Q&A
ボストン住宅価格データセット（14項目）をCSVにダウンロードしようとしたのですが、なぜか目的変数（13項目）しかダウンロードできす、目的変数(1項目(MEDV：1000ドルでの所有者居住住宅の中央値)がダウンロードできません。
どなたか、お教え頂ければ幸いです。
from sklearn import datasets boston = datasets.load_boston() import pandas as pd boston_df = pd.DataFrame(boston.data, columns=boston.feature_names) boston_df.to_csv('boston.csv')
print(boston_df)
CRIM ZN INDUS CHAS NOX RM AGE DIS RAD TAX \ 0 0.00632 18.0 2.31 0.0 0.538 6.575 65.2 4.0900 1.0 296.0 1 0.02731 0.0 7.07 0.0 0.469 6.421 78.9 4.9671 2.0 242.0 2 0.02729 0.0 7.07 0.0 0.469 7.185 61.1 4.9671 2.0 242.0 3 0.03237 0.0 2.18 0.0 0.458 6.998 45.8 6.0622 3.0 222.0 4 0.06905 0.0 2.18 0.0 0.458 7.147 54.2 6.0622 3.0 222.0 5 0.02985 0.0 2.18 0.0 0.458 6.430 58.7 6.0622 3.0 222.0 6 0.08829 12.5 7.87 0.0 0.524 6.012 66.6 5.5605 5.0 311.0 7 0.14455 12.5 7.87 0.0 0.524 6.172 96.1 5.9505 5.0 311.0 8 0.21124 12.5 7.87 0.0 0.524 5.631 100.0 6.0821 5.0 311.0 9 0.17004 12.5 7.87 0.0 0.524 6.004 85.9 6.5921 5.0 311.0 10 0.22489 12.5 7.87 0.0 0.524 6.377 94.3 6.3467 5.0 311.0 11 0.11747 12.5 7.87 0.0 0.524 6.009 82.9 6.2267 5.0 311.0 12 0.09378 12.5 7.87 0.0 0.524 5.889 39.0 5.4509 5.0 311.0 13 0.62976 0.0 8.14 0.0 0.538 5.949 61.8 4.7075 4.0 307.0 14 0.63796 0.0 8.14 0.0 0.538 6.096 84.5 4.4619 4.0 307.0 15 0.62739 0.0 8.14 0.0 0.538 5.834 56.5 4.4986 4.0 307.0 16 1.05393 0.0 8.14 0.0 0.538 5.935 29.3 4.4986 4.0 307.0 17 0.78420 0.0 8.14 0.0 0.538 5.990 81.7 4.2579 4.0 307.0 18 0.80271 0.0 8.14 0.0 0.538 5.456 36.6 3.7965 4.0 307.0 19 0.72580 0.0 8.14 0.0 0.538 5.727 69.5 3.7965 4.0 307.0 20 1.25179 0.0 8.14 0.0 0.538 5.570 98.1 3.7979 4.0 307.0 21 0.85204 0.0 8.14 0.0 0.538 5.965 89.2 4.0123 4.0 307.0 22 1.23247 0.0 8.14 0.0 0.538 6.142 91.7 3.9769 4.0 307.0 23 0.98843 0.0 8.14 0.0 0.538 5.813 100.0 4.0952 4.0 307.0 24 0.75026 0.0 8.14 0.0 0.538 5.924 94.1 4.3996 4.0 307.0 25 0.84054 0.0 8.14 0.0 0.538 5.599 85.7 4.4546 4.0 307.0 26 0.67191 0.0 8.14 0.0 0.538 5.813 90.3 4.6820 4.0 307.0 27 0.95577 0.0 8.14 0.0 0.538 6.047 88.8 4.4534 4.0 307.0 28 0.77299 0.0 8.14 0.0 0.538 6.495 94.4 4.4547 4.0 307.0 29 1.00245 0.0 8.14 0.0 0.538 6.674 87.3 4.2390 4.0 307.0 .. ... ... ... ... ... ... ... ... ... ... 476 4.87141 0.0 18.10 0.0 0.614 6.484 93.6 2.3053 24.0 666.0 477 15.02340 0.0 18.10 0.0 0.614 5.304 97.3 2.1007 24.0 666.0 478 10.23300 0.0 18.10 0.0 0.614 6.185 96.7 2.1705 24.0 666.0 479 14.33370 0.0 18.10 0.0 0.614 6.229 88.0 1.9512 24.0 666.0 480 5.82401 0.0 18.10 0.0 0.532 6.242 64.7 3.4242 24.0 666.0 481 5.70818 0.0 18.10 0.0 0.532 6.750 74.9 3.3317 24.0 666.0 482 5.73116 0.0 18.10 0.0 0.532 7.061 77.0 3.4106 24.0 666.0 483 2.81838 0.0 18.10 0.0 0.532 5.762 40.3 4.0983 24.0 666.0 484 2.37857 0.0 18.10 0.0 0.583 5.871 41.9 3.7240 24.0 666.0 