Q&A
試したことは実際のコードでしょうか？
trainに対して処理していますが、やるべきはtestに対してではないでしょうか？
引用テキスト### 前提・実現したいこと
pandasでtestデータとtrainデータを整形していますが
trainでは```Python3
コード
train = train.astype(float) #全てfloatに変換される
しかし、testでは以下を実行するとエラーメッセージ
test = test.astype(float) --------------------------------------------------------------------------- ValueError Traceback (most recent call last) <ipython-input-41-2f18abe8c2b8> in <module> ----> 1 test = test.astype(float) ~/opt/anaconda3/lib/python3.7/site-packages/pandas/core/generic.py in astype(self, dtype, copy, errors) 5696 else: 5697 # else, only a single dtype is given -> 5698 new_data = self._data.astype(dtype=dtype, copy=copy, errors=errors) 5699 return self._constructor(new_data).__finalize__(self) 5700 ~/opt/anaconda3/lib/python3.7/site-packages/pandas/core/internals/managers.py in astype(self, dtype, copy, errors) 580 581 def astype(self, dtype, copy: bool = False, errors: str = "raise"): --> 582 return self.apply("astype", dtype=dtype, copy=copy, errors=errors) 583 584 def convert(self, **kwargs): ~/opt/anaconda3/lib/python3.7/site-packages/pandas/core/internals/managers.py in apply(self, f, filter, **kwargs) 440 applied = b.apply(f, **kwargs) 441 else: --> 442 applied = getattr(b, f)(**kwargs) 443 result_blocks = _extend_blocks(applied, result_blocks) 444 ~/opt/anaconda3/lib/python3.7/site-packages/pandas/core/internals/blocks.py in astype(self, dtype, copy, errors) 623 vals1d = values.ravel() 624 try: --> 625 values = astype_nansafe(vals1d, dtype, copy=True) 626 except (ValueError, TypeError): 627 # e.g. astype_nansafe can fail on object-dtype of strings ~/opt/anaconda3/lib/python3.7/site-packages/pandas/core/dtypes/cast.py in astype_nansafe(arr, dtype, copy, skipna) 895 if copy or is_object_dtype(arr) or is_object_dtype(dtype): 896 # Explicit copy, or required since NumPy can't view from / to object. --> 897 return arr.astype(dtype, copy=True) 898 899 return arr.view(dtype) ValueError: could not convert string to float: ```Python3 が出てしまいます。なぜなのでしょうか。
#train(floatに変換できている)
PassengerId Survived Pclass Age SibSp Parch Fare man woman child A B C D E F G C_Embarked Q_Embarked S_Embarked female male
0 1.0 0.0 3.0 22.0 1.0 0.0 7.2500 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0
1 2.0 1.0 1.0 38.0 1.0 0.0 71.2833 1.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 1.0 0.0 0.0 1.0 0.0
2 3.0 1.0 3.0 26.0 0.0 0.0 7.9250 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0
3 4.0 1.0 1.0 35.0 1.0 0.0 53.1000 1.0 1.0 0.0 0.0 0.0 1.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 1.0 0.0
4 5.0 0.0 3.0 35.0 0.0 0.0 8.0500 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.0 1.0
#test 全てstr型 floatに変換できない。
PassengerId Pclass Age SibSp Parch Fare man woman child A B C D E F G C_Embarked Q_Embarked S_Embarked female male
0 892 3 34.5 0 0 7.8292 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1
1 893 3 47 1 0 7 1 1 0 0 0 0 0 0 0 0 0 0 1 1 0
2 894 2 62 0 0 9.6875 1 0 0 0 0 0 0 0 0 0 0 1 0 0 1
3 895 3 27 0 0 8.6625 1 0 0 0 0 0 0 0 0 0 0 0 1 0 1
4 896 3 22 1 1 12.2875 1 1 0 0 0 0 0 0 0 0 0 0 1 1 0
### 試したこと 'Age'が'2','4','',...,'',...と欠損している場所があったため、
train['Age'] = train['Age'].apply(lambda x: '0' if x == '' else x)
test['Age'] = test['Age'].apply(lambda x: '0' if x == '' else x)
で補完しています。後は、特段の欠損は見られません。 ### 補足情報（FW/ツールのバージョンなど） ここにより詳細な情報を記載してください。
回答1件
0
ベストアンサー
空文字列があると提示エラーが発生しますが、試したことのように処理していると問題なく動作すると思います。
あとはデータを見ないと何とも言えないので、以下のような感じでtestデータをCSVファイルとして出力し、その中身をコードブロックで囲んで提示ください。
Python
1import pandas as pd 2 3df = pd.DataFrame({'Age':['1.2','']}) 4print(df) 5# Age 6#0 1.2 7#1 8df.to_csv('test.csv', index=None) # 検証用データを出力 9 10 11df['Age'] = df['Age'].apply(lambda x: '0' if x == '' else x) # ★ 12df['Age'] = df['Age'].astype(float) # ★がないと ValueError: could not convert string to float: 13print(df) 14# Age 15#0 1.2 16#1 0.0
test.csv
Age 1.2 ""
投稿2020/07/23 04:28
編集2020/07/23 04:29総合スコア38341
test.csvはこちらになります。
```
PassengerId,Pclass,Age,SibSp,Parch,Fare,man,woman,child,A,B,C,D,E,F,G,C_Embarked,Q_Embarked,S_Embarked,female,male
892,3,34.5,0,0,7.8292,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
893,3,47,1,0,7,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
894,2,62,0,0,9.6875,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
895,3,27,0,0,8.6625,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
896,3,22,1,1,12.2875,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
897,3,14,0,0,9.225,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
898,3,30,0,0,7.6292,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
899,2,26,1,1,29,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
