R:来自具有多个函数的聚合的结果在进一步的计算中不可用.为什么？

Question

Hello Stackoverflow用户,

我对R中的聚合函数的结果有一个问题.我的目的是从数据集中选择某些鸟类,并计算被调查区域内观察到的个体的密度.为此,我获取了主数据文件的一个子集,然后在区域上聚合,计算平均值和个体数量(由向量长度表示).然后我想用计算出的平均面积和个体数来计算密度.那没用.我使用的代码如下:

> head(data)

  positionmonth positionyear quadrant           Species  Code sum_areainkm2

1             5         2014        1 Bar-tailed Godwit  5340      155.6562

2             5         2014        1 Bar-tailed Godwit  5340      155.6562

3             5         2014        1 Bar-tailed Godwit  5340      155.6562

4             5         2014        1 Bar-tailed Godwit  5340      155.6562

5             5         2014        1            Gannet   710      155.6562

6             5         2014        1 Bar-tailed Godwit  5340      155.6562


sub.gannet<-subset(data, species == "Gannet")

sub.gannet<-data.frame(sub.gannet)


x<-sub.gannet

aggr.gannet<-aggregate(sub.gannet$sum_areainkm2, by=list(sub.gannet$positionyear, sub.gannet$positionmonth, sub.gannet$quadrant, sub.gannet$Species, sub.gannet$Code), FUN=function(x) c(observed_area=mean(x), NoInd=length(x)))

names(aggr.gannet)<-c("positionyear", "positionmonth", "quadrant", "species", "code", "x")

aggr.gannet<-data.frame(aggr.gannet)


> aggr.gannet

  positionyear positionmonth quadrant species code x.observed_area x.NoInd

1         2014             5        4  Gannet  710         79.8257 10.0000


density <- c(aggr.gannet$x.NoInd/aggr.gannet$x.observed_area)

aggr.gannet <- cbind(aggr.gannet, density)

Error in data.frame(..., check.names = FALSE) : 

  Arguments imply differing number of rows: 1, 0

> density

numeric(0)

> aggr.gannet$x.observed_area

NULL

> aggr.gannet$x.NoInd

NULL

R似乎没有将函数(observed_area和NoInd)的结果视为数值本身.当我无法给每个人起名字时,这已经很明显了,但不得不称他们为"x".

有人可以告诉我,为什么会这样.在这些情况下如何计算密度？或者是否有另一种方法可以在同一个变量上聚合多个函数,从而产生可用的输出？

任何想法将不胜感激,谢谢!

Answer 1

这是一个具有多个聚合的聚合的怪癖,结果聚合存储在与聚合变量相关的列中的列表中.

摆脱这种情况的最简单方法是通过as.list之前的方法as.dataframe来平衡数据结构.

aggr.gannet <- as.data.frame(as.list(aggr.gannet))

它仍然会x用作名称.我发现修复此问题的方法是使用公式接口aggregate,因此您的聚合看起来更像

aggr.gannet<-aggregate(
  sum_areainkm2 ~ positionyear + positionmonth +
    quadrant + Species + Code,
  data=sub.gannet,
  FUN=function(x) c(observed_area=mean(x), NoInd=length(x)))

穿过它(这里我没有采用子集来说明物种的聚合)

df <- structure(list(positionmonth = c(5L, 5L, 5L, 5L, 5L, 5L), positionyear = c(2014L, 2014L, 2014L, 2014L, 2014L, 2014L), quadrant = c(1L, 1L, 1L, 1L, 1L, 1L), Species = structure(c(1L, 1L, 1L, 1L, 2L, 1L), .Label = c("Bar-tailed Godwit", "Gannet"), class = "factor"), Code = c(5340L, 5340L, 5340L, 5340L, 710L, 5340L), sum_areainkm2 = c(155.6562, 155.6562, 155.6562, 155.6562, 155.6562, 155.6562)), .Names = c("positionmonth", "positionyear", "quadrant", "Species", "Code", "sum_areainkm2"), class = "data.frame", row.names = c(NA, -6L))

df.agg <- as.data.frame(as.list(aggregate(
      sum_areainkm2 ~ positionyear + positionmonth +
        quadrant + Species + Code,
      data=df,
      FUN=function(x) c(observed_area=mean(x), NoInd=length(x)))))

这导致你想要的:

> df.agg
  positionyear positionmonth quadrant           Species Code
1         2014             5        1            Gannet  710
2         2014             5        1 Bar-tailed Godwit 5340
  sum_areainkm2.observed_area sum_areainkm2.NoInd
1                    155.6562                   1
2                    155.6562                   5
> names(df.agg)
[1] "positionyear"                "positionmonth"
[3] "quadrant"                    "Species"
[5] "Code"                        "sum_areainkm2.observed_area"
[7] "sum_areainkm2.NoInd"

这里强制性注意到,这dplyr和data.table是允许非常简单而有效地做这样的聚集强大的库.

dplyr

Dplyr有一些奇怪的语法(%>%运算符),但最终具有很强的可读性,并允许链接更复杂的操作

> require(dplyr)
> df %>%
  group_by(positionyear, positionmonth, quadrant, Species, Code) %>%
  summarise(observed_area=mean(sum_areainkm2), NoInd = n())

data.table

data.table具有更紧凑的语法,对于大型数据集可能更快.

dt[,
  .(observed_area=mean(sum_areainkm2), NoInd=.N),
  by=.(positionyear, positionmonth, quadrant, Species, Code)]