60520
タイトルの通りです。  
tsvファイルをpythonで読み込み、MeCabで分かち書きをしたのちにkmeans法でクラスタリングをすることには成功しています。  
このクラスタリングによって得られた結果から、特定のクラスターの文章データを呼び出したいのですがうまくいきません。  
当方、プログラミング初心者なためもしかしたら筋違いな質問かも知れませんが、どなたかご教授いただけると幸いです。

**使用環境  
jupyter notebook  
windows10**

ここから成功した部分

```

    from gensim.models.doc2vec import Doc2Vec
    from gensim.models.doc2vec import TaggedDocument
    
    import MeCab
    import csv
    
    mt = MeCab.Tagger()
    
    reports = []
    with open("インプットファイル",mode='r',encoding='utf-8') as f:
        # インプットファイルには一行に文章ID,文章がtab区切りで保存されている
        reader = csv.reader(f, delimiter="\t")
        for report_id, report in reader:
            words = []
            node = mt.parseToNode(report)
            while node:
                if len(node.surface) > 0:
                    words.append(node.surface)
                node = node.next
            stopword = ['あれ','それ','これ']
            words2 = [token for token in words if token not in stopword]
            # wordsが文章の単語のリスト,tagsには文章IDを指定
            reports.append(TaggedDocument(words=words2, tags=[report_id]))
            print(words2)
    
```

```

    model = Doc2Vec(documents=reports, size=128, window=8, min_count=2, workers=8)
    model.save("allcomment_stop_doc2vec.model")
    
```

```

    m = Doc2Vec.load("allcomment_stop_doc2vec.model")
    
```

```

    from gensim.models.doc2vec import Doc2Vec
    from gensim.models.doc2vec import TaggedDocument
    from sklearn.cluster import KMeans
    import sys
    from collections import defaultdict
    import numpy as np
    import matplotlib.pyplot as plt
    
    
    #ベクトルをリストに格納
    vectors_list=[m.docvecs[n] for n in range(len(m.docvecs))]
    
    #ドキュメント番号のリスト
    doc_nums=range(1,1+len(m.docvecs))
    
    #クラスタリング設定
    n_clusters = 6
    kmeans_model = KMeans(n_clusters=n_clusters, verbose=1, random_state=1, n_jobs=-1)
    
    #クラスタリング実行
    kmeans_model.fit(vectors_list)
    
    #クラスタリングデータにラベル付け
    labels=kmeans_model.labels_
    
    #ラベルとドキュメント番号の辞書づくり
    cluster_to_docs = defaultdict(list)
    for cluster_id, doc_num in zip(labels, doc_nums):
        cluster_to_docs[cluster_id].append(doc_num)
    
    #クラスター出力
    
    for docs in cluster_to_docs.values():
        print(docs)
    
    
```

