根据其大小（即数值）对ggplot2排序条形图 [英] Ordering bar plots with ggplot2 according to their size, i.e. numerical value

问题描述

这个问题询问根据未整理的表格订购条形图。我有一个稍微不同的情况。以下是我原始数据的一部分：

 实验，pvs_id，src，hrc，mqs，mcs，dmqs，imcs 
 dna-wm，0,7,9,4.454545454545454,1.4545454545454546,1.4545454545454541,4.3939393939393945 
 dna-wm，1,7,4,2.909090909090909,1.8181818181818181,0.09090909090909083,3.9090909090909087 
 dna-wm，2,7， 1,4.818181818181818,1.4545454545454546,1.8181818181818183,4.3939393939393945 
 dna-wm，3,7,8,3.4545454545454546,1.5454545454545454,0.4545454545454546,4.272727272727273 
 dna-wm，4,7,10,3.8181818181818183,1.9090909090909092,0.8181818181818183， 3.7878787878787876 
 dna-wm，5,7,7,3.909090909090909,1.9090909090909092,0.9090909090909092,3.7878787878787876 
 dna-wm，6,7,0,4.909090909090909,1.3636363636363635,1.9090909090909092,4.515151515151516 
 dna-wm ，7,7,3,3.909090909090909,1.7272727272727273,0.9090909090909092,4.030303030303029 
 dna-wm，8,7,11,3.6363636363636362,1.5454545454545454,0.6363636363636362,4.272727272727273 
  

我只需要几个var其中的 c $ c> mqs 和 imcs ，按照它们的 pvs_id

  m = melt（t，id.var =pvs_id，measure。 var = c（mqs，imcs））
  

我可以将其作为条形图在那里你可以看到 MQS 和 IMCS 之间的相关性。



  ggplot （m，aes（x = pvs_id，y = value））
 + geom_bar（aes（fill = variable），position =dodge，stat =identity）
  

但是，我希望结果栏由 MQS 值按从左到右的顺序排序。 IMCS 值应当与那些排序。

我该如何实现这一点？一般来说，给定任何熔化的数据框 - 这对于ggplot2中的图形显示非常有用，而今天我第一次偶然发现它 - 如何指定一个变量的顺序？

解决方案

这一切都在制作

pvs_id

  dat $ pvs_id<  -  factor（dat $ pvs_id，levels = dat [order（-dat $ mqs ），2]）
 
m = melt（dat，id.var =pvs_id，measure.var = c（mqs，imcs））
 
 ggplot （m，aes（x = pvs_id，y = value））+ 
 geom_bar（aes（fill = variable），position =dodge，stat =identity）
  
 
 
 
产生以下图表： 
 
 
  
 
 编辑： 
   c> pvs_id 是数字，它以有序方式处理。如果你有一个因素，没有订单。所以即使你有数字标签 pvs_id 实际上是一个因素（标称值）。就 dat [order（-dat $ mqs），2] 而言，具有负号的顺序函数将数据帧从变量 MQS 。但是您对 pvs_id 变量的顺序感兴趣，因此您需要索引第二列的该列。如果你把它分开，你会看到它给你：
 > dat [order（-dat $ mqs），2] 
 [1] 6 2 0 5 7 4 8 3 1 
  
现在你将它提供给 factor 的 levels 参数，想要它。
 
This question asks about ordering a bar graph according to an unsummarized table. I have a slightly different situation. Here's part of my original data:
experiment,pvs_id,src,hrc,mqs,mcs,dmqs,imcs
dna-wm,0,7,9,4.454545454545454,1.4545454545454546,1.4545454545454541,4.3939393939393945
dna-wm,1,7,4,2.909090909090909,1.8181818181818181,0.09090909090909083,3.9090909090909087
dna-wm,2,7,1,4.818181818181818,1.4545454545454546,1.8181818181818183,4.3939393939393945
dna-wm,3,7,8,3.4545454545454546,1.5454545454545454,0.4545454545454546,4.272727272727273
dna-wm,4,7,10,3.8181818181818183,1.9090909090909092,0.8181818181818183,3.7878787878787876
dna-wm,5,7,7,3.909090909090909,1.9090909090909092,0.9090909090909092,3.7878787878787876
dna-wm,6,7,0,4.909090909090909,1.3636363636363635,1.9090909090909092,4.515151515151516
dna-wm,7,7,3,3.909090909090909,1.7272727272727273,0.9090909090909092,4.030303030303029
dna-wm,8,7,11,3.6363636363636362,1.5454545454545454,0.6363636363636362,4.272727272727273
I only need a few variables from this, namely mqs and imcs, grouped by their pvs_id, so I create a new table:
m = melt(t, id.var="pvs_id", measure.var=c("mqs","imcs"))
I can plot this as a bar graph where one can see the correlation between MQS and IMCS.
ggplot(m, aes(x=pvs_id, y=value)) 
+ geom_bar(aes(fill=variable), position="dodge", stat="identity")


However, I'd like the resulting bars to be ordered by the MQS value, from left to right, in decreasing order. The IMCS values should be ordered with those, of course.

How can I accomplish that? Generally, given any molten dataframe — which seems useful for graphing in ggplot2 and today's the first time I've stumbled over it — how do I specify the order for one variable?
解决方案
It's all in making 

pvs_id a factor and supplying the appropriate levels to it:
dat$pvs_id <- factor(dat$pvs_id, levels = dat[order(-dat$mqs), 2])

m = melt(dat, id.var="pvs_id", measure.var=c("mqs","imcs"))

ggplot(m, aes(x=pvs_id, y=value))+ 
    geom_bar(aes(fill=variable), position="dodge", stat="identity")
This produces the following plot:



EDIT:
Well since pvs_id was numeric it is treated in an ordered fashion.  Where as if you have a factor no order is assumed.  So even though you have numeric labels pvs_id is actually a factor (nominal).  And as far as dat[order(-dat$mqs), 2] is concerned the order function with a negative sign orders the data frame from largest to smallest along the variable mqs.  But you're interested in that order for the pvs_id variable so you index that column which is the second column.  If you tear that apart you'll see it gives you:
> dat[order(-dat$mqs), 2]
[1] 6 2 0 5 7 4 8 3 1
Now you supply that to the levels argument of factor and this orders the factor as you want it.

                        
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