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csv - * txt 출력 파일에서 R로 데이터 추출

R에서 수행하는 분석의 결과 인 output.txt 파일이 있습니다. 추출하고 싶습니다 :

  • 와이즈 비즈  각 주제에 대한 .txt 파일의 테이블을 R 데이터 프레임으로 결합합니다. 출력 항목 이름은 각 주제마다 일치합니다.
  • 와이즈 위즈도 마찬가지  R의 데이터 프레임으로 결합하십시오.

알다시피, 출력 파일은 필요없는 사이에 텍스트를 썼습니다.

output.txt 파일의 구조를 쉽게 볼 수 있도록 다음 링크 여기 . 또한 출력이 어떻게 구성되어 있는지 보여주기 위해 아래 스크린 샷을 넣습니다.

다음과 같은 것을 사용하여이 작업을 시도했지만 운이 없습니다 :

<< Output >>

<< Predicted Output >>
rcsvdataframereadr
  • 답변 # 1

    시작해보십시오. 필요한 경우 더 많은 조건을 추가하십시오. 도움이 되길 바랍니다. 궁금한 점이 있으면 언제든지 문의하십시오.

    b = readLines(file('ivivc_outputs.txt', 'r'))
n_out = 1
n_pred = 1
listOutput = list()
listPredictOutput = list()   
for(i in 1:length(b)){
    if(b[i] == "<< Output >>"){
        a = strsplit(b[i+1], " ")[[1]]
        a = a[a != ""]
        #         print(a)
        df <- data.frame(matrix(ncol = length(a), nrow = 0))
        colnames(df) = a       
        control = 2
        while(control != 20){
            l = strsplit(b[i+control], " ")[[1]]
            l = l[l != ""]
            df[control-1,] = l
            control = control + 1 
        }
        listOutput[[n_out]] = df
        n_out = n_out+1
    }
    if(b[i] == "<< Predicted Output >>"){
        a = strsplit(b[i+1], " ")[[1]]
        a = a[a != ""]
        #         print(a)
        df <- data.frame(matrix(ncol = length(a), nrow = 0))
        colnames(df) = a       
        control = 2
        while(control != 20){
            l = strsplit(b[i+control], " ")[[1]]
            l = l[l != ""]
            df[control-1,] = l
            control = control + 1 
        }
        listPredictOutput[[n_pred]] = df
        n_pred = n_pred+1
    }
}


# to merge all data frames use `bind_rows` from `dplyr`
library(dplyr)
dfOutput = bind_rows(listOutput)
dfPredictOutput = bind_rows(listPredictOutput)