上記の出力結果(数値はtsvファイルに書かれている文章idに対応したものです)

```

    [1, 6, 7, 9, 10, 17, 25, 35, 47, 104, 129, 131, 147, 150, 151, 152, 154, 155, 156, 157, 160, 162, 163, 164, 166, 168, 170, 171, 172, 174, 176, 177, 178, 180, 183, 191, 194, 199, 210, 219, 222, 233, 239, 240, 242, 253, 255, 256, 257, 268, 269, 272, 275, 294, 301, 303, 307, 311, 312, 314, 315, 320, 321, 322, 324, 330, 340, 347, 355, 357, 368, 369, 371, 373, 374, 376, 378, 380, 381, 385, 387, 405, 407, 409, 414, 417, 418, 419, 421, 427, 431, 432, 433, 436, 439, 442, 443, 444, 445, 446, 447, 448, 455, 458, 459, 460, 463, 465, 466, 468, 471, 490, 493, 500, 507, 536, 552, 565, 566, 568, 573, 575, 577, 579, 581, 583, 596, 604, 611, 612, 618, 619, 625, 630, 634, 640, 644, 646, 648, 649, 654, 655, 663, 667, 668, 670, 675, 681, 682, 684, 685, 687, 695, 696, 697, 698, 702, 703, 708, 710, 711, 736, 755, 762, 763, 766, 771, 779, 791, 799, 807, 810, 813, 814, 817, 824, 829, 842, 843, 847, 856, 860, 870, 879, 889, 894, 895, 897, 904, 911, 919, 920, 922, 924, 925, 926, 927, 928, 930, 931, 932, 933, 934, 936, 937, 949, 951, 952, 956, 957, 958, 959, 962, 963, 965, 968, 979, 985, 989, 996, 997, 999]
    [2, 11, 21, 22, 23, 26, 27, 30, 34, 36, 38, 43, 45, 50, 51, 52, 53, 54, 55, 57, 58, 60, 61, 63, 64, 65, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 105, 106, 107, 108, 109, 110, 111, 113, 114, 116, 121, 123, 124, 126, 127, 128, 130, 132, 134, 137, 138, 139, 140, 141, 142, 143, 144, 145, 153, 159, 167, 193, 200, 201, 204, 205, 206, 209, 211, 212, 214, 215, 217, 218, 224, 225, 234, 235, 238, 241, 243, 249, 250, 251, 254, 258, 259, 264, 266, 270, 271, 276, 277, 278, 279, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 345, 346, 349, 350, 353, 359, 360, 363, 364, 365, 366, 367, 370, 372, 377, 379, 423, 424, 425, 449, 451, 452, 453, 454, 469, 475, 477, 479, 481, 483, 486, 494, 502, 506, 510, 511, 513, 514, 516, 523, 526, 527, 528, 530, 531, 532, 533, 537, 541, 544, 547, 548, 551, 555, 558, 559, 560, 561, 562, 584, 585, 586, 588, 590, 591, 593, 594, 595, 598, 600, 601, 605, 606, 617, 636, 645, 669, 689, 705, 706, 712, 714, 715, 716, 721, 722, 723, 724, 725, 726, 727, 728, 729, 731, 732, 733, 734, 738, 739, 741, 742, 744, 745, 747, 749, 751, 752, 754, 758, 760, 761, 764, 765, 767, 768, 769, 770, 773, 774, 775, 776, 781, 783, 785, 787, 789, 790, 794, 796, 802, 803, 812, 815, 816, 819, 825, 832, 848, 853, 855, 857, 861, 862, 864, 865, 866, 869, 871, 872, 873, 876, 888, 898, 899, 900, 905, 906, 907, 909, 915, 917, 938, 940, 943, 948, 964, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1010, 1011, 1012, 1013, 1015, 1016, 1017, 1018, 1020, 1022, 1023, 1025, 1026, 1028, 1030, 1033, 1034, 1035]
    [3, 4, 5, 8, 12, 13, 14, 18, 19, 20, 24, 28, 29, 31, 32, 33, 37, 39, 40, 41, 42, 44, 46, 48, 49, 56, 59, 62, 66, 93, 112, 115, 117, 118, 119, 120, 122, 125, 133, 135, 136, 146, 149, 158, 161, 165, 173, 179, 185, 202, 203, 207, 208, 213, 216, 220, 221, 223, 226, 227, 228, 229, 230, 231, 232, 236, 237, 244, 245, 246, 247, 248, 252, 261, 262, 263, 265, 267, 273, 274, 280, 342, 343, 344, 348, 351, 352, 356, 358, 361, 362, 382, 384, 386, 388, 404, 406, 408, 410, 411, 412, 413, 415, 416, 420, 422, 426, 428, 429, 434, 435, 437, 438, 450, 456, 462, 464, 467, 472, 473, 474, 476, 478, 480, 482, 484, 485, 487, 488, 489, 491, 492, 495, 496, 497, 498, 499, 501, 503, 504, 505, 508, 509, 512, 515, 517, 518, 519, 520, 521, 522, 524, 525, 529, 534, 535, 538, 539, 540, 542, 545, 546, 549, 550, 553, 554, 556, 557, 563, 564, 569, 578, 582, 587, 589, 592, 597, 599, 602, 607, 613, 614, 616, 624, 651, 657, 658, 660, 661, 662, 