485 3.67367 0.0 18.10 0.0 0.583 6.312 51.9 3.9917 24.0 666.0 486 5.69175 0.0 18.10 0.0 0.583 6.114 79.8 3.5459 24.0 666.0 487 4.83567 0.0 18.10 0.0 0.583 5.905 53.2 3.1523 24.0 666.0 488 0.15086 0.0 27.74 0.0 0.609 5.454 92.7 1.8209 4.0 711.0 489 0.18337 0.0 27.74 0.0 0.609 5.414 98.3 1.7554 4.0 711.0 490 0.20746 0.0 27.74 0.0 0.609 5.093 98.0 1.8226 4.0 711.0 491 0.10574 0.0 27.74 0.0 0.609 5.983 98.8 1.8681 4.0 711.0 492 0.11132 0.0 27.74 0.0 0.609 5.983 83.5 2.1099 4.0 711.0 493 0.17331 0.0 9.69 0.0 0.585 5.707 54.0 2.3817 6.0 391.0 494 0.27957 0.0 9.69 0.0 0.585 5.926 42.6 2.3817 6.0 391.0 495 0.17899 0.0 9.69 0.0 0.585 5.670 28.8 2.7986 6.0 391.0 496 0.28960 0.0 9.69 0.0 0.585 5.390 72.9 2.7986 6.0 391.0 497 0.26838 0.0 9.69 0.0 0.585 5.794 70.6 2.8927 6.0 391.0 498 0.23912 0.0 9.69 0.0 0.585 6.019 65.3 2.4091 6.0 391.0 499 0.17783 0.0 9.69 0.0 0.585 5.569 73.5 2.3999 6.0 391.0 500 0.22438 0.0 9.69 0.0 0.585 6.027 79.7 2.4982 6.0 391.0 501 0.06263 0.0 11.93 0.0 0.573 6.593 69.1 2.4786 1.0 273.0 502 0.04527 0.0 11.93 0.0 0.573 6.120 76.7 2.2875 1.0 273.0 503 0.06076 0.0 11.93 0.0 0.573 6.976 91.0 2.1675 1.0 273.0 504 0.10959 0.0 11.93 0.0 0.573 6.794 89.3 2.3889 1.0 273.0 505 0.04741 0.0 11.93 0.0 0.573 6.030 80.8 2.5050 1.0 273.0 PTRATIO B LSTAT 0 15.3 396.90 4.98 1 17.8 396.90 9.14 2 17.8 392.83 4.03 3 18.7 394.63 2.94 4 18.7 396.90 5.33 5 18.7 394.12 5.21 6 15.2 395.60 12.43 7 15.2 396.90 19.15 8 15.2 386.63 29.93 9 15.2 386.71 17.10 10 15.2 392.52 20.45 11 15.2 396.90 13.27 12 15.2 390.50 15.71 13 21.0 396.90 8.26 14 21.0 380.02 10.26 15 21.0 395.62 8.47 16 21.0 386.85 6.58 17 21.0 386.75 14.67 18 21.0 288.99 11.69 19 21.0 390.95 11.28 20 21.0 376.57 21.02 21 21.0 392.53 13.83 22 21.0 396.90 18.72 23 21.0 394.54 19.88 24 21.0 394.33 16.30 25 21.0 303.42 16.51 26 21.0 376.88 14.81 27 21.0 306.38 17.28 28 21.0 387.94 12.80 29 21.0 380.23 11.98 .. ... ... ... 476 20.2 396.21 18.68 477 20.2 349.48 24.91 478 20.2 379.70 18.03 479 20.2 383.32 13.11 480 20.2 396.90 10.74 481 20.2 393.07 7.74 482 20.2 395.28 7.01 483 20.2 392.92 10.42 484 20.2 370.73 13.34 485 20.2 388.62 10.58 486 20.2 392.68 14.98 487 20.2 388.22 11.45 488 20.1 395.09 18.06 489 20.1 344.05 23.97 490 20.1 318.43 29.68 491 20.1 390.11 18.07 492 20.1 396.90 13.35 493 19.2 396.90 12.01 494 19.2 396.90 13.59 495 19.2 393.29 17.60 496 19.2 396.90 21.14 497 19.2 396.90 14.10 498 19.2 396.90 12.92 499 19.2 395.77 15.10 500 19.2 396.90 14.33 501 21.0 391.99 9.67 502 21.0 396.90 9.08 503 21.0 396.90 5.64 504 21.0 393.45 6.48 505 21.0 396.90 7.88 [506 rows x 13 columns]
回答1件
0
目的変数はboston.targetです。
【データ解析】ボストン住宅価格データセットを使ってデータ解析する
投稿2019/11/28 06:49
総合スコア442
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