在过滤后的字符上拆分数据框并制作多个新列

Question

我有一个数据预处理问题，这在我的工作中很常见。我通常有两个文件，最后我想对其进行大型匹配操作。这通常是一个两步过程，第一步涉及制作第一个文件的 "cleaned" 数据帧，第二步是与更大数据帧的第二个文件进行匹配（vlookup）。我需要帮助解决这个问题的第一步。我在下面创建了一个简单的示例来进行处理。我的简化数据框：

c1 <- 1:15
c2 <- c("Valuelabels", "V1", "1", "2", "Valuelabels", "V2", "1", "2", "3", "Valuelabels", "V3", "1", "2", "3", "4")
c3 <- c("", "", "Male", "Female", "", "", "Married", "Single", "Other", "", "", "SingleWithChildren", "SingleWithoutChildren","MarriedWithChildren", "PartneredWithChildren") 

df <- data.frame(row.names =c1,c2,c3)
df

            c2                    c3
1  Valuelabels                      
2           V1                      
3            1                  Male
4            2                Female
5  Valuelabels                      
6           V2                     
7            1               Married
8            2                Single
9            3                 Other
10 Valuelabels                      
11          V3                      
12           1    SingleWithChildren
13           2 SingleWithoutChildren
14           3   MarriedWithChildren
15           4 PartneredWithChildren

现在，我想在第一列的 "Valuelabel" 字符串上拆分数据框，最后得到一个如下所示的新数据框：

   V1 V1_match V2 V2_match V3              V3_match
1:  1     Male  1  Married  1    SingleWithChildren
2:  2   Female  2   Single  2 SingleWithoutChildren
3: NA           3    Other  3   MarriedWithChildren
4: NA          NA           4 PartneredWithChildren

最后我想创建一个数据框，其中 V1 作为列名，并将这些值下的匹配值作为我示例中命名的新列 V1_match... 以此类推 V2 到V3.

此数据框将在与更大的数据框匹配之前结束我的第一步。

非常感谢您的帮助。

Answer 1

这是一个可能的 data.table 解决方案

library(data.table) # v 1.9.5
setDT(df)[, indx := c2[2L], by = cumsum(c2 == "Valuelabels")]
df2 <- df[!grepl("\D", c2)][, indx2 := seq_len(.N), by = indx]
dcast(df2, indx2 ~ indx, value.var = c("c2", "c3"))
#    indx2 V1_c2 V2_c2 V3_c2  V1_c3   V2_c3                 V3_c3
# 1:     1     1     1     1   Male Married    SingleWithChildren
# 2:     2     2     2     2 Female  Single SingleWithoutChildren
# 3:     3    NA     3     3     NA   Other   MarriedWithChildren
# 4:     4    NA    NA     4     NA      NA PartneredWithChildren

您需要安装 data.table v > 1.9.5 才能运行使用

library(devtools)
install_github("Rdatatable/data.table", build_vignettes = FALSE)

Answer 2

另一种方法基础R：

lst = lapply(split(df,cumsum(df$c2=='Valuelabels')), tail, -2)
Reduce(function(u,v) merge(u,v,by='c2',all=T), lst)
#  c2   c3.x    c3.y                    c3
#1  1   Male Married    SingleWithChildren
#2  2 Female  Single SingleWithoutChildren
#3  3   <NA>   Other   MarriedWithChildren
#4  4   <NA>    <NA> PartneredWithChildren

在过滤后的字符上拆分数据框并制作多个新列

Split dataframe on filtered character and make multiple new columns

r

dataframe

reshape