671, 672, 674, 678, 686, 688, 694, 699, 707, 713, 717, 718, 719, 720, 730, 735, 737, 740, 743, 746, 748, 750, 753, 756, 757, 759, 772, 777, 778, 780, 782, 784, 786, 788, 792, 793, 795, 797, 798, 800, 801, 804, 805, 806, 808, 809, 811, 818, 823, 826, 827, 828, 830, 831, 833, 834, 835, 836, 837, 838, 839, 840, 841, 844, 845, 846, 849, 850, 851, 852, 854, 858, 859, 863, 867, 868, 874, 875, 877, 878, 880, 881, 882, 883, 884, 885, 886, 887, 890, 891, 892, 893, 896, 901, 902, 903, 908, 910, 912, 913, 914, 916, 941, 942, 944, 946, 947, 950, 953, 954, 960, 961, 966, 967, 994, 995, 1009, 1014, 1019, 1021, 1024, 1027, 1029, 1031, 1032, 1036, 1037]
    [15, 16, 148, 169, 175, 181, 182, 184, 186, 187, 188, 189, 190, 192, 195, 196, 197, 198, 260, 292, 295, 296, 297, 299, 300, 304, 306, 309, 310, 313, 316, 317, 327, 332, 337, 338, 339, 354, 375, 383, 389, 400, 430, 440, 441, 457, 461, 470, 567, 570, 574, 580, 603, 609, 610, 615, 620, 622, 623, 626, 627, 628, 629, 631, 632, 633, 635, 638, 647, 650, 652, 653, 656, 659, 673, 676, 677, 679, 680, 690, 691, 693, 700, 709, 918, 921, 923, 929, 935, 939, 945, 955, 969, 971, 972, 973, 974, 975, 976, 977, 978, 980, 981, 982, 983, 984, 986, 987, 988, 990, 991, 992, 993, 998]
    [293, 298, 302, 305, 308, 318, 319, 323, 325, 326, 328, 329, 331, 333, 334, 335, 341, 390, 391, 395, 396, 397, 398, 399, 401, 402, 403, 543, 571, 572, 576, 608, 621, 637, 639, 641, 642, 643, 692, 701, 704, 820, 821, 822, 970]
    [336, 392, 393, 394, 664, 665, 666, 683]
    [222, 331, 317, 114, 45, 8] range(0, 6) 194, 199, 210, 219, 222, 233, 239, 240, 242, 253, 255, 256, 257, 268, 269, 272, 275, 294, 301, 303, 307, 311, 312, 314, 315, 320, 321, 322, 324, 330, 340, 347, 355, 357, 368, 369, 371, 373, 374, 376, 378, 380, 381, 385, 387, 405, 407, 409, 414, 417, 418, 419, 421, 427, 431, 432, 433, 436, 439, 442, 443, 444, 445, 446, 447, 448, 455, 458, 459, 460, 463, 465, 466, 468, 471, 490, 493, 500, 507, 536, 552, 565, 566, 568, 573, 575, 577, 579, 581, 583, 596, 604, 611, 612, 618, 619, 625, 630, 634, 640, 644, 646, 648, 649, 654, 655, 663, 667, 668, 670, 675, 681, 682, 684, 685, 687, 695, 696, 697, 698, 702, 703, 708, 710, 711, 736, 755, 762, 763, 766, 771, 779, 791, 799, 807, 810, 813, 814, 817, 824, 829, 842, 843, 847, 856, 860, 870, 879, 889, 894, 895, 897, 904, 911, 919, 920, 922, 924, 925, 926, 927, 928, 930, 931, 932, 933, 934, 936, 937, 949, 951, 952, 956, 957, 958, 959, 962, 963, 965, 968, 979, 985, 989, 996, 997, 999]
    [2, 11, 21, 22, 23, 26, 27, 30, 34, 36, 38, 43, 45, 50, 51, 52, 53, 54, 55, 57, 58, 60, 61, 63, 64, 65, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 105, 106, 107, 108, 109, 110, 111, 113, 114, 116, 121, 123, 124, 126, 127, 128, 130, 132, 134, 137, 138, 139, 140, 141, 142, 143, 144, 145, 153, 159, 167, 193, 200, 201, 204, 205, 206, 209, 211, 212, 214, 215, 217, 218, 224, 225, 234, 235, 238, 241, 243, 249, 250, 251, 254, 258, 259, 264, 266, 270, 271, 276, 277, 278, 279, 281, 282, 283, 284, 285, 286, 287, 288, 289, 290, 291, 345, 346, 349, 350, 353, 359, 360, 363, 364, 365, 366, 367, 370, 372, 377, 379, 423, 424, 425, 449, 451, 452, 453, 454, 469, 475, 477, 479, 481, 483, 486, 494, 502, 506, 510, 511, 513, 514, 516, 523, 526, 527, 528, 530, 531, 532, 533, 537, 541, 544, 547, 548, 551, 555, 558, 559, 560, 561, 562, 584, 585, 586, 588, 590, 591, 593, 594, 595, 598, 600, 601, 605, 606, 617, 636, 645, 669, 689, 705, 706, 712, 714, 715, 716, 721, 722, 723, 724, 725, 726, 727, 728, 729, 731, 732, 733, 734, 738, 739, 741, 742, 744, 745, 747, 749, 751, 752, 754, 758, 760, 761, 764, 765, 767, 768, 769, 770, 773, 774, 775, 776, 781, 783, 785, 787, 789, 790, 794, 796, 802, 803, 812, 815, 816, 819, 825, 832, 848, 853, 855, 857, 861, 862, 864, 865, 866, 869, 871, 872, 873, 876, 888, 898, 899, 900, 905, 906, 907, 909, 915, 917, 938, 940, 943, 948, 964, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1010, 1011, 1012, 1013, 1015, 1016, 1017, 1018, 1020, 1022, 1023, 1025, 1026, 1028, 1030, 1033, 1034, 1035]
