回答編集履歴
2
質問の修正に合わせて値の修正
answer
CHANGED
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@@ -4,7 +4,7 @@
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4
4
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5
5
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df = pd.DataFrame({ 'time': ['2020-09-16 00:00:00', '2020-09-16 00:00:00', '2020-09-16 00:00:00', '2020-09-16 00:05:00', '2020-09-16 00:05:00', '2020-09-16 00:05:00', '2020-09-16 00:10:00', '2020-09-16 00:10:00', '2020-09-16 00:10:00'],
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6
6
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'item_name': ['item_a', 'item_b', 'item_c', 'item_a', 'item_b', 'item_c', 'item_a', 'item_b', 'item_c'],
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7
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-
'value': [
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7
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+
'value': [100, 5, 20, 10, 5, 20, 20, 10, 5]})
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8
8
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df_sums = df.groupby(['time']).agg({'value': np.sum})
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9
9
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print(df_sums['value'][df_sums['value'] == df_sums['value'].max()])
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10
10
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```
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1
結果出力の修正
answer
CHANGED
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@@ -6,5 +6,5 @@
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6
6
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'item_name': ['item_a', 'item_b', 'item_c', 'item_a', 'item_b', 'item_c', 'item_a', 'item_b', 'item_c'],
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7
7
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'value': [10, 5, 20, 10, 5, 20, 20, 10, 5]})
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8
8
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df_sums = df.groupby(['time']).agg({'value': np.sum})
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9
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-
df_sums['value'].max()
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9
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+
print(df_sums['value'][df_sums['value'] == df_sums['value'].max()])
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10
10
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```
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