用R编程语言创建OLAP多维数据集 [英] create OLAP cube in R programming language

问题描述

我有以下数据

  Function    SB `Country Region` `+1 Function` `+1 SB` `+1 Country Region`
     <chr> <chr>            <chr>         <chr>   <chr>               <chr>
1      ENG  SB10             AMER           ENG    SB10                AMER
2       IT  SB07             EMEA            IT    SB07                EMEA
3      QLT  SB05             EMEA           QLT    SB05                EMEA
4      MFG  SB07             EMEA           MFG    SB07                EMEA
5      MFG  SB04             EMEA           MFG    SB05                EMEA
6      SCM  SB08             EMEA           SCM    SB08                EMEA

我想创建3维OLAP多维数据集，其中功能SB国家/地区"列应位于行中，而+1 Function，+1 SB，+1 Country Region列应位于列中.

i want to create 3 dimensional OLAP cube in which column Function SB Country Region should be in row and +1 Function,+1 SB, +1 Country Region should be in column .

输出应采用以下格式

                   `+1 Function` `+1 SB` `+1 Country Region`  
Function
SB 
Country Region

谢谢

添加精确的RpivotTable输出.

Adding exact RpivotTable output.

推荐答案

例如，您可以使用ftable():

df <- read.table(text =
"  Function    SB 'Country Region' '+1 Function' '+1 SB' '+1 Country Region'
       ENG  SB10             AMER           ENG    SB10                AMER
        IT  SB07             EMEA            IT    SB07                EMEA
       QLT  SB05             EMEA           QLT    SB05                EMEA
       MFG  SB07             EMEA           MFG    SB07                EMEA
       MFG  SB04             EMEA           MFG    SB05                EMEA
       SCM  SB08             EMEA           SCM    SB08                EMEA",
  stringsAsFactors = FALSE, header = TRUE, check.names = FALSE)

foo <- ftable(df, row.vars = c(3, 1, 2), col.vars = c(6, 4, 5))

as.matrix(foo)[apply(foo, 1, function(x) any(x != 0)), apply(foo, 2, function(x) any(x != 0))]
# Or simply:
as.matrix(foo)[apply(foo, 1, any), apply(foo, 2, any)]

#                           +1 Country Region_+1 Function_+1 SB
# Country Region_Function_SB AMER_ENG_SB10 EMEA_IT_SB07 EMEA_MFG_SB05 EMEA_MFG_SB07 EMEA_QLT_SB05 EMEA_SCM_SB08
#              AMER_ENG_SB10             1            0             0             0             0             0
#              EMEA_IT_SB07              0            1             0             0             0             0
#              EMEA_MFG_SB04             0            0             1             0             0             0
#              EMEA_MFG_SB07             0            0             0             1             0             0
#              EMEA_QLT_SB05             0            0             0             0             1             0
#              EMEA_SCM_SB08             0            0             0             0             0             1

与rpivotTable::rpivotTable(df, rows = c("Country Region", "Function", "SB"), cols = c("+1 Country Region", "+1 Function", "+1 SB"))的比较:

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