900,3,18,0,0,7.2292,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
901,3,21,2,0,24.15,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
902,3,0.0,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
903,1,46,0,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
904,1,23,1,0,82.2667,1,1,0,0,1,0,0,0,0,0,0,0,1,1,0
905,2,63,1,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
906,1,47,1,0,61.175,1,1,0,0,0,0,0,1,0,0,0,0,1,1,0
907,2,24,1,0,27.7208,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
908,2,35,0,0,12.35,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
909,3,21,0,0,7.225,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
910,3,27,1,0,7.925,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
911,3,45,0,0,7.225,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
912,1,55,1,0,59.4,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
913,3,9,0,1,3.1708,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
914,1,0.0,0,0,31.6833,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
915,1,21,0,1,61.3792,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
916,1,48,1,3,262.375,1,1,0,0,1,0,0,0,0,0,1,0,0,1,0
917,3,50,1,0,14.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
918,1,22,0,1,61.9792,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0
919,3,22.5,0,0,7.225,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
920,1,41,0,0,30.5,1,0,0,1,0,0,0,0,0,0,0,0,1,0,1
921,3,0.0,2,0,21.6792,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
922,2,50,1,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
923,2,24,2,0,31.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
924,3,33,1,2,20.575,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
925,3,0.0,1,2,23.45,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
926,1,30,1,0,57.75,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1
927,3,18.5,0,0,7.2292,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
928,3,0.0,0,0,8.05,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
929,3,21,0,0,8.6625,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
930,3,25,0,0,9.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
931,3,0.0,0,0,56.4958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
932,3,39,0,1,13.4167,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
933,1,0.0,0,0,26.55,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1
934,3,41,0,0,7.85,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
935,2,30,0,0,13,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
936,1,45,1,0,52.5542,1,1,0,0,0,0,1,0,0,0,0,0,1,1,0
937,3,25,0,0,7.925,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
938,1,45,0,0,29.7,1,0,0,1,0,0,0,0,0,0,1,0,0,0,1
939,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
940,1,60,0,0,76.2917,1,1,0,0,0,0,1,0,0,0,1,0,0,1,0
941,3,36,0,2,15.9,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
942,1,24,1,0,60,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1
943,2,27,0,0,15.0333,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
944,2,20,2,1,23,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
945,1,28,3,2,263,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0
946,2,0.0,0,0,15.5792,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
947,3,10,4,1,29.125,0,0,1,0,0,0,0,0,0,0,0,1,0,0,1
948,3,35,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
949,3,25,0,0,7.65,1,0,0,0,0,0,0,0,1,0,0,0,1,0,1
950,3,0.0,1,0,16.1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
951,1,36,0,0,262.375,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0
952,3,17,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
953,2,32,0,0,13.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
954,3,18,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
955,3,22,0,0,7.725,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
956,1,13,2,2,262.375,0,0,1,0,1,0,0,0,0,0,1,0,0,0,1
957,2,0.0,0,0,21,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
958,3,18,0,0,7.8792,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
959,1,47,0,0,42.4,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
960,1,31,0,0,28.5375,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1
961,1,60,1,4,263,1,1,0,0,0,1,0,0,0,0,0,0,1,1,0
962,3,24,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
963,3,21,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
964,3,29,0,0,7.925,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
965,1,28.5,0,0,27.7208,1,0,0,0,0,0,1,0,0,0,1,0,0,0,1
966,1,35,0,0,211.5,0,0,0,0,0,1,0,0,0,0,1,0,0,1,0
967,1,32.5,0,0,211.5,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1
968,3,0.0,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
969,1,55,2,0,25.7,1,1,0,0,0,1,0,0,0,0,0,0,1,1,0
