回答編集履歴
1
パフォーマンス意識
test
CHANGED
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@@ -8,7 +8,7 @@
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8
8
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df = pd.DataFrame({'A':range(10), 'B':range(10), 'C':range(10)})
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10
10
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11
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-
np.random.shuffle(df.loc[:, 'A'])
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11
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np.random.shuffle(df.loc[:, 'A'].to_numpy())
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@@ -37,3 +37,19 @@
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# 9 9 9 9
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```
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40
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41
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42
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43
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```Python
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>>> %timeit df.iloc[:,0] = df.iloc[:,0].sample(frac=1).reset_index(drop=True)
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412 µs ± 1.72 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)
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>>> %timeit np.random.shuffle(df.loc[:, 'A'].to_numpy())
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40.3 µs ± 117 ns per loop (mean ± std. dev. of 7 runs, 10000 loops each)
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```
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