计算R上基于五分位数的分数

时间:2016-09-26 02:39:29

标签: r statistics aggregate-functions quantile tapply

我有一个年度(2006年至2010年)的数据框,4个行业部门,150个公司名称和这些公司的净收入。总共我有750个观察结果,每个公司每年一个。我希望根据五分位数给每个行业年度的公司提供收入。因此,每个行业年收入在前20%的公司获得5分,接下来的20%获得4分,依此类推。最低的20%获得1分。

示例数据库是:

eval `opam config env`

我如何在R中执行此操作?我已尝试Year Industry Firm Income 2006 Chemicals ABC 334.50 2007 Chemicals ABC 388.98 . . 2006 Pharma XYZ 91.45 . . aggregate以及tapply,但无法达到应该用于此的逻辑。请帮忙。

我试过这个只是将得分1分配给最低的20%,但它返回了一个错误。

quantile

1 个答案:

答案 0 :(得分:1)

试试这个方法:

首先,我将创建样本,以测试下面的函数:

y = c(rep(2001,15),rep(2002,15),rep(2003,15))
ind = c("A","B","C","D","E","G","H","I","J","K","L","M","N","O","P")
val = runif(45,10,100)
df = data.frame(y,ind,val)

head(df,20)

      y ind      val
1  2001   A 63.32011
2  2001   B 85.67976
3  2001   C 86.77527
4  2001   D 32.18319
5  2001   E 49.86626
6  2001   G 57.73214
7  2001   H 18.08216
8  2001   I 22.31012
9  2001   J 44.11174
10 2001   K 54.76902
11 2001   L 41.82495
12 2001   M 64.84514
13 2001   N 59.16529
14 2001   O 61.28870
15 2001   P 84.76561
16 2002   A 83.68185
17 2002   B 45.01354
18 2002   C 62.22964
19 2002   D 98.41717
20 2002   E 19.91548

有3年,从A到P的行业。数据框架按行和年份排序。

以下此功能需要一年的值y,并计算年df$valdf$y的所有y的五分类

quintile = function(y) {
    x = df$val[df$y == y]
    qn = quantile(x, probs = (0:5)/5)
    result = as.numeric(cut(x, qn, include.lowest = T))
}

唯一剩下的就是将此功能应用于唯一年份值

df$qn = unlist(lapply(unique(df$y), quintile))

结果:

> head(df,20)
      y ind      val qn
1  2001   A 63.32011  4
2  2001   B 85.67976  5
3  2001   C 86.77527  5
4  2001   D 32.18319  1
5  2001   E 49.86626  2
6  2001   G 57.73214  3
7  2001   H 18.08216  1
8  2001   I 22.31012  1
9  2001   J 44.11174  2
10 2001   K 54.76902  3
11 2001   L 41.82495  2
12 2001   M 64.84514  4
13 2001   N 59.16529  3
14 2001   O 61.28870  4
15 2001   P 84.76561  5
16 2002   A 83.68185  4
17 2002   B 45.01354  1
18 2002   C 62.22964  3
19 2002   D 98.41717  5
20 2002   E 19.91548  1

也许有一种更简单的方法来实现这个......

按两栏分组

如果您想根据两列的分组计算五分位数:ygrp

y = c(rep(2001,15),rep(2002,15),rep(2003,15))
grp = c("G1","G1","G1","G1","G1","G2","G2","G2","G2","G2","G3","G3","G3","G3","G3")
ind = c("A","B","C","D","E","G","H","I","J","K","L","M","N","O","P")
val = round(runif(45,10,100))
df = data.frame(y,grp,ind,val)

> head(df,20)
      y grp ind val
1  2001  G1   A  40
2  2001  G1   B  33
3  2001  G1   C  65
4  2001  G1   D  99
5  2001  G1   E  18
6  2001  G2   G  36
7  2001  G2   H  15
8  2001  G2   I  17
9  2001  G2   J  42
10 2001  G2   K  67
11 2001  G3   L  60
12 2001  G3   M  34
13 2001  G3   N  61
14 2001  G3   O  76
15 2001  G3   P  15
16 2002  G1   A  18
17 2002  G1   B  15
18 2002  G1   C  44
19 2002  G1   D  79
20 2002  G1   E  22

然后使用:

quintile = function(z) {
    x = df$val[df$y == z[1] & df$grp == z[2]]
    qn = quantile(x, probs = (0:5)/5)
    result = as.numeric(cut(x, qn, include.lowest = T))
}


df$qn = as.vector(apply(unique(df[,c("y","grp")]),1, quintile))

结果:

> head(df,20)
      y grp ind val qn
1  2001  G1   A  40  3
2  2001  G1   B  33  2
3  2001  G1   C  65  4
4  2001  G1   D  99  5
5  2001  G1   E  18  1
6  2001  G2   G  36  3
7  2001  G2   H  15  1
8  2001  G2   I  17  2
9  2001  G2   J  42  4
10 2001  G2   K  67  5
11 2001  G3   L  60  3
12 2001  G3   M  34  2
13 2001  G3   N  61  4
14 2001  G3   O  76  5
15 2001  G3   P  15  1
16 2002  G1   A  18  2
17 2002  G1   B  15  1
18 2002  G1   C  44  4
19 2002  G1   D  79  5
20 2002  G1   E  22  3

我是这个例子,y将成为行业组grp年,ind公司和val收入。

注意c("y","grp")apply的顺序以及五分位函数内的列名称。您必须使用所需的列名替换它们。

请注意,如果您的小组很小(在此示例中为每组5家公司),则五分位数可能不是唯一的,并且会弹出错误。

使用问题

中的列名称
quintile = function(z) {
    x = df$Income[df$Year == z[1] & df$Industry == z[2]]
    qn = quantile(x, probs = (0:5)/5)
    result = as.numeric(cut(x, qn, include.lowest = T))
}


df$qn = as.vector(apply(unique(df[,c("Year","Industry")]),1, quintile))

在应用此数据之前,必须按年​​份和行业订购数据框df