970,2,30,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
971,3,24,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
972,3,6,1,1,15.2458,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1
973,1,67,1,0,221.7792,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1
974,1,49,0,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
975,3,0.0,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
976,2,0.0,0,0,10.7083,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
977,3,0.0,1,0,14.4542,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
978,3,27,0,0,7.8792,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
979,3,18,0,0,8.05,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
980,3,0.0,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
981,2,2,1,1,23,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
982,3,22,1,0,13.9,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
983,3,0.0,0,0,7.775,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
984,1,27,1,2,52,1,1,0,0,1,0,0,0,0,0,0,0,1,1,0
985,3,0.0,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
986,1,25,0,0,26,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
987,3,25,0,0,7.7958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
988,1,76,1,0,78.85,1,1,0,0,0,1,0,0,0,0,0,0,1,1,0
989,3,29,0,0,7.925,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
990,3,20,0,0,7.8542,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
991,3,33,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
992,1,43,1,0,55.4417,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0
993,2,27,1,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
994,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
995,3,26,0,0,7.775,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
996,3,16,1,1,8.5167,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
997,3,28,0,0,22.525,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
998,3,21,0,0,7.8208,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
999,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1000,3,0.0,0,0,8.7125,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1001,2,18.5,0,0,13,1,0,0,0,0,0,0,0,1,0,0,0,1,0,1
1002,2,41,0,0,15.0458,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1003,3,0.0,0,0,7.7792,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1004,1,36,0,0,31.6792,0,0,0,1,0,0,0,0,0,0,1,0,0,1,0
1005,3,18.5,0,0,7.2833,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1006,1,63,1,0,221.7792,1,1,0,0,0,1,0,0,0,0,0,0,1,1,0
1007,3,18,1,0,14.4542,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1008,3,0.0,0,0,6.4375,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1009,3,1,1,1,16.7,0,0,0,0,0,0,0,0,0,1,0,0,1,1,0
1010,1,36,0,0,75.2417,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1
1011,2,29,1,0,26,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1012,2,12,0,0,15.75,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1013,3,0.0,1,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1014,1,35,1,0,57.75,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0
1015,3,28,0,0,7.25,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1016,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1017,3,17,0,1,16.1,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1018,3,22,0,0,7.7958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1019,3,0.0,2,0,23.25,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1020,2,42,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1021,3,24,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1022,3,32,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1023,1,53,0,0,28.5,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1
1024,3,0.0,0,4,25.4667,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1025,3,0.0,1,0,6.4375,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1026,3,43,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1027,3,24,0,0,7.8542,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1028,3,26.5,0,0,7.225,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1029,2,26,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1030,3,23,0,0,8.05,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1031,3,40,1,6,46.9,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1032,3,10,5,2,46.9,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1033,1,33,0,0,151.55,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1034,1,61,1,3,262.375,1,0,0,0,1,0,0,0,0,0,1,0,0,0,1
1035,2,28,0,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1036,1,42,0,0,26.55,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1037,3,31,3,0,18,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1038,1,0.0,0,0,51.8625,1,0,0,0,0,0,0,1,0,0,0,0,1,0,1
