Question

所以我有一个csv，我操纵过给我这个叫做的表 Completion

 dput(Completion)

 structure(list(value = structure(1:16, .Label = c("0%", "100%", "13%", "15%","16%", "24%", "26%", "28%", "33%", "40%", "50%", "53%", "66%", "73%", "75%", "93%"), class = "factor"), All = c(13L, 0L, 3L, 0L, 0L, 1L, 1L, 0L, 1L, 1L, 0L, 2L, 0L, 1L, 0L, 3L), 
M0 = c(14L, 10L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 1L, 0L, 
0L, 0L, 0L, 0L), M1 = c(17L, 6L, 0L, 0L, 0L, 0L, 0L, 1L, 
0L, 0L, 1L, 0L, 1L, 0L, 0L, 0L), M2 = c(21L, 4L, 0L, 0L, 
1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L), M3 = c(21L, 
2L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 2L, 0L)), 
.Names = c("value", "All", "M0", "M1", "M2", "M3"), row.names = c(NA, 16L), class = 
c("cast_df", "data.frame"), idvars = "value", rdimnames = list(structure(list(value = 
structure(1:16, .Label = c("0%", "100%", "13%", "15%", "16%", "24%", "26%", "28%", "33%", 
"40%", "50%", "53%", "66%", "73%", "75%", "93%"), class = "factor")), 
.Names = "value", row.names = c("0%", "100%", "13%", "15%", "16%", "24%", "26%", "28%", 
"33%", "40%", "50%", "53%", "66%", "73%", "75%", "93%"), class = "data.frame"), 
structure(list(Module = structure(1:5, .Label = c("All", 
"M0", "M1", "M2", "M3"), class = "factor")), .Names = "Module", row.names = c("All", 
"M0", "M1", "M2", "M3"), class = "data.frame")), .Label = 
c("0-49","50-59","60-69", "70-79",
"80-89", ">90"))

此表显示课程中给定模块完成（值）％的人数。

我想要做的是为值创建类别如下; 多数（90％-100％），实质性（75％-89％），部分（50％-74％），最小（1％-49％）和不完整（0％）然后，我希望能够计算出 by module 的所有实例，如下所示：

              M0     M1     M2     M3     All
Majority       1      2      3      4       5
Substantial    5      4      3      2       1 
Partial        4      3      2      1       5 
Minimal        3      2      1      5       4 
Incomplete     2      1      5      4       3

每个实例的计数将填满表格。

有办法做到这一点吗？我尝试制作不同的数据透视表，并附加关卡;

comp.rate <- Completion$value
comp.rate <- ordered(comp.rate, levels = c("Majority", "Substantial", "Partial", "Minimal", 
"Incomplete"))

我想我不知道如何将我想要的值分配给这些级别然后反过来让R吐出它们的出现次数。我也有问题，因为值是百分比形式...而不是十进制。我没有附上我的完整代码，但如果有任何用处我可以... 任何帮助是极大的赞赏。谢谢！

Answer 1

您可以这样做：

首先，您必须使用gsub

将百分比列转换为数字列

d$value <- as.numeric(gsub("[%]", "", d$value))

然后您可以使用条件和colSums来计算所有出现次数：

#Majority(90%-100%)
colSums(d[ d$value >= 90, ])
value   All    M0    M1    M2    M3 
  193     3    10     6     4     2 

# or Substantial(75%-89%)
colSums(d[ d$value >= 75 & d$value < 89, ])
value   All    M0    M1    M2    M3 
   75     0     0     0     0     2

将所有内容保存在一个data.frame中：

a1 <- colSums(d[ d$value >= 90,])
a2 <- colSums(d[ d$value >= 75 & d$value < 89, ])
result <- data.frame(rbind(a1, a2))
result$value <- c("Majority", "Substantial")
result
         value All M0 M1 M2 M3
a1    Majority   3 10  6  4  2
a2 Substantial   0  0  0  0  2

将类别附加到一系列值（百分比）并排序？

1 个答案: