我有以下数据集:
sample.data <- data.frame(Step = c(1,2,3,4,1,2,1,2,3,1,1),
Case = c(1,1,1,1,2,2,3,3,3,4,5),
Decision = c("Referred","Referred","Referred","Approved","Referred","Declined","Referred","Referred","Declined","Approved","Declined"))
sample.data
Step Case Decision
1 1 1 Referred
2 2 1 Referred
3 3 1 Referred
4 4 1 Approved
5 1 2 Referred
6 2 2 Declined
7 1 3 Referred
8 2 3 Referred
9 3 3 Declined
10 1 4 Approved
11 1 5 Declined
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是否有可能在R中将其转换为宽表格格式,并在标题上做出决定,每个单元格的值都是事件的计数,例如:
Case Referred Approved Declined
1 3 1 0
2 1 0 1
3 2 0 1
4 0 1 0
5 0 0 1
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Jaa*_*aap 13
-package dcast函数中的聚合参数reshape2默认为length(= count).在data.table-package中,dcast实现了该功能的改进版本.所以在你的情况下,这将是:
library('reshape2') # or library('data.table')
newdf <- dcast(sample.data, Case ~ Decision)
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或明确使用参数:
newdf <- dcast(sample.data, Case ~ Decision,
value.var = "Decision", fun.aggregate = length)
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这给出了以下数据帧:
> newdf
Case Approved Declined Referred
1 1 1 0 3
2 2 0 1 1
3 3 0 1 2
4 4 1 0 0
5 5 0 1 0
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如果未指定聚合函数,则会收到警告,告知您将dcast其lenght用作默认值.
您可以通过简单的table()声明来完成此任务.您可以使用设置因子级别来获得您想要的响应.
sample.data$Decision <- factor(x = sample.data$Decision,
levels = c("Referred","Approved","Declined"))
table(Case = sample.data$Case,sample.data$Decision)
Case Referred Approved Declined
1 3 1 0
2 1 0 1
3 2 0 1
4 0 1 0
5 0 0 1
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这是一个dplyr + tidyr方法:
if (!require("pacman")) install.packages("pacman")
pacman::p_load(dplyr, tidyr)
sample.data %>%
count(Case, Decision) %>%
spread(Decision, n, fill = 0)
## Case Approved Declined Referred
## (dbl) (dbl) (dbl) (dbl)
## 1 1 1 0 3
## 2 2 0 1 1
## 3 3 0 1 2
## 4 4 1 0 0
## 5 5 0 1 0
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