1039,3,22,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1040,1,0.0,0,0,26.55,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1041,2,30,1,1,26,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1042,1,23,0,1,83.1583,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0
1043,3,0.0,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1044,3,60.5,0,0,,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1045,3,36,0,2,12.1833,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1046,3,13,4,2,31.3875,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1047,3,24,0,0,7.55,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1048,1,29,0,0,221.7792,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0
1049,3,23,0,0,7.8542,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1050,1,42,0,0,26.55,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1
1051,3,26,0,2,13.775,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1052,3,0.0,0,0,7.7333,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1053,3,7,1,1,15.2458,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1
1054,2,26,0,0,13.5,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1055,3,0.0,0,0,7,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1056,2,41,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1057,3,26,1,1,22.025,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1058,1,48,0,0,50.4958,1,0,0,0,1,0,0,0,0,0,1,0,0,0,1
1059,3,18,2,2,34.375,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1060,1,0.0,0,0,27.7208,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
```
```
1061,3,22,0,0,8.9625,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1062,3,0.0,0,0,7.55,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1063,3,27,0,0,7.225,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1064,3,23,1,0,13.9,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1065,3,0.0,0,0,7.2292,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1066,3,40,1,5,31.3875,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1067,2,15,0,2,39,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1068,2,20,0,0,36.75,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1069,1,54,1,0,55.4417,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1
1070,2,36,0,3,39,1,1,0,0,0,0,0,0,1,0,0,0,1,1,0
1071,1,64,0,2,83.1583,1,1,0,0,0,0,0,1,0,0,1,0,0,1,0
1072,2,30,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1073,1,37,1,1,83.1583,1,0,0,0,0,0,0,1,0,0,1,0,0,0,1
1074,1,18,1,0,53.1,1,1,0,0,0,0,1,0,0,0,0,0,1,1,0
1075,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1076,1,27,1,1,247.5208,1,1,0,0,1,0,0,0,0,0,1,0,0,1,0
1077,2,40,0,0,16,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1078,2,21,0,1,21,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1079,3,17,2,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1080,3,0.0,8,2,69.55,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1081,2,40,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1082,2,34,1,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1083,1,0.0,0,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1084,3,11.5,1,1,14.5,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1085,2,61,0,0,12.35,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1086,2,8,0,2,32.5,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1087,3,33,0,0,7.8542,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1088,1,6,0,2,134.5,0,0,1,0,0,0,0,1,0,0,1,0,0,0,1
1089,3,18,0,0,7.775,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1090,2,23,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1091,3,0.0,0,0,8.1125,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1092,3,0.0,0,0,15.5,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1093,3,0.33,0,2,14.4,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1094,1,47,1,0,227.525,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1
1095,2,8,1,1,26,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1096,2,25,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1097,1,0.0,0,0,25.7417,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1098,3,35,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1099,2,24,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1100,1,33,0,0,27.7208,0,0,0,1,0,0,0,0,0,0,1,0,0,1,0
1101,3,25,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1102,3,32,0,0,22.525,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1103,3,0.0,0,0,7.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1104,2,17,0,0,73.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1105,2,60,1,0,26,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1106,3,38,4,2,7.775,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1107,1,42,0,0,42.5,1,0,0,0,1,0,0,0,0,0,0,0,1,0,1
