp[1,]
df <- tmp[-1,]
df <- df |> mutate(across(.cols= -c(Country), as.numeric)) |> 
  filter(Year %in% c(1985,2000,2015), Country %in% c('Canada','France','Turkey'))
clr <- ec.clmn("(p) => { return p.dataIndex==0 ? 'violet' : p.dataIndex==1 ? 'orange' : 'brown' }")

df |> group_by(Year) |> 
ec.init(
  yAxis= list(list(name='income', max=45000), 
              list(name='life', max=85)),
  tl.series= list(type='bar', name='income',
                  encode= list(x='Country', y='Income')),
  tooltip= list(show=T), 
  legend= list(data= c('income','life','pop.'))
) |> 
ec.upd({
  options <- lapply(options, \(oo) {
    dix <- oo$series[[1]]$datasetIndex  # from tl.series (bar)
    oo$series <- append(oo$series, 
      list(
        list(type='bar', name='life', yAxisIndex=1, 
             datasetIndex= dix,
             encode= list(x='Country', y='Life Expectancy')),
        list(type='pie', name='pop.', itemStyle= list(color=clr),
             datasetIndex= dix,
             encode= list(value='Population', itemName='Country'), 
             center= c('75%', '25%'), radius= '20%', 
             label= list(show=T), labelLine= list(length=5, length2=0))
    ))
    oo
  })
})

helgasoft · 2023-12-26T20:06:49Z

some less used chart types, translated to echarty from official source, for @msgoussi

waterfall

# original https://echarts.apache.org/examples/en/editor.html?c=bar-waterfall2
xdat <- paste('Nov',1:11)
jscode <- htmlwidgets::JS("function(params) {
  let tar;
  if (params[1] && params[1].value !== '-') {
    tar = params[1];
  } else {
    tar = params[2];
  }
  return tar && tar.name + '<br/>' + tar.seriesName + ' : ' + tar.value;
}")

ec.init(
  title=list(text='Accumulated Waterfall Chart'),
  legend= list(show=T),
  grid= list(left='3%',right='4%',bottom='3%',containLabel=TRUE),
  xAxis=list(type='category', data=xdat),
  yAxis=list(type='value'),
  series=list(
    list(type='bar',stack='Total',silent=TRUE,  #Placeholder
         itemStyle=list(borderColor='transparent',color='transparent'),
         emphasis=list(itemStyle=list(borderColor='transparent',color='transparent')),
         data=list(0, 900, 1245, 1530, 1376, 1376, 1511, 1689, 1856, 1495, 1292)),
    list(name='Income',type='bar',stack='Total',label=list(show=TRUE,position='top'),
         data=list(900, 345, 393, '-', '-', 135, 178, 286, '-', '-', '-')),
    list(name='Expenses',type='bar',stack='Total',label=list(show=TRUE,position='bottom'),
         data=list('-', '-', '-', 108, 154, '-', '-', '-', 119, 361, 203))),
  tooltip=list(trigger='axis', axisPointer=list(type='shadow'), 
               formatter= jscode )
)

bar race

# original https://echarts.apache.org/examples/en/editor.html?c=bar-race
data <- round(runif(5,1, 200))
js <- paste0("
const data=[",paste(data,collapse=","),"];
function run() {
  for (var i = 0; i < data.length; ++i) {
    if (Math.random() > 0.9) {
      data[i] += Math.round(Math.random() * 2000);
    } else {
      data[i] += Math.round(Math.random() * 200);
    }
  }
  chart.setOption({ series: [{type: 'bar', data}] });
}
setTimeout(function () { run(); }, 0);
setInterval(function () { run();}, 3000);"
)

ec.init( js= js,
  xAxis = list(max = "dataMax"), 
  yAxis = list(type = "category", data = list("A","B","C","D","E"), inverse = TRUE, 
               animationDuration = 300, animationDurationUpdate = 300), 
  series = list(
    list(realtimeSort= TRUE, type= "bar", 
         data= data, colorBy= 'data',
         label= list(show= TRUE, position= "right", valueAnimation= TRUE))), 
  animationDuration= 0, animationDurationUpdate= 2000, 
  animationEasing= "linear", animationEasingUpdate= "linear"
)

helgasoft · 2024-01-24T05:24:50Z

New extras function 💲 to build a two-level axis, with responsive auto-resize.
Currently coded in Javascript, but usable with ec.init. R-code version planned also.
Often used to present category groups, see apache/echarts#18923.

helgasoft pinned this issue Nov 22, 2021

rdatasculptor mentioned this issue Sep 20, 2023

How to put javascript function in json rendered by e_inspect()? JohnCoene/echarts4r#560

Closed

helgasoft mentioned this issue Dec 19, 2023

Features question #32

Closed

MrMisc mentioned this issue Dec 29, 2023

Combining pie chart with bar chart #34

Closed

helgasoft mentioned this issue Jun 12, 2024

Grouped Categories apache/echarts#18923

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Code gists to the rescue #3

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Code gists to the rescue #3

Code gists to the rescue #3

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waterfall

bar race

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