查找组中两个变量之间的共现 [英] Finding cooccurences between two variables within a group
问题描述
鉴于我的数据框如下所示：
df = data .frame（group = c（1,1,1,2,2,2），var1 = c（1,2,4,2,2,4），var2 = c（4,1,2,1,3 ，2））
> df
组var1 var2
1 1 1 4
2 1 2 1
3 1 4 2
4 2 2 1
5 2 2 3
6 2 4 2
我希望将其转化为新的共现矩阵，其中行代表var1，列代表var2。
编辑：对于那些不熟悉共现的人，我对一组中同时出现的价值对感兴趣。例如， 2和 1的组合在组1中发生一次，而在组2中其他时间发生，因此意味着出现2次共现。在我的示例中，我将组合彼此相邻，但是它们可能会出现在组内的任何地方。
它应如下所示：
> cooc
1 2 3 4
1 0 2 0 1
2 2 0 1 2
3 0 1 0 0
4 1 2 0 0
在使用xtabs函数仅使用组中的一个变量处理同现时，我已经这样做过确保如何将其应用于多个列。例如，如果我有兴趣查找不同组中var1的共存，则可以执行以下操作：
> td = xtabs（〜group + var1，data = df）
> cooc = crossprod（td，td）
> diag（cooc）= 0
如果我了解您问题正确，我相信这应该可行：
＃我只在这里使用data.table，以防万一我们需要这样做 group
＃，但在此解决方案中我不使用它，因为我没有看到分组
### library（data.table）
###的意义
＃ df<-data.table（df）
＃这将创建一对值 a_b
df $ ID<-paste（df $ var1，df $ var2，sep = _）
＃我们枚举所有唯一值，这样我们就可以创建
＃映射以稍后匹配数据并映射
uniqval<-sort（unique（c（df $ var1，df $ var2）））
grid<-expand.grid（uniqval，uniqval）
grid $ ID<-paste（grid $ Var1，grid $ Var2，sep = _）
＃将我们的数据与该地图匹配
匹配<-sort（match（df $ ID，grid $ ID））
＃将结果汇总到数据框
标签中< -data.frame（table（grid $ ID [matches]））
＃将ID拆分回值
tab $ Var2<-s ubstr（tab $ Var1,3,3）
tab $ Var1<-substr（tab $ Var1,1,1）
＃创建空结果矩阵
cooc<-matrix（ 0，nrow = length（uniqval），ncol = length（uniqval））
行名（cooc）<-uniqval
colnames（cooc）<-uniqval
＃还有其他方法可以做到这一点
＃但对我来说这似乎很简单
＃我们只需要将列表结果
＃替换到矩阵
中的所需位置＃即 a_b频率进入[a，b]和[b，a]位置
for（m in 1：nrow（tab））{
i<-tab $ Var1 [m]
j<-tab $ Var2 [m]
＃通过将其添加到先前的值
＃中，我们得出的是 a_b当量。到 b_a
cooc [i，j] <-cooc [i，j] + tab $ Freq [m]
cooc [j，i] <-cooc [i，j]
}
I am hoping to efficiently compute a co-occurence matrix by finding the co-occurences between two different variables within a group, ideally without using a complex loop that iterates through all possible combinations.
Given that my dataframe looks as follows:
df = data.frame(group = c(1,1,1,2,2,2),var1 = c(1,2,4,2,2,4),var2 = c(4,1,2,1,3,2))
> df
group var1 var2
1 1 1 4
2 1 2 1
3 1 4 2
4 2 2 1
5 2 2 3
6 2 4 2
I am hoping to turn this into a new co-occurence matrix, where the rows represent var1 and columns var2.
EDIT: For those unfamiliar with co-occurences, I am interested in pairs of values that occur simultaneously in a group. For example, the combination of "2" and "1" happens once in group 1, and other time in group 2, thus implying 2 co-occurences. In my example, I put the combination next two each other, but they could occur anywhere within the group.
It should look like the following:
> cooc
1 2 3 4
1 0 2 0 1
2 2 0 1 2
3 0 1 0 0
4 1 2 0 0
I have done this before when dealing with co-occurences using just one variable within a group by using the xtabs function, but not sure how to apply it to multiple columns. For example, if I was interested in finding the co-occurences for var1 within the different groups, I would do the following:
> td = xtabs(~group + var1,data = df)
> cooc = crossprod(td,td)
> diag(cooc) = 0
if i am understanding your question correctly, I believe this should work:
# i only use data.table here in case we need to do this "by group"
# but in this solution I do not use it as i did not see the significance
# of grouping
###library(data.table)
###df <- data.table(df)
# this creates the pair of values "a_b"
df$ID <- paste(df$var1,df$var2,sep="_")
# we enumerate all the unique values that way we can create
# a map to later match the data and map
uniqval <- sort(unique(c(df$var1,df$var2)))
grid <- expand.grid(uniqval,uniqval)
grid$ID <- paste(grid$Var1,grid$Var2,sep="_")
# match our data to this map
matches <- sort(match(df$ID,grid$ID))
# tabulate our results into a dataframe
tab <- data.frame(table(grid$ID[matches]))
# split up our ID back into values
tab$Var2 <- substr(tab$Var1,3,3)
tab$Var1 <- substr(tab$Var1,1,1)
# create our empty result matrix
cooc <- matrix(0,nrow=length(uniqval),ncol=length(uniqval))
rownames(cooc) <- uniqval
colnames(cooc) <- uniqval
# there are other ways to do this
# but this seemed simple enough of a loop for me
# we just need to replace the tabulation results
# into our desired location in the matrix
# namely, "a_b" frequencies into [a,b] and [b,a] positions
for(m in 1:nrow(tab)){
i <- tab$Var1[m]
j <- tab$Var2[m]
# by adding this to the previous value
# we are accounting for "a_b" equiv. to "b_a"
cooc[i,j] <- cooc[i,j]+tab$Freq[m]
cooc[j,i] <- cooc[i,j]
}
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