1108,3,0.0,0,0,7.8792,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1109,1,57,1,1,164.8667,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1110,1,50,1,1,211.5,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0
1111,3,0.0,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1112,2,30,1,0,13.8583,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0
1113,3,21,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1114,2,22,0,0,10.5,1,1,0,0,0,0,0,0,1,0,0,0,1,1,0
1115,3,21,0,0,7.7958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1116,1,53,0,0,27.4458,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
1117,3,0.0,0,2,15.2458,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
1118,3,23,0,0,7.7958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1119,3,0.0,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1120,3,40.5,0,0,15.1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1121,2,36,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1122,2,14,0,0,65,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1123,1,21,0,0,26.55,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1124,3,21,1,0,6.4958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1125,3,0.0,0,0,7.8792,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1126,1,39,1,0,71.2833,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1
1127,3,20,0,0,7.8542,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1128,1,64,1,0,75.25,1,0,0,0,0,0,1,0,0,0,1,0,0,0,1
1129,3,20,0,0,7.225,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1130,2,18,1,1,13,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1131,1,48,1,0,106.425,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0
1132,1,55,0,0,27.7208,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
1133,2,45,0,2,30,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1134,1,45,1,1,134.5,1,0,0,0,0,0,0,1,0,0,1,0,0,0,1
1135,3,0.0,0,0,7.8875,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1136,3,0.0,1,2,23.45,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1137,1,41,1,0,51.8625,1,0,0,0,0,0,1,0,0,0,0,0,1,0,1
1138,2,22,0,0,21,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1139,2,42,1,1,32.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1140,2,29,1,0,26,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1141,3,0.0,1,0,14.4542,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
1142,2,0.92,1,2,27.75,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1143,3,20,0,0,7.925,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1144,1,27,1,0,136.7792,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1
1145,3,24,0,0,9.325,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1146,3,32.5,0,0,9.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1147,3,0.0,0,0,7.55,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1148,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1149,3,28,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1150,2,19,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1151,3,21,0,0,7.775,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1152,3,36.5,1,0,17.4,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1153,3,21,0,0,7.8542,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1154,2,29,0,2,23,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
```
```
1155,3,1,1,1,12.1833,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1156,2,30,0,0,12.7375,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1157,3,0.0,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1158,1,0.0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1159,3,0.0,0,0,7.55,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1160,3,0.0,0,0,8.05,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1161,3,17,0,0,8.6625,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1162,1,46,0,0,75.2417,1,0,0,0,0,1,0,0,0,0,1,0,0,0,1
1163,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1164,1,26,1,0,136.7792,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0
1165,3,0.0,1,0,15.5,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1166,3,0.0,0,0,7.225,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1167,2,20,1,0,26,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1168,2,28,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1169,2,40,1,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1170,2,30,1,0,21,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1171,2,22,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1172,3,23,0,0,8.6625,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1173,3,0.75,1,1,13.775,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1174,3,0.0,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1175,3,9,1,1,15.2458,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0
