Open-source software is awesome. If I found that a piece of closed-source software was missing a feature that I wanted, well, bad luck. I probably couldn't even tell if was actually missing or if I just didn't know about it. When the source is available, maintained, and documented however, things get fun. We can identify, and perhaps fill gaps.

I've thought for a couple of projects which had bar-graphs that it would be neat to have the categories labelled by an icon or a picture. Say, the logo for a company or an illustrative example. Sure, you could fire up GIMP/Inkscape and manually insert them over the top of the text labels (each and every time you re-produce the graph... no thanks) but that's not how I operate.

There are probably very few cases for which this is technically a good idea (trying to be a featured author on JunkCharts might very well be one of those reasons). Nonetheless, there are at least a couple of requests for this floating around on stackoverflow; here and here for example. I struggled to find any satisfactory solutions that were in current working order (though perhaps my Google-fu has failed me).

The second link there has a working example, but the big update to ggplot2 breaks that pretty strongly; opts was deprecated and now element_text() has a gatekeeper validation routine that prevents any such messing around. The first link however takes a different route. I couldn't get that one to work either, but in any case the answer is a year out of date (updates in ggplot2can easily have broken the gTree relations), not particularly flexible, and relies on saving intermittent image files for PostScriptTrace to read back in which I'm not a fan of (and couldn't get to work anyway).

I decided that I perhaps had enough ammunition to hack something together myself (emphasis on hack), and sure enough it seems to have worked (for a limited definition of "worked" with no attached or implied guarantees whatsoever).

GDP per capita with flags for x-axis labels. This was harder to make than it seemed, but I've since added a little more flexibility to it.

The way to go about making your own is as follows;

    1. Stop and carefully re-evaluate the choices that you've made to bring you to this decision. Are you sure? Okay...
    2. Save the images (in the correct factor order) into a list (e.g. pics).
    3. Build your bar graph with categorical x-axis as per normal, using theme() to remove the labels. Save as an object (e.g. g).
    4. Source the function from this gist (at your own risk... copy and paste if you prefer):
devtools::source_gist("1d1bdb00a7b3910d62bf3eec8a77b4a7")
  #' Replace categorical x-axis labels with images
  #'
  #' Pipe a ggplot2 graph (with categorical x-axis) into this function with the argument of a list of
  #' pictures (e.g. loaded via readImage) and it builds a new grob with the x-axis categories
  #' now labelled by the images. Solves a problem that you perhaps shouldn't have.
  #'
  #' @author J. Carroll, \email{jono@@jcarroll.com.au}
  #' @references \url{http://stackoverflow.com/questions/29939447/icons-as-x-axis-labels-in-r-ggplot2}
  #'
  #' @param g ggplot graph with categorical x axis
  #' @param pics ordered list of pictures to place along x-axis
  #'
  #' @return NULL (called for the side-effect of producing a new grob with images for x-axis labels)
  #'
  #' @import grid
  #' @import ggplot2
  #'
  #' @export
  #'
  #' @example
  #' \dontrun{ggplot(data, aes(x=factor(x),y=y)) + geom_point() %>% add_images_as_xlabels(pics)}
  #'
  add_images_as_xlabels <- function(g, pics) {
   
  ## ensure that the input is a ggplot
  if(!inherits(g, "ggplot")) stop("Requires a valid ggplot to attach images to.")
   
  ## extract the components of the ggplot
  gb <- ggplot_build(gg)
  xpos <- gb$panel$ranges[[1]]$x.major
  yrng <- gb$panel$ranges[[1]]$y.range
   
  ## ensure that the number of pictures to use for labels
  ## matches the number of x categories
  if(length(xpos) != length(pics)) stop("Detected a different number of pictures to x categories")
   
  ## create a new grob of the images aligned to the x-axis
  ## at the categorical x positions
  my_g <- do.call("grobTree", Map(rasterGrob, pics, x=xpos, y=0))
   
  ## annotate the original ggplot with the new grob
  gg <- gg + annotation_custom(my_g,
  xmin = -Inf,
  xmax = Inf,
  ymax = yrng[1] + 0.25*(yrng[2]-yrng[1])/npoints,
  ymin = yrng[1] - 0.50*(yrng[2]-yrng[1])/npoints)
   
  ## turn off clipping to allow plotting outside of the plot area
  gg2 <- ggplotGrob(gg)
  gg2$layout$clip[gg2$layout$name=="panel"] <- "off"
   
  ## produce the final, combined grob
  grid.newpage()
  grid.draw(gg2)
   
  return(invisible(NULL))
   
  }
 
    1. Call (or pipe your ggplot object to) the function:
g %>% add_images_as_xlabels(pics)
 
## or
 
add_images_as_xlabels(g, pics)
  1. Your image will be re-drawn with your pictures labelling the categories.

