回答編集履歴
3
test
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@@ -1,38 +1,2 @@
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1
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※ 削除
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2
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3
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「操作順に」とありますが、質問にあるコードでは操作順にソートする処理がありません。レコードが操作順にデータフレームに格納されているのかもしれませんが、念の為にソートしています。(`sort_values(['user_id', '操作順'])`)
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4
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5
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```python
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import pandas as pd
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import io
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def point_mean(gamedf):
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gamedf['order'] = gamedf.sort_values(['user_id', '操作順']).groupby('user_id')['操作順'].cumcount()
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return gamedf.pivot(index='order', columns='user_id', values='point')
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# 「操作順」データが連続する値(例えば [0, 1, 2, 3, ..., 12, 13])の場合は pivot() だけでもよいはず
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# def point_mean(gamedf):
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# return gamedf.pivot(index='操作順', columns='user_id', values='point')
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if __name__ == '__main__':
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csv_data = '''
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user_id,操作順,point
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aaaa,0,10
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aaaa,1,2
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aaaa,2,100
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aaaa,13,20
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bbbb,0,5
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zzzz,13,40
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'''
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df = pd.read_csv(io.StringIO(csv_data))
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resultdf = point_mean(df)
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print(resultdf)
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# user_id aaaa bbbb zzzz
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# order
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# 0 10.0 5.0 40.0
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# 1 2.0 NaN NaN
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# 2 100.0 NaN NaN
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# 3 20.0 NaN NaN
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38
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```
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2
test
CHANGED
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@@ -9,6 +9,10 @@
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def point_mean(gamedf):
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gamedf['order'] = gamedf.sort_values(['user_id', '操作順']).groupby('user_id')['操作順'].cumcount()
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return gamedf.pivot(index='order', columns='user_id', values='point')
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# 「操作順」データが連続する値(例えば [0, 1, 2, 3, ..., 12, 13])の場合は pivot() だけでもよいはず
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# def point_mean(gamedf):
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# return gamedf.pivot(index='操作順', columns='user_id', values='point')
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if __name__ == '__main__':
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csv_data = '''
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1
test
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@@ -8,7 +8,7 @@
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def point_mean(gamedf):
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gamedf['order'] = gamedf.sort_values(['user_id', '操作順']).groupby('user_id')['操作順'].cumcount()
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return gamedf.pivot(index='
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return gamedf.pivot(index='order', columns='user_id', values='point')
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if __name__ == '__main__':
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csv_data = '''
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