R:将描述性列和相关值组合成矩阵形式

时间：2022-02-06 04:21:39

I have a lengthy data set of operations (op#) and times {tm#) associated with various widgets. Unfortunately the operations are in no specific order so a paint operation might occur in the first operation or the 80th. Each operation has the associated time it takes to complete that operation in the column to the right. I would like to organize the data so that each column is a unique operation name, and the values in the column are the associated time it takes to complete that operation.

我有一个很长的操作数据集(op#)和与各种小部件相关的时间{tm#)。不幸的是，操作没有特定的顺序，因此油漆操作可能在第一次操作或第80次操作中发生。每个操作都有完成右边列中的操作所需的相关时间。我希望对数据进行组织，使每个列都是唯一的操作名，列中的值是完成该操作所需的相关时间。

# sample data frame
df = data.frame(widget = c("widget 1", "widget 2", "widget 3", "widget 4"),
            op1 = c("paint", "weld", "frame", "weld"),
            tm1 = c(20, 24, 14, 40),
            op2 = c("weld", "coat", "weld", "paint"),
            tm2 = c(10, 20, 50, 30))

print(df)
>      part   op1 tm1   op2 tm2  
> 1 widget1 paint  20  weld  10
> 2 widget2  weld  24  coat  20
> 3 widget3 frame  14  weld  50
> 4 widget4  weld  40 paint  30

I am trying to reorganize the data frame as...

我试图把数据框重新组织成……

>      part  paint  weld  coat  frame 
> 1 widget1     20    10  NULL   NULL
> 2 widget2   NULL    24    20   NULL
> 3 widget3   NULL    50  NULL     14
> 4 widget4     30    40  NULL   NULL

Any suggestions?

有什么建议吗?

1 个解决方案

#1

2  

Try:

试一试:

If `df1` is the dataset

names(df1)[grep("^op|^tm",names(df1))] <- gsub("([[:alpha:]]+)(\\d+)", "\\1_\\2",   names(df1)[grep("^op|^tm", names(df1))])
 df2 <- reshape(df1, idvar="widget", varying= grep("^op|^tm",names(df1)), sep="_", direction="long")
 library(reshape2)
 dcast(df2, widget~op, value.var="tm")[,c(1,3:5,2)]
 #      widget paint weld coat frame
 #1 widget 1    20   10   NA    NA
 #2 widget 2    NA   24   20    NA
 #3 widget 3    NA   50   NA    14  ##looks like you have 50 instead of 60 as shown in the expected
 #4 widget 4    30   40   NA    NA
  • I used a combination of grep and gsub to modify the names of those columns (tm, op) so that there is separation _ between common characters and the corresponding numbers, makes it easy to work with reshape
  • 我使用了grep和gsub的组合来修改这些列的名称(tm, op)，以便在公共字符和相应的数字之间有分离_，这样就很容易进行重新组合
  • After reshaping to longer format, reformat it back to a different wide format with dcast
  • 重新格式化为较长的格式后，使用dcast将其重新格式化为不同的宽格式

#1

2  

Try:

试一试:

If `df1` is the dataset

names(df1)[grep("^op|^tm",names(df1))] <- gsub("([[:alpha:]]+)(\\d+)", "\\1_\\2",   names(df1)[grep("^op|^tm", names(df1))])
 df2 <- reshape(df1, idvar="widget", varying= grep("^op|^tm",names(df1)), sep="_", direction="long")
 library(reshape2)
 dcast(df2, widget~op, value.var="tm")[,c(1,3:5,2)]
 #      widget paint weld coat frame
 #1 widget 1    20   10   NA    NA
 #2 widget 2    NA   24   20    NA
 #3 widget 3    NA   50   NA    14  ##looks like you have 50 instead of 60 as shown in the expected
 #4 widget 4    30   40   NA    NA
  • I used a combination of grep and gsub to modify the names of those columns (tm, op) so that there is separation _ between common characters and the corresponding numbers, makes it easy to work with reshape
  • 我使用了grep和gsub的组合来修改这些列的名称(tm, op)，以便在公共字符和相应的数字之间有分离_，这样就很容易进行重新组合
  • After reshaping to longer format, reformat it back to a different wide format with dcast
  • 重新格式化为较长的格式后，使用dcast将其重新格式化为不同的宽格式
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