  >   dfPredictOutput
    #      pH subj       formula. time    FABpred conc.pred     AUCpred
    # 1   1.2    1        capsule  0.0   0.000000   0.00000     0.00000
    # 2   1.2    1        capsule  1.0   2.528737   8.39300     4.19650
    # 3   1.2    1        capsule  2.0   7.415708  22.57987    19.68293
    # 4   1.2    1        capsule  3.0  15.845734  45.08950    53.51761
    # 5   1.2    1        capsule  4.0  24.275759  62.14611   107.13542
    # 6   1.2    1        capsule  5.0  33.133394  76.48998   176.45346
    # 7   1.2    1        capsule  6.0  41.991029  87.35901   258.37796
    # 8   1.2    1        capsule  6.5  45.900606  89.90799   302.69471
    # 9   1.2    1        capsule  7.0  49.810183  92.12832   348.20378
    # 10  1.2    1        capsule  7.5  53.719760  94.06237   394.75146
    # 11  1.2    1        capsule  8.0  57.629337  95.74705   442.20381
    # 12  1.2    1        capsule  8.0  57.629337  95.74705   442.20381
    # 13  1.2    1        capsule  9.0  63.860225  93.23271   536.69369
    # 14  1.2    1        capsule 10.0  70.091113  91.32747   628.97378
    # 15  1.2    1        capsule 12.0  79.498532  79.70975   800.01101
    # 16  1.2    1        capsule 16.0  90.372043  49.52751  1058.48553
    # 17  1.2    1        capsule 20.0 101.245554  40.79704  1239.13462
    # 18  1.2    1        capsule 24.0 107.354268  26.67212  1374.07293
    # 19  1.2    1 capsuleContent  0.0   0.000000  0.000000    0.000000
    # 20  1.2    1 capsuleContent  1.0   1.490256  4.946231    2.473115
    # 21  1.2    1 capsuleContent  2.0   5.338746 16.521316   13.206889
    # 22  1.2    1 capsuleContent  3.0  13.341161 39.079386   41.007240
    # 23  1.2    1 capsuleContent  4.0  21.343576 56.172708   88.633287
    # 24  1.2    1 capsuleContent  5.0  30.017950 71.355393  152.397337
    # 25  1.2    1 capsuleContent  6.0  38.692324 82.860036  229.505052
    # 26  1.2    1 capsuleContent  6.5  42.571357 85.881180  271.690356
    # 27  1.2    1 capsuleContent  7.0  46.450390 88.512793  315.288850
    # 28  1.2    1 capsuleContent  7.5  50.329423 90.805099  360.118323
    # 29  1.2    1 capsuleContent  8.0  54.208457 92.801847  406.020060
    # 30  1.2    1 capsuleContent  8.0  54.208457 92.801847  406.020060
    # 31  1.2    1 capsuleContent  9.0  60.439345 91.000989  497.921478
    # 32  1.2    1 capsuleContent 10.0  66.670233 89.636393  588.240168
    # 33  1.2    1 capsuleContent 12.0  76.322001 79.472871  757.349432
    # 34  1.2    1 capsuleContent 16.0  87.256599 49.607701 1015.510577
    # 35  1.2    1 capsuleContent 20.0  98.191197 40.968947 1196.663873
    # 36  1.2    1 capsuleContent 24.0 104.177736 26.424419 1331.450604
    # 37  1.2    2        capsule  0.0   0.000000   0.00000     0.00000
    # 38  1.2    2        capsule  1.0   2.528737   8.39300     4.19650
    # 39  1.2    2        capsule  2.0   7.415708  22.57987    19.68293
    # 40  1.2    2        capsule  3.0  15.845734  45.08950    53.51761
    # 41  1.2    2        capsule  4.0  24.275759  62.14611   107.13542
    # 42  1.2    2        capsule  5.0  33.133394  76.48998   176.45346
    # 43  1.2    2        capsule  6.0  41.991029  87.35901   258.37796
    # 44  1.2    2        capsule  6.5  45.900606  89.90799   302.69471
    # 45  1.2    2        capsule  7.0  49.810183  92.12832   348.20378
    # 46  1.2    2        capsule  7.5  53.719760  94.06237   394.75146
    # 47  1.2    2        capsule  8.0  57.629337  95.74705   442.20381
    # 48  1.2    2        capsule  8.0  57.629337  95.74705   442.20381
    # 49  1.2    2        capsule  9.0  63.860225  93.23271   536.69369
    # 50  1.2    2        capsule 10.0  70.091113  91.32747   628.97378
    # 51  1.2    2        capsule 12.0  79.498532  79.70975   800.01101
    # 52  1.2    2        capsule 16.0  90.372043  49.52751  1058.48553
    # 53  1.2    2        capsule 20.0 101.245554  40.79704  1239.13462
    # 54  1.2    2        capsule 24.0 107.354268  26.67212  1374.07293
