在plyr中使用多个变量 [英] using multiple variables in plyr

问题描述

我正在尝试使用plyr，但是在使用多个变量时遇到困难. 这里举个例子.

I am trying to use plyr but have difficulties in using several variables. Here an example.

    df <- read.table(header=TRUE, text="
    Firm Foreign SME Turnover
A1       N   Y      200
A2       N   N     1000
A3       Y   Y      100
A1       N   N      500
A2       Y   Y      200
A3       Y   Y     1000
A1       Y   N      200
A2       N   N     1000
A2       N   Y      100
A2       N   Y      200  ")

我正在尝试创建一个表，该表总结了两个变量的营业额. 基本上结合以下代码

I am trying to create a table which summarize the Turnover on the two variables. Basically combining the following codes

t1 <- ddply(df, c('Firm', 'Foreign'), summarise, 
        BudgetForeign    = sum(Turnover, na.rm = TRUE))

t2 <- ddply(df, c('Firm', 'SME'), summarise, 
        BudgetSME    = sum(Turnover, na.rm = TRUE))

具有以下结果

res <- read.table(header=TRUE, text="
Firm          A1   A2   A3  
BudgetForeign 200  200 1100
BudgetSME     200  500 1100")
res

如何在不进行多次操作和子集再合并的情况下实现此目标?

How can I achieve this without doing multiple operations and subset and combine afterwards ?

先谢谢了.

推荐答案

我认为您只需要Foreign或SME为'Y' ...的值.我会使用reshape2软件包中的melt和dcast而不是plyr.

I think you only want the values where Foreign or SME are 'Y'... if that's the case. I would use melt and dcast from the reshape2 package rather than plyr.

df.m <- melt(df, id.var=c('Firm', 'Turnover'))

dcast(df.m[df.m$value=='Y',], variable ~ Firm, value.var='Turnover', fun.aggregate=sum)

  variable  A1  A2   A3
1  Foreign 200 200 1100
2      SME 200 500 1100

如果要查看Y和N之间的差异，也可以将它们添加到dcast中的公式中:

If you want to see the differences between Y and N also you can add them to the formula in dcast:

> dcast(df.m, variable + value ~ Firm, value.var='Turnover', fun.aggregate=sum)
  variable value  A1   A2   A3
1  Foreign     N 700 2300    0
2  Foreign     Y 200  200 1100
3      SME     N 700 2000    0
4      SME     Y 200  500 1100
> 

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