1176,3,2,1,1,20.2125,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1177,3,36,0,0,7.25,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1178,3,0.0,0,0,7.25,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1179,1,24,1,0,82.2667,1,0,0,0,1,0,0,0,0,0,0,0,1,0,1
1180,3,0.0,0,0,7.2292,1,0,0,0,0,0,0,0,1,0,1,0,0,0,1
1181,3,0.0,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1182,1,0.0,0,0,39.6,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1183,3,30,0,0,6.95,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1184,3,0.0,0,0,7.2292,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1185,1,53,1,1,81.8583,0,0,0,1,0,0,0,0,0,0,0,0,1,0,1
1186,3,36,0,0,9.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1187,3,26,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1188,2,1,1,2,41.5792,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0
1189,3,0.0,2,0,21.6792,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1190,1,30,0,0,45.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1191,3,29,0,0,7.8542,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1192,3,32,0,0,7.775,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1193,2,0.0,0,0,15.0458,1,0,0,0,0,0,1,0,0,0,1,0,0,0,1
1194,2,43,0,1,21,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1195,3,24,0,0,8.6625,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1196,3,0.0,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1197,1,64,1,1,26.55,1,1,0,0,1,0,0,0,0,0,0,0,1,1,0
1198,1,30,1,2,151.55,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1
1199,3,0.83,0,1,9.35,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1200,1,55,1,1,93.5,1,0,0,0,1,0,0,0,0,0,0,0,1,0,1
1201,3,45,1,0,14.1083,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1202,3,18,0,0,8.6625,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1203,3,22,0,0,7.225,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1204,3,0.0,0,0,7.575,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1205,3,37,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1206,1,55,0,0,135.6333,1,1,0,0,0,1,0,0,0,0,1,0,0,1,0
1207,3,17,0,0,7.7333,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1208,1,57,1,0,146.5208,1,0,0,0,1,0,0,0,0,0,1,0,0,0,1
1209,2,19,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1210,3,27,0,0,7.8542,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1211,2,22,2,0,31.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1212,3,26,0,0,7.775,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1213,3,25,0,0,7.2292,1,0,0,0,0,0,0,0,1,0,1,0,0,0,1
1214,2,26,0,0,13,1,0,0,0,0,0,0,0,1,0,0,0,1,0,1
1215,1,33,0,0,26.55,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1216,1,39,0,0,211.3375,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1217,3,23,0,0,7.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1218,2,12,2,1,39,0,0,0,0,0,0,0,0,1,0,0,0,1,1,0
1219,1,46,0,0,79.2,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1220,2,29,1,0,26,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1221,2,21,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1222,2,48,0,2,36.75,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1223,1,39,0,0,29.7,1,0,0,1,0,0,0,0,0,0,1,0,0,0,1
1224,3,0.0,0,0,7.225,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1225,3,19,1,1,15.7417,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
1226,3,27,0,0,7.8958,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1227,1,30,0,0,26,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1
1228,2,32,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1229,3,39,0,2,7.2292,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1230,2,25,0,0,31.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1231,3,0.0,0,0,7.2292,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1
1232,2,18,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1233,3,32,0,0,7.5792,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1234,3,0.0,1,9,69.55,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1235,1,58,0,1,512.3292,1,1,0,0,1,0,0,0,0,0,1,0,0,1,0
1236,3,0.0,1,1,14.5,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1237,3,16,0,0,7.65,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1238,2,26,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1239,3,38,0,0,7.2292,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
1240,2,24,0,0,13.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1241,2,31,0,0,21,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1242,1,45,0,1,63.3583,1,1,0,0,0,0,1,0,0,0,1,0,0,1,0
