Question

我想将R用于具有两个数据帧的基本数据库目的：第一个数据框是具有不同特征的个人列表：

data = data.frame("individual"=c("Steve","Bob","Simon","Lisa"),
                  "feature1"=c(1,2,2,3),
                  "feature2"=c(3,4,1,NA))

第二个数据框具有特征描述：

description = data.frame("feature"=c(1,2,3,4,NA), 
                         "label"=c("foot","golf","curling","ski","No answer"))

我的目标是制作第三个数据框，其中包含个人姓名及其功能描述：

Steve foot curling
Bob   golf ski

依旧......

Answer 1

sqldf 尝试以下三种方式加入：

library(sqldf)

data[is.na(data)] <- "NA"
description[is.na(description)] <- "NA"

sqldf("select d1.individual, d2.label, d3.label
        from data d1 
        left join description d2 on d1.feature1 = d2.feature
        left join description d3 on d1.feature2 = d3.feature"
)

输出结果为：

  individual   label     label
1      Simon    golf      foot
2      Steve    foot   curling
3        Bob    golf       ski
4       Lisa curling No answer

<强>下标

此解决方案假设我们已经运行了上面的两条<- "NA"行。

labels <- with(description, setNames(label, feature))
with(data, 
  data.frame(individual, labels[feature1], labels[feature2], stringsAsFactors = FALSE)
)

给出输出：

   individual labels.feature1. labels.feature2.
3       Steve             foot          curling
4         Bob             golf              ski
1       Simon             golf             foot
NA       Lisa          curling        No answer

修订：

使用左连接。
将NAs处理为常规值。
添加第二个解决方案。

Answer 2

对于此任务，可以使用match。

cbind(data[1], as.data.frame(lapply(data[-1], function(x) 
                              description$label[match(x, description$feature)])))

  individual feature1  feature2
1      Steve     foot   curling
2        Bob     golf       ski
3      Simon     golf      foot
4       Lisa  curling No answer

Answer 3

使用plyr和reshape2

来获取第三种方法

require(reshape2)
require(plyr)
dcast(join(melt(data, id = "individual", value.name = "feature"), description),
      individual ~ variable, value.var = "label")

  individual feature1  feature2
1        Bob     golf       ski
2       Lisa  curling No answer
3      Simon     golf      foot
4      Steve     foot   curling

类似数据库的基本用法

3 个答案: