我有一个巨大的数据集,我需要根据一些标准来匹配样本。例如,每一位电影明星在一个地方和自治区找到我两个人(随机)谁不是电影明星。电影明星是1,非电影明星是0.
location<- c('manhattan', 'manhattan' ,'manhattan', 'manhattan', 'manhattan', 'manhattan')
moviestar<- c(0,1,0,0,0,1)
id<- c(1,2,3,4,5,6)
borough <- c('williamsburg', 'williamsburg', 'williamsburg', 'williamsburg', 'williamsburg','williamsburg')
df<- data.frame(location,moviestar, borough, id)我想要创建一个子集,其中有一对电影明星和另外两个非电影明星(随机挑选)居住在同一地点和行政区。有什么建议吗?基本上有6个人住在曼哈顿,曼哈顿住着两颗恒星,我想匹配每颗恒星,在这种情况下,2和6是恒星,那么我想在最终数据中找到匹配对,如下(一些随机配对):
我期待的输出是这样的,
matcheddata
location moviestar borough id matchpairid
manhattan 1 williamsburg 2 match1
manhattan 0 williamsburg 1 match1
manhttan 0 williamsburg 5 match1
manhattan 1 williamsburg 6 match2
manhattan 0 williamsburg 3 match2
manhttan 0 williamsburg 5 match2发布于 2017-10-29 23:50:07
下面是另一种直接产生预期结果的方法,在每一行电影明星后面跟着两行随机挑选的非电影明星:
library(data.table)
setDT(df)[, {
n_stars <- .SD[moviestar == 1, .N]
rbind(.SD[moviestar == 1], .SD[moviestar == 0][sample.int(.N, 2L * n_stars)])[
, pairid := rep(1:n_stars, 3L)][order(pairid)]
}, by = .(location, borough)]location borough moviestar id pairid 1: manhattan williamsburg 1 2 1 2: manhattan williamsburg 0 3 1 3: manhattan williamsburg 0 1 1 4: manhattan williamsburg 1 6 2 5: manhattan williamsburg 0 4 2 6: manhattan williamsburg 0 5 2
发布于 2017-10-27 16:05:42
这应该可以做到:
library(data.table)
setDT(df)[, .(moviestar.id = id[moviestar == 1],
match.id = sample(id[moviestar == 0], 2*sum(moviestar == 1)))
, by = .(location, borough)]
# location borough moviestar.id match.id
#1: manhattan williamsburg 2 3
#2: manhattan williamsburg 6 5
#3: manhattan williamsburg 2 1
#4: manhattan williamsburg 6 4之后你可以用你喜欢的任何形式按摩它。
https://stackoverflow.com/questions/46979060
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