如何在r中给定另一列的连续字符串的情况下找到列中连续数字的均值 [英] How to find the means of consecutive numbers in a column given consecutive string of another column in r
问题描述
我有一个与此类似的数据集:
I have a dataset that looks similar to this:
head(df,20)
mmpd tot
1 0 0
2 mm 0
3 mm 1
4 0 0
5 0 0
6 mm 0
7 mm 1
8 mm 3
9 mm 1
10 0 0
11 0 0
12 0 0
13 0 0
14 mm 0
15 mm 0
16 0 0
17 0 0
18 mm 4
19 mm 1
20 mm 0
当df$mmpd 中的一串mm 对应时,我想得到df$tot 的平均值.因此,对于示例数据集,我想获得以下数字字符串:.5、1.25、0、1.667.df$mmpd 将始终是一串 mm > 1 或 0,并且该列可以以 0 或一串 mm 开头.
I would like to get the average of df$tot when it corresponds to a string of mm in df$mmpd. So for the example dataset, I'd like to get the following string of numbers: .5, 1.25, 0, 1.667. df$mmpd will always either be a string of mm > 1, or 0, and the column can begin with either 0 or a string of mm.
有没有办法在没有 for 循环的情况下做到这一点?
Is there a way to do this without a for loop?
推荐答案
Using data.table
library(data.table) # v 1.9.5+
setDT(df)[,.(my=mean(tot)), by=.(indx=rleid(mmpd),mmpd)][,indx:=NULL][mmpd=='mm']
mmpd my
#1: mm 0.500000
#2: mm 1.250000
#3: mm 0.000000
#4: mm 1.666667
显然,有很多方法可以做到(参见r 沿向量搜索并计算平均值).data.table
方法在此处速度最快且经过调整.
Apparently, there are many ways to do it (see r search along a vector and calculate the mean). The data.table
method was fastest and adapted here.
注意:rleid
可以在 data.table
语法之外使用.这将更像传统"R
语法并产生相同的结果.
Note: rleid
can be use outside of the data.table
syntax. This will be more like "traditional" R
syntax and produce the same results.
subset(aggregate(tot ~ indx + mmpd,
data=cbind(df,indx=rleid(df$mmpd)),
FUN=mean),mmpd=="mm")
rleid(myrleid)不同生成方式的速度比较来自@JasonAizkalns 的回答).
Speed comparison of different ways to generate rleid (myrleid is from @JasonAizkalns answer).
> set.seed(1); x<-sample(1:2,100000,replace=T);
microbenchmark(rleid(x),
myrleid2=cumsum(c(1,diff(x)!=0)),
myrleid(x))
Unit: milliseconds
expr min lq mean median uq max neval cld
rleid(x) 1.422263 1.500873 1.586482 1.571315 1.662982 1.938254 100 a
myrleid2 3.860290 3.908308 4.369646 3.962497 4.177673 15.674611 100 b
myrleid(x) 7.282868 7.386515 7.753515 7.444008 7.654126 18.864898 100 c
对于非数字 x:
> set.seed(1); x<-sample(c('a','b'),100000,replace=T);
> microbenchmark(rleid(x),myrleid2=cumsum(c(1,diff(as.numeric(factor(x)))!=0)),myrleid(x))
Unit: milliseconds
expr min lq mean median uq max neval cld
rleid(x) 1.465466 1.571662 1.684568 1.606614 1.66080 2.900983 100 a
myrleid2 8.705447 9.276787 12.393393 9.907403 10.35032 61.080374 100 b
myrleid(x) 11.970271 13.176144 18.779256 13.790767 14.09626 69.845587 100 c
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