回答編集履歴
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Update
test
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後々の事を考えると、固定長で確保するよりは `dtype` に `object` を指定する方が良いかもしれません。
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```python
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#InitData = np.full((65,18),1)
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#boardData = InitData.astype(str)
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boardData = np.full((65,18), '', dtype=object)
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```
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**余談**
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xfpath = 'data.xml'
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df = pd.read_xml(
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df = pd.read_xml(xfpath, xpath='board')
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df.fillna('', inplace=True)
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boardData = df.to_numpy(copy=True)
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print(f'boardData:\n{boardData}\n')
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print(f' Type: {type(boardData)}')
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print(f' Type: {type(boardData)}')
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print(f' DataType: {type(boardData.dtype)}')
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print(f'Shape
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print(f' Shape: {boardData.shape}')
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boardData[2][1] = boardData[2][1] * 5
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print(f'boardData[2][1]: {boardData[2][1]}')
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print(f'\nboardData[2][1]: {boardData[2][1]}')
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_ = """
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boardData:
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[[1 'AKT53' 'K82' 'QT3' 'Q6' 'QJ7' 'T64' '976' 'J942' 98.0 'AJ93' 'A85'
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'T875' '642' 'Q75' 'KJ42' 'AK3' 'NONE' 'N']
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[2 '87' '64' 'T52' 'AQ6532' 'QT965' 'AT8' 'J64' '87' 4.0 'J953' 'K9873'
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'J94' 'AKJ32' 'KQ72' 'AQ' 'KT' 'NS' 'E']
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[3 'AKQJT98765432' '' '' '' '' 'AKQJT98765432' '' '' '' ''
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'AKQJT98765432' 'J94' '' '' '' 'AKQJT98765432' '' 'W']]
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Type: <class 'numpy.ndarray'>
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Type: <class 'numpy.ndarray'>
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DataType: <class 'numpy.dtype[object_]'>
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Shape
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Shape: (3, 19)
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boardData[2][1]: AKQJT98765432AKQJT98765432AKQJT98765432AKQJT98765432AKQJT98765432
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1
Update
test
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以下の説明は間違いです。正しくは bsdfan さんのコメントをお読み下さい。
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===== ここから =====
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ちなみに、`numpy 1.21.4` ではデフォルトで `21` バイト確保されるので当該の問題は発生しません。
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```python
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```
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===== ここまで =====
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**余談**
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boardData = df.to_numpy(copy=True)
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print(f' Type: {type(boardData)}')
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print(f'Shape : {boardData.shape}')
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boardData[2][1] = boardData[2][1] * 5
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print(f'boardData[2][1]: {boardData[2][1]}')
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0 1 AKT53 K82 QT3 Q6 QJ7 ... 642 Q75 KJ42 AK3 NONE N
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1 2 87 64 T52 AQ6532 QT965 ... AKJ32 KQ72 AQ KT NS E
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2 3 AKQJT98765432 ... AKQJT98765432 W
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_ = """
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Type: <class 'numpy.ndarray'>
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Shape : (3, 19)
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boardData[2][1]: AKQJT98765432AKQJT98765432AKQJT98765432AKQJT98765432AKQJT98765432
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"""
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```
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