質問編集履歴
2
詳細情報の追記
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Pythonもライブラリも最新のはずです。
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訓練データのデータフレームは
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```
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Id MSSubClass MSZoning LotFrontage LotArea Street Alley LotShape LandContour Utilities ... PoolArea PoolQC Fence MiscFeature MiscVal MoSold YrSold SaleType SaleCondition SalePrice
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0 1 60 RL 65.0 8450 Pave NaN Reg Lvl AllPub ... 0 NaN NaN NaN 0 2 2008 WD Normal 208500
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1 2 20 RL 80.0 9600 Pave NaN Reg Lvl AllPub ... 0 NaN NaN NaN 0 5 2007 WD Normal 181500
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2 3 60 RL 68.0 11250 Pave NaN IR1 Lvl AllPub ... 0 NaN NaN NaN 0 9 2008 WD Normal 223500
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3 4 70 RL 60.0 9550 Pave NaN IR1 Lvl AllPub ... 0 NaN NaN NaN 0 2 2006 WD Abnorml 140000
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4 5 60 RL 84.0 14260 Pave NaN IR1 Lvl AllPub ... 0 NaN NaN NaN 0 12 2008 WD Normal 250000
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5 rows × 81 columns
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```
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となっていて、訓練データ、テストデータ共に、モデルに使用する説明変数の欠損値は0個の状態になってます。
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エラーを省略せずに記しました。
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```
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---------------------------------------------------------------------------
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IndexingError Traceback (most recent call last)
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<ipython-input-62-686d210ba347> in <module>()
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1 # 作ったモデルをテスト用データに適用してみる
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----> 2 Pred = forest.predict(test.loc[:, ["OverallQual", "YearBuilt", "YearRemodAdd", "1stFlrSF", "GrLivArea", "FullBath", "GarageCars"]].values.reshape(-1,))
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~\Anaconda3\lib\site-packages\pandas\core\indexing.py in __getitem__(self, key)
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1470 except (KeyError, IndexError):
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1471 pass
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-> 1472 return self._getitem_tuple(key)
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1473 else:
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1474 # we by definition only have the 0th axis
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~\Anaconda3\lib\site-packages\pandas\core\indexing.py in _getitem_tuple(self, tup)
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873
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874 # no multi-index, so validate all of the indexers
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--> 875 self._has_valid_tuple(tup)
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876
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877 # ugly hack for GH #836
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~\Anaconda3\lib\site-packages\pandas\core\indexing.py in _has_valid_tuple(self, key)
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218 for i, k in enumerate(key):
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219 if i >= self.obj.ndim:
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--> 220 raise IndexingError('Too many indexers')
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221 try:
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222 self._validate_key(k, i)
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IndexingError: Too many indexers
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70
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