r - 创建信息更丰富的表格输出

Question

我有一个数据表，如下

panelID = c(1:50)   
year= c(2001:2010)
country = c("NLD", "BEL", "GER")
urban = c("A", "B", "C")
indust = c("D", "E", "F")
sizes = c(1,2,3,4,5)
n <- 2
library(data.table)
set.seed(123)
DT <- data.table(panelID = rep(sample(panelID), each = n),
                 country = rep(sample(country, length(panelID), replace = T), each = n),
                 year = c(replicate(length(panelID), sample(year, n))),
                 some_NA = sample(0:5, 6),                                             
                 some_NA_factor = sample(0:5, 6), 
                 industry = rep(sample(indust, length(panelID), replace = T), each = n),
                 urbanisation = rep(sample(urban, length(panelID), replace = T), each = n),
                 size = rep(sample(sizes, length(panelID), replace = T), each = n),
                 norm = round(runif(100)/10,2),
                 sales= round(rnorm(10,10,10),2),
                 Happiness = sample(10,10),
                 Sex = round(rnorm(10,0.75,0.3),2),
                 Age = sample(100,100),
                 Educ = round(rnorm(10,0.75,0.3),2))        
DT [, uniqueID := .I]                                                         # Creates a unique ID     
DT[DT == 0] <- NA 
DT$sales[DT$sales< 0] <- NA 
DT <- as.data.frame(DT)

setDT(DT)[,Mean_Sales_pergroup := mean(sales, na.rm=TRUE),  by=c("industry", "year")]

现在我想比较多年来每个行业的Mean_Sales_pergroup的差异，所以我想尝试一下:

table(DT$Mean_Sales_pergroup, DT$year)

但这给了我:

                   2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
  2.11                0    0    0    0    0    0    1    0    0    0
  2.18                0    0    0    0    0    0    0    0    0    1
  2.61                2    0    0    0    0    0    0    1    0    0
  3.6775              0    0    0    0    4    0    0    0    0    0
  ...
  14.19               0    0    0    0    0    0    0    2    0    0

这当然毫无信息可言。

我该怎么做才能得到类似的东西:

           2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
Industry D  ..
Industry E
Industry F

编辑:

@rg255 的评论给出:

dcast(DT, industry ~ year, value.var = "Mean_Sales_pergroup")
Aggregate function missing, defaulting to 'length'
   industry 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010
1:        D    1    1    5    5    3    4    1    1    6    1
2:        E    2    5    5    3    4    3    3    1    3    5
3:        F    1    6    2    3    4    7    5    2    4    4

Answer 1

制作唯一的行然后进行转换

dcast(unique(DT[, .(industry, year, Mean_Sales_pergroup)]), ... ~ year)

给出所需的输出

   industry  2001  2002   2003     2004    2005     2006     2007  2008
1:        D  2.61 4.260  6.204 9.650000 10.7050 8.625000 2.110000  2.61
2:        E 13.24 6.766  9.940 5.156667  3.6775 9.225000 4.606667 13.24
3:        F  2.61 8.000  ...