从R中的数据帧获取净值作为比例的结果(第2部分)

时间:2018-06-28 19:28:52

标签: r dataframe dplyr

我最近在calculating net proportions for a table in R方面获得了帮助,但是尝试对其进行总结是没有用的,当我选择答案时,我需要发布一个新问题。

这是我的原始数据(我称为qf):

genre  status  rb  wrb  inn
Fiction  FAILURE  621  66  1347
Fiction  FAILURE  400  46  928
Fiction  FAILURE  238  35  663
Poetry  FAILURE  513  105  1732
Poetry  FAILURE  165  47  393
Poetry  FAILURE  896  193  2350
Love-story  FAILURE  5690  501  8869
Love-story  FAILURE  1284  174  2793
Love-story  FAILURE  7279  715  13852
Love-story  SUCCESS  18150  1734  39635
Poetry  SUCCESS  1988  226  4712
Love-story  SUCCESS  20110  2222  43953
Love-story  SUCCESS  20762  2288  46706
Poetry  SUCCESS  1824  322  3984
Poetry  SUCCESS  1105  148  2751
Adventure  SUCCESS  4675  617  8462
Adventure  SUCCESS  7943  599  17247
Adventure  SUCCESS  7290  601  17774

由于有了答案,我设法按类型和成功/失败总结了它(我喜欢跟踪所有转换,因此跟踪多个数据帧):

qf2 <- qf %>% group_by(genre,status) %>% summarise_all(sum)

qf3 <- ff2 %>%  as.data.frame()

qf4 <- qf3 %>% mutate(rowSum = rowSums(.[,names(qf3)[3:5]])) %>% 
group_by(genre) %>% 
summarise_at(vars(names(qf3)[3:5]),   
           funs(net = .[status == "SUCCESS"]/rowSum[status == "SUCCESS"] - 
                  .[status == "FAILURE"]/rowSum[status == "FAILURE"] )) %>%
as.data.frame()

但是我现在要做的是获取整体比例。但是,无论我尝试什么,都行不通。我想我缺少明显的东西。

我想要得到的是以下内容的输出:

Sum-FAILURE  0.329241738  0.036265536  0.634492726
Sum-SUCCESS  0.301794636  0.031519501  0.666685863
Net  -0.027447103  -0.004746035  0.032193137

我试图创建的计算是(对于rb):

(Sum(success_rb)/(Sum(success_rb)+Sum(success_wrb)+Sum(Success_inn)) -  (Sum(failure_rb)/(Sum(failure_rb)+Sum(failure_wrb)+Sum(failure_inn))

1 个答案:

答案 0 :(得分:2)

qf %>% 
  select(-genre)%>%
  group_by(status) %>% 
  summarise_all(sum)%>%
  {.[-1]/rowSums(.[-1])}%>%
  rbind(.[2,]-.[1,])

          rb          wrb        inn
1   0.3292417  0.036265536 0.63449273
2   0.3017946  0.031519501 0.66668586
21 -0.0274471 -0.004746035 0.03219314

library(data.table)
setDT(qf)[,lapply(.SD,sum),status,.SDcols=3:5][,
             .SD/rowSums(.SD),.SDcols=-1][,rbind(.SD,.SD[2]-.SD[1])]
           rb          wrb        inn
1:  0.3292417  0.036265536 0.63449273
2:  0.3017946  0.031519501 0.66668586
3: -0.0274471 -0.004746035 0.03219314