    # 55  1.2    2 capsuleContent  0.0   0.000000  0.000000    0.000000
    # 56  1.2    2 capsuleContent  1.0   1.490256  4.946231    2.473115
    # 57  1.2    2 capsuleContent  2.0   5.338746 16.521316   13.206889
    # 58  1.2    2 capsuleContent  3.0  13.341161 39.079386   41.007240
    # 59  1.2    2 capsuleContent  4.0  21.343576 56.172708   88.633287
    # 60  1.2    2 capsuleContent  5.0  30.017950 71.355393  152.397337
    # 61  1.2    2 capsuleContent  6.0  38.692324 82.860036  229.505052
    # 62  1.2    2 capsuleContent  6.5  42.571357 85.881180  271.690356
    # 63  1.2    2 capsuleContent  7.0  46.450390 88.512793  315.288850
    # 64  1.2    2 capsuleContent  7.5  50.329423 90.805099  360.118323
    # 65  1.2    2 capsuleContent  8.0  54.208457 92.801847  406.020060
    # 66  1.2    2 capsuleContent  8.0  54.208457 92.801847  406.020060
    # 67  1.2    2 capsuleContent  9.0  60.439345 91.000989  497.921478
    # 68  1.2    2 capsuleContent 10.0  66.670233 89.636393  588.240168
    # 69  1.2    2 capsuleContent 12.0  76.322001 79.472871  757.349432
    # 70  1.2    2 capsuleContent 16.0  87.256599 49.607701 1015.510577
    # 71  1.2    2 capsuleContent 20.0  98.191197 40.968947 1196.663873
    # 72  1.2    2 capsuleContent 24.0 104.177736 26.424419 1331.450604
    # 73  1.2    3        capsule  0.0   0.000000   0.00000     0.00000
    # 74  1.2    3        capsule  1.0   2.528737   8.39300     4.19650
    # 75  1.2    3        capsule  2.0   7.415708  22.57987    19.68293
    # 76  1.2    3        capsule  3.0  15.845734  45.08950    53.51761
    # 77  1.2    3        capsule  4.0  24.275759  62.14611   107.13542
    # 78  1.2    3        capsule  5.0  33.133394  76.48998   176.45346
    # 79  1.2    3        capsule  6.0  41.991029  87.35901   258.37796
    # 80  1.2    3        capsule  6.5  45.900606  89.90799   302.69471
    # 81  1.2    3        capsule  7.0  49.810183  92.12832   348.20378
    # 82  1.2    3        capsule  7.5  53.719760  94.06237   394.75146
    # 83  1.2    3        capsule  8.0  57.629337  95.74705   442.20381
    # 84  1.2    3        capsule  8.0  57.629337  95.74705   442.20381
    # 85  1.2    3        capsule  9.0  63.860225  93.23271   536.69369
    # 86  1.2    3        capsule 10.0  70.091113  91.32747   628.97378
    # 87  1.2    3        capsule 12.0  79.498532  79.70975   800.01101
    # 88  1.2    3        capsule 16.0  90.372043  49.52751  1058.48553
    # 89  1.2    3        capsule 20.0 101.245554  40.79704  1239.13462
    # 90  1.2    3        capsule 24.0 107.354268  26.67212  1374.07293
    # 91  1.2    3 capsuleContent  0.0   0.000000  0.000000    0.000000
    # 92  1.2    3 capsuleContent  1.0   1.490256  4.946231    2.473115
    # 93  1.2    3 capsuleContent  2.0   5.338746 16.521316   13.206889
    # 94  1.2    3 capsuleContent  3.0  13.341161 39.079386   41.007240
    # 95  1.2    3 capsuleContent  4.0  21.343576 56.172708   88.633287
    # 96  1.2    3 capsuleContent  5.0  30.017950 71.355393  152.397337
    # 97  1.2    3 capsuleContent  6.0  38.692324 82.860036  229.505052
    # 98  1.2    3 capsuleContent  6.5  42.571357 85.881180  271.690356
    # 99  1.2    3 capsuleContent  7.0  46.450390 88.512793  315.288850
    # 100 1.2    3 capsuleContent  7.5  50.329423 90.805099  360.118323
    # 101 1.2    3 capsuleContent  8.0  54.208457 92.801847  406.020060
    # 102 1.2    3 capsuleContent  8.0  54.208457 92.801847  406.020060
    # 103 1.2    3 capsuleContent  9.0  60.439345 91.000989  497.921478
    # 104 1.2    3 capsuleContent 10.0  66.670233 89.636393  588.240168
    # 105 1.2    3 capsuleContent 12.0  76.322001 79.472871  757.349432
    # 106 1.2    3 capsuleContent 16.0  87.256599 49.607701 1015.510577
    # 107 1.2    3 capsuleContent 20.0  98.191197 40.968947 1196.663873
    # 108 1.2    3 capsuleContent 24.0 104.177736 26.424419 1331.450604

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