1243,2,25,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1244,2,18,0,0,73.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1245,2,49,1,2,65,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1246,3,0.17,1,2,20.575,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1247,1,50,0,0,26,1,0,0,0,0,0,0,1,0,0,0,0,1,0,1
1248,1,59,2,0,51.4792,1,1,0,0,0,1,0,0,0,0,0,0,1,1,0
1249,3,0.0,0,0,7.8792,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1250,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1251,3,30,1,0,15.55,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1252,3,14.5,8,2,69.55,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1253,2,24,1,1,37.0042,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
1254,2,31,0,0,21,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1255,3,27,0,0,8.6625,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1256,1,25,1,0,55.4417,1,1,0,0,0,0,0,1,0,0,1,0,0,1,0
1257,3,0.0,1,9,69.55,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1258,3,0.0,1,0,14.4583,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1259,3,22,0,0,39.6875,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1260,1,45,0,1,59.4,1,1,0,0,0,0,0,0,0,0,1,0,0,1,0
1261,2,29,0,0,13.8583,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1
1262,2,21,1,0,11.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1263,1,31,0,0,134.5,0,0,0,0,0,0,0,1,0,0,1,0,0,1,0
1264,1,49,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0,1
1265,2,44,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1266,1,54,1,1,81.8583,1,1,0,1,0,0,0,0,0,0,0,0,1,1,0
1267,1,45,0,0,262.375,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0
1268,3,22,2,0,8.6625,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1269,2,21,0,0,11.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1270,1,55,0,0,50,1,0,0,0,0,1,0,0,0,0,0,0,1,0,1
1271,3,5,4,2,31.3875,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1272,3,0.0,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1273,3,26,0,0,7.8792,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1274,3,0.0,0,0,14.5,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1275,3,19,1,0,16.1,1,1,0,0,0,0,0,0,0,0,0,0,1,1,0
1276,2,0.0,0,0,12.875,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1277,2,24,1,2,65,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1278,3,24,0,0,7.775,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1279,2,57,0,0,13,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1280,3,21,0,0,7.75,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1281,3,6,3,1,21.075,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1282,1,23,0,0,93.5,1,0,0,0,1,0,0,0,0,0,0,0,1,0,1
1283,1,51,0,1,39.4,1,1,0,0,0,0,1,0,0,0,0,0,1,1,0
1284,3,13,0,2,20.25,0,0,1,0,0,0,0,0,0,0,0,0,1,0,1
1285,2,47,0,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1286,3,29,3,1,22.025,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1287,1,18,1,0,60,1,1,0,0,0,1,0,0,0,0,0,0,1,1,0
1288,3,24,0,0,7.25,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1289,1,48,1,1,79.2,1,1,0,0,1,0,0,0,0,0,1,0,0,1,0
1290,3,22,0,0,7.775,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1291,3,31,0,0,7.7333,1,0,0,0,0,0,0,0,0,0,0,1,0,0,1
1292,1,30,0,0,164.8667,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0
1293,2,38,1,0,21,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1294,1,22,0,1,59.4,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0
1295,1,17,0,0,47.1,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1296,1,43,1,0,27.7208,1,0,0,0,0,0,1,0,0,0,1,0,0,0,1
1297,2,20,0,0,13.8625,1,0,0,0,0,0,1,0,0,0,1,0,0,0,1
1298,2,23,1,0,10.5,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1299,1,50,1,1,211.5,1,0,0,0,0,1,0,0,0,0,1,0,0,0,0
1300,3,0.0,0,0,7.7208,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1301,3,3,1,1,13.775,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1302,3,0.0,0,0,7.75,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0
1303,1,37,1,0,90,1,1,0,0,0,1,0,0,0,0,0,1,0,1,0
1304,3,28,0,0,7.775,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0
1305,3,0.0,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1306,1,39,0,0,108.9,0,0,0,0,0,1,0,0,0,0,1,0,0,1,0
1307,3,38.5,0,0,7.25,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1308,3,0.0,0,0,8.05,1,0,0,0,0,0,0,0,0,0,0,0,1,0,1
1309,3,0.0,1,1,22.3583,0,0,1,0,0,0,0,0,0,0,1,0,0,0,1
```
この欄はコードブロックが効かないので質問本文を修正して追記ください。
また、できればエラーが再現する最小限のCSVを新たに作成して提示していただけないでしょうか？
なお、こちらのコメント欄での３つのCSV文字列を連結してtest.csvに保存して実行してみましたが、エラーなく正常に動作しました。
ご回答ありがとうございます。
1万字を超えてしまったため追記できませんでした。
上の通り別のノートブックで実行したところ、trainと同じように変換することができました。
ご確認ありがとうございました。
あなたの回答
tips
プレビュー