Here's an example of the code used to generate the GDP per capita image, featuring some fairly brief (for what it does) rvest scraping (to reiterate; I don't want to have to do any of this by hand, so let's code it up!).

  library(rvest)
   
  ## GDP per capita, top 10 countries
  url <- "https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)_per_capita"
  html <- read_html(url)
  gdppc <- html_table(html_nodes(html, "table")[3])[[1]][1:10,]
   
  ## clean up; remove non-ASCII and perform type conversions
  gdppc$Country <- gsub("Â ", "", gdppc$Country)
  gdppc$Rank <- iconv(gdppc$Rank, "latin1", "ASCII", sub="")
  gdppc$Country <- iconv(gdppc$Country, "latin1", "ASCII", sub="")
  gdppc$`US$` <- as.integer(sub(",", "", gdppc$`US$`))
   
  ## flag images (yes, this processing could be done neater, I'm sure)
  ## get the 200px versions
  flags_img <- html_nodes(html_nodes(html, "table")[3][[1]], "img")[1:10]
  flags_url <- paste0('http://', sub('[0-9]*px', '200px', sub('\\".*$', '', sub('^.*src=\\"//', '', flags_img))))
  flags_name <- sub('.*(Flag_of)', '\\1', flags_url)
   
  if(!dir.exists("flags")) dir.create("flags")
  for(flag in seq_along(flags_url)) {
  switch(Sys.info()[['sysname']],
  Windows= {download.file(flags_url[flag], destfile=file.path("flags", paste0(flag,"_", flags_name[flag])), method="auto", mode="wb")},
  Linux = {download.file(flags_url[flag], destfile=file.path("flags", paste0(flag,"_", flags_name[flag])))},
  Darwin = {print("Not tested on Mac. Use one of the above and find out?")})
  }
   
  library(EBImage) ## readImage
  library(dplyr) ## %>%
  library(ggplot2) ## devtools::install_github("hadley/ggplot2)
  library(grid) ## rasterGrob
  library(ggthemes) ## theme_minimal
  library(scales) ## comma
   
  ## create a dummy dataset
  npoints <- length(flags_name)
  y <- gdppc$`US$`
  x <- seq(npoints)
  dat <- data.frame(x=factor(x), y=y)
   
  ## load the images from filenames
  ## one day I'll remember to make these sorted on save
  pics <- vector(mode="list", length=npoints)
  image.file <- dir("flags", full.names=TRUE)
  image.file <- image.file[order(as.integer(sub("_.*", "", sub("flags/", "", image.file))))]
   
  ## save the images into a list
  for(i in 1:npoints) {
  pics[[i]] <- EBImage::readImage(image.file[i])
  }
   
  ## create the graph, as per normal
  ## NB: #85bb65 is the color of money in the USA apparently.
  gg <- ggplot(dat, aes(x=x, y=y/1e3L, group=1))
  gg <- gg + geom_bar(col="black", fill="#85bb65", stat="identity")
  gg <- gg + scale_x_discrete()
  gg <- gg + theme_minimal()
  gg <- gg + theme(plot.margin = unit(c(0.5,0.5,5,0.5), "lines"),
  axis.text.x = element_blank(),
  axis.text.y = element_text(size=14))
  gg <- gg + scale_fill_discrete(guide=FALSE)
  gg <- gg + theme(plot.background = element_rect(fill="grey90"))
  gg <- gg + labs(title="GDP per Capita", subtitle=paste0("Top 10 countries\n(", url, ")"), x="", y="$US/1000")
  gg
   
  ## insert imags (pics) as x-axis labels
  ## well, at least appear to do so
  gg %>% add_images_as_xlabels(pics)
view rawGDP_per_capita.R hosted with  by GitHub
 

At least a few caveats surround what I did manage to get working, including but not limited to:

  • I'm not sure how to put the x-axis title back in at the right position without padding it with a lot of linebreaks ("\n\n\n\nX-AXIS TITLE").
  • I'm not sure how to move the caption line from labs() (assuming you're using the development version of ggplot2 on GitHub with @hrbrmstr's excellent annotation additions) so it potentially gets drawn over.
  • The spacing below the graph is currently arbitrarily set to a few lines more than necessary, but it's a compromise in having an arbitrary number of images loaded at their correct sizes.
  • Similarly, I've just expanded the plot range of the original graph by a seemingly okay amount which has worked for the few examples I've tried.
  • Using a graph like this places the onus of domain knowledge onto the reader; if you don't know what those flags refer to then this graph is less useful than one with the countries labelled with words. Prettier though.

I've no doubt that there must be a better way to do this, but it's beyond my understanding of how ggproto works, and I can't seem to bypass element_text's requirements with what I do know. If you would like to help develop this into something more robust then I'm most interested. Given that it's a single function I wasn't going to create a package just for this, but I'm willing to help incorporate it into someone's existing package. Hit the comments or ping me on Twitter (@carroll_jono)!

转自:http://jcarroll.com.au/2016/06/02/images-as-x-axis-labels/

Images as x-axis labels的更多相关文章

  1. Axis.Labels.CustomSize

    tChart1.Axes.Bottom.Labels.CustomSize = ; //Changes spacing occupied by the axis labels between the ...