    [3, 4, 5, 8, 12, 13, 14, 18, 19, 20, 24, 28, 29, 31, 32, 33, 37, 39, 40, 41, 42, 44, 46, 48, 49, 56, 59, 62, 66, 93, 112, 115, 117, 118, 119, 120, 122, 125, 133, 135, 136, 146, 149, 158, 161, 165, 173, 179, 185, 202, 203, 207, 208, 213, 216, 220, 221, 223, 226, 227, 228, 229, 230, 231, 232, 236, 237, 244, 245, 246, 247, 248, 252, 261, 262, 263, 265, 267, 273, 274, 280, 342, 343, 344, 348, 351, 352, 356, 358, 361, 362, 382, 384, 386, 388, 404, 406, 408, 410, 411, 412, 413, 415, 416, 420, 422, 426, 428, 429, 434, 435, 437, 438, 450, 456, 462, 464, 467, 472, 473, 474, 476, 478, 480, 482, 484, 485, 487, 488, 489, 491, 492, 495, 496, 497, 498, 499, 501, 503, 504, 505, 508, 509, 512, 515, 517, 518, 519, 520, 521, 522, 524, 525, 529, 534, 535, 538, 539, 540, 542, 545, 546, 549, 550, 553, 554, 556, 557, 563, 564, 569, 578, 582, 587, 589, 592, 597, 599, 602, 607, 613, 614, 616, 624, 651, 657, 658, 660, 661, 662, 671, 672, 674, 678, 686, 688, 694, 699, 707, 713, 717, 718, 719, 720, 730, 735, 737, 740, 743, 746, 748, 750, 753, 756, 757, 759, 772, 777, 778, 780, 782, 784, 786, 788, 792, 793, 795, 797, 798, 800, 801, 804, 805, 806, 808, 809, 811, 818, 823, 826, 827, 828, 830, 831, 833, 834, 835, 836, 837, 838, 839, 840, 841, 844, 845, 846, 849, 850, 851, 852, 854, 858, 859, 863, 867, 868, 874, 875, 877, 878, 880, 881, 882, 883, 884, 885, 886, 887, 890, 891, 892, 893, 896, 901, 902, 903, 908, 910, 912, 913, 914, 916, 941, 942, 944, 946, 947, 950, 953, 954, 960, 961, 966, 967, 994, 995, 1009, 1014, 1019, 1021, 1024, 1027, 1029, 1031, 1032, 1036, 1037]
    [15, 16, 148, 169, 175, 181, 182, 184, 186, 187, 188, 189, 190, 192, 195, 196, 197, 198, 260, 292, 295, 296, 297, 299, 300, 304, 306, 309, 310, 313, 316, 317, 327, 332, 337, 338, 339, 354, 375, 383, 389, 400, 430, 440, 441, 457, 461, 470, 567, 570, 574, 580, 603, 609, 610, 615, 620, 622, 623, 626, 627, 628, 629, 631, 632, 633, 635, 638, 647, 650, 652, 653, 656, 659, 673, 676, 677, 679, 680, 690, 691, 693, 700, 709, 918, 921, 923, 929, 935, 939, 945, 955, 969, 971, 972, 973, 974, 975, 976, 977, 978, 980, 981, 982, 983, 984, 986, 987, 988, 990, 991, 992, 993, 998]
    [293, 298, 302, 305, 308, 318, 319, 323, 325, 326, 328, 329, 331, 333, 334, 335, 341, 390, 391, 395, 396, 397, 398, 399, 401, 402, 403, 543, 571, 572, 576, 608, 621, 637, 639, 641, 642, 643, 692, 701, 704, 820, 821, 822, 970]
    [336, 392, 393, 394, 664, 665, 666, 683]
    [222, 331, 317, 114, 45, 8] 
    
```

ここまでは成功した部分です。  
ここで、最初のクラスタの文章データを呼び出そうと

```

    print(reports[1, 6, 7, 9,~,999])
    
```

とすると

```

    list indices must be integers or slices, not tuple
    
```

となり複数の引数を渡すことができません。  
解決策をどなたかご教授いただけると幸いです。
CC BY-SA 4.0
2019-11-12T06:29:47.037
60445
2019-11-14T11:40:31.417
36375
question
python
kmeansとDoc2vecでクラスタリングした文章データのうち、特定のクラスタを呼び出したい
`print(list(map(reports.__getitem__, (1, 6, 7, 9, 999))))` など。

文章データのみを呼び出すには、TaggedDocument
の構造がよく分かりませんので、確かな事は言えないのですが、`print([reports[i].words for i in (1, 6, 7, 9,
999)])` でしょうか。

\-- この回答は、[metropolis
さん](https://ja.stackoverflow.com/users/16894/metropolis)のコメントを元にコミュニティ wiki
として投稿するものです。
CC BY-SA 4.0
2019-11-14T11:40:31.417
60520
2019-11-14T11:40:31.417
19110
60445
answer