Take randomly sample based on groups

前端 未结 8 641
说谎
说谎 2020-11-28 13:23

I have a df made by almost 50,000 rows spread in 15 different IDs (every ID has thousands of observations). df looks like:

        ID  Year    Temp    ph
1           


        
相关标签:
8条回答
  • 2020-11-28 14:12
    mydata1 is your original data(not tested)
    
    mydata2<- split(mydata1,mydata1$ID)
    names(mydata2)<-paste0("mydata2",1:length(levels(ID))) 
    mysample<-Map(function(x) x[sample((1:nrow(x)),size=500,replace=FALSE),], mydata2)
    
    library(plyr)# for rbinding the mysample
    ldply(mysample)
    
    0 讨论(0)
  • 2020-11-28 14:14

    Here is one approach in base R.

    First, the prerequisite sample data to work with:

    set.seed(1)
    mydf <- data.frame(ID = rep(1:3, each = 5), matrix(rnorm(45), ncol = 3))
    mydf
    #    ID         X1          X2          X3
    # 1   1 -0.6264538 -0.04493361  1.35867955
    # 2   1  0.1836433 -0.01619026 -0.10278773
    # 3   1 -0.8356286  0.94383621  0.38767161
    # 4   1  1.5952808  0.82122120 -0.05380504
    # 5   1  0.3295078  0.59390132 -1.37705956
    # 6   2 -0.8204684  0.91897737 -0.41499456
    # 7   2  0.4874291  0.78213630 -0.39428995
    # 8   2  0.7383247  0.07456498 -0.05931340
    # 9   2  0.5757814 -1.98935170  1.10002537
    # 10  2 -0.3053884  0.61982575  0.76317575
    # 11  3  1.5117812 -0.05612874 -0.16452360
    # 12  3  0.3898432 -0.15579551 -0.25336168
    # 13  3 -0.6212406 -1.47075238  0.69696338
    # 14  3 -2.2146999 -0.47815006  0.55666320
    # 15  3  1.1249309  0.41794156 -0.68875569
    

    Second, the sampling:

    do.call(rbind, 
            lapply(split(mydf, mydf$ID), 
                   function(x) x[sample(nrow(x), 3), ]))
    #      ID         X1          X2         X3
    # 1.2   1  0.1836433 -0.01619026 -0.1027877
    # 1.1   1 -0.6264538 -0.04493361  1.3586796
    # 1.5   1  0.3295078  0.59390132 -1.3770596
    # 2.10  2 -0.3053884  0.61982575  0.7631757
    # 2.9   2  0.5757814 -1.98935170  1.1000254
    # 2.8   2  0.7383247  0.07456498 -0.0593134
    # 3.13  3 -0.6212406 -1.47075238  0.6969634
    # 3.12  3  0.3898432 -0.15579551 -0.2533617
    # 3.15  3  1.1249309  0.41794156 -0.6887557
    

    There is also strata from the sampling package, which is convenient when you want to sample different sizes from each group:

    # install.packages("sampling")
    library(sampling)
    set.seed(1)
    x <- strata(mydf, "ID", size = c(2, 3, 2), method = "srswor")
    getdata(mydf, x)
    #            X1          X2         X3 ID ID_unit Prob Stratum
    # 2   0.1836433 -0.01619026 -0.1027877  1       2  0.4       1
    # 5   0.3295078  0.59390132 -1.3770596  1       5  0.4       1
    # 6  -0.8204684  0.91897737 -0.4149946  2       6  0.6       2
    # 8   0.7383247  0.07456498 -0.0593134  2       8  0.6       2
    # 9   0.5757814 -1.98935170  1.1000254  2       9  0.6       2
    # 14 -2.2146999 -0.47815006  0.5566632  3      14  0.4       3
    # 15  1.1249309  0.41794156 -0.6887557  3      15  0.4       3
    
    0 讨论(0)
提交回复
热议问题