  2. 3D Slicer Hide 3D Cube and Axis Labels Programmatically 使用代码隐藏三维视图中的方框和坐标轴标签

    在3D Slicer中,我们如果想在自己写的插件中来修改三维视图中的默认设置的话,那么首先就需要获得三维视图的结点,其类型为vtkMRMLViewNode,获得了这个结点后,我们就可以用代码来修改一系 ...

  3. TeeChart中Axis的CalcIncrement属性

    private void Init() { tChart = new TChart(); panel1.Controls.Add(tChart); tChart.Aspect.View3D = fal ...

  4. 应用matplotlib绘制地图

    #!/usr/bin/env python # -*- coding: utf-8 -*- from math import sqrt import shapefile from matplotlib ...

  5. 数字格式化函数:Highcharts.numberFormat()

    (转)数字格式化函数:Highcharts.numberFormat() 一.函数说明 该函数用于图表中数值的格式化,常见用途有数值精度控制.小数点符.千位符显示控制等.   二.函数使用   1.函 ...

  6. Highcharts X轴名称太长,如何设置下面这种样式

      Highcharts所有的图表除了饼图都有X轴和Y轴,默认情况下,x轴显示在图表的底部,y轴显示在左侧(多个y轴时可以是显示在左右两侧),通过chart.inverted = true 可以让x, ...

  7. R绘图基础

    一,布局 R绘图所占的区域,被分成两大部分,一是外围边距,一是绘图区域. 外围边距可使用par()函数中的oma来进行设置.比如oma=c(4,3,2,1),就是指外围边距分别为下边距:4行,左边距3 ...

  8. Python图表绘制:matplotlib绘图库入门

    matplotlib 是Python最著名的绘图库,它提供了一整套和matlab相似的命令API,十分适合交互式地行制图.而且也可以方便地将它作为绘图控件,嵌入GUI应用程序中. 它的文档相当完备,并 ...

  9. (转)数字格式化函数:Highcharts.numberFormat()

    一.函数说明 该函数用于图表中数值的格式化,常见用途有数值精度控制.小数点符.千位符显示控制等.   二.函数使用   1.函数构造及参数 Highcharts.numberFormat (Numbe ...

  10. 数据可视化(5)--jqplot经典实例

    本来想把实例也写到上篇博客里,最后发现太长了,拆成两篇博客了. 实例来源于官方文档:http://www.jqplot.com/tests/ 这篇博客主要是翻译了官方文档关于经典实例的解说,并在相应代 ...

随机推荐

  1. 浅谈css中单位px和em,rem的区别-转载

    px是你屏幕设备物理上能显示出的最小的一个点,这个点不是固定宽度的,不同设备上点的长宽.比例有可能会不同.假设:你现在用的显示器上1px宽=1毫米,但我用的显示器1px宽=两毫米,那么你定义一个div ...

  2. css中auto的用法

    —什么是auto? +auto是自适应的意思,auto是很多尺寸值的默认值,也就是由浏览器自动计算. +块级元素中margin.border.padding以及content宽度之和构成父元素widt ...

  3. javascript核心概念——new

    如果完全没有编程经验的朋友看到这个词会想到什么? 上过幼儿园的都知道new表示 "新的" 的意思. var a = new Date() 按照字面的意思表示什么? 把一个新的dat ...

  4. Python多层目录模块调用

    一. 引用模块在 父+级目录中: 1. 将导入模块所在目录(../model/模块)添加到系统环境变量path下,可添加多个 import syssys.path.append("../mo ...

  5. 《Algorithms Unlocked》读书笔记2——二分查找和排序算法

    <Algorithms Unlocked>是 <算法导论>的合著者之一 Thomas H. Cormen 写的一本算法基础,算是啃CLRS前的开胃菜和辅助教材.如果CLRS的厚 ...

  6. USACO Section 1.1-1 Your Ride Is Here

    USACO 1.1-1 Your Ride Is Here 你的飞碟在这儿 众所周知,在每一个彗星后都有一只UFO.这些UFO时常来收集地球上的忠诚支持者.不幸的是,他们的飞碟每次出行都只能带上一组支 ...

  7. MetaProducts Offline Explorer使用简易教程

    MetaProducts Offline Explorer使用简易教程 by windtrace  20170419 最近想下载一个网站上的内容打包成chm文件,以便离线浏览,webzip太长时间不更 ...

  8. ionic打包项目,运行时报错A problem occurred configuring root project 'android'。。。

    运行报错的原因是sdk没有下载完整 解决办法: 1,打开sdk manage.分别下载android support repository.Google play services.google re ...

  9. C++学习笔记1(扩充:C++中的格式控制)

    前一章,我们了解了再C++中的标准的输入输出问题,那么肯能就有人会问了再C语言中我们可以灵活的控制输出和显示,那么再再C++中可以实现吗?我的回答是当然可以的,只不过再C++中的控制可能相比较而言要比 ...

  10. spring 动态创建数据源

    项目需求如下,公司对外提供服务,公司本身有个主库,另外公司会为每个新客户创建一个数据库,客户的数据库地址,用户名,密码,都保存在主数据库中.由于不断有新的客户加入,所以要求,项目根据主数据库中的信息, ...