在R中创建一个二进制指标矩阵(布尔矩阵) [英] Create a binary indicator matrix (Boolean matrix) in R

问题描述

我有一个数据列表，表明参加会议的情况如下:

I have a list of data indicating attendance to conferences like this:

Event                     Participant  
ConferenceA               John   
ConferenceA               Joe  
ConferenceA               Mary    
ConferenceB               John  
ConferenceB               Ted  
ConferenceC               Jessica  

我想创建以下格式的二进制指标出勤矩阵:

I would like to create a binary indicator attendance matrix of the following format:

Event        John  Joe  Mary  Ted  Jessica  
ConferenceA  1     1    1     0    0  
ConferenceB  1     0    0     1    0  
ConferenceC  0     0    0     0    1  

有没有办法在R中做到这一点?

Is there a way to do this in R?

推荐答案

假设您的data.frame被称为"mydf"，只需使用table:

Assuming your data.frame is called "mydf", simply use table:

> table(mydf)
             Participant
Event         Jessica Joe John Mary Ted
  ConferenceA       0   1    1    1   0
  ConferenceB       0   0    1    0   1
  ConferenceC       1   0    0    0   0

如果某人有可能多次参加会议，导致table返回大于1的值，则可以像这样将所有大于1的值重新编码.

If there is a chance that someone would have attended a conference more than once, leading table to return a value greater than 1, you can simply recode all values greater than 1 to 1, like this.

temp <- table(mydf)
temp[temp > 1] <- 1

请注意，这将返回table.如果要返回data.frame，请使用as.data.frame.matrix:

Note that this returns a table. If you want a data.frame to be returned, use as.data.frame.matrix:

> as.data.frame.matrix(table(mydf))
            Jessica Joe John Mary Ted
ConferenceA       0   1    1    1   0
ConferenceB       0   0    1    0   1
ConferenceC       1   0    0    0   0

---

在上面，"mydf"定义为:

---

In the above, "mydf" is defined as:

mydf <- structure(list(Event = c("ConferenceA", "ConferenceA", 
  "ConferenceA", "ConferenceB", "ConferenceB", "ConferenceC"), 
  Participant = c("John", "Joe", "Mary", "John", "Ted", "Jessica")), 
  .Names = c("Event", "Participant"), class = "data.frame", 
  row.names = c(NA, -6L))

请以后以类似方式共享您的数据.

Please share your data in a similar manner in the future.

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