回答編集履歴
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追記
test
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@@ -65,3 +65,65 @@
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参考：
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[pandas.DataFrame.groupby — pandas 0.23.0 documentation](https://pandas.pydata.org/pandas-docs/stable/generated/pandas.DataFrame.groupby.html)
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### 追記
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とりあえずdatetime.timeにしてみました。
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```python
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import io
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import datetime
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import pandas as pd
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# ただの読み込み処理
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data = """
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2018-05-28 18:01:00 100 200
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2018-05-28 18:05:00 100 200
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2018-05-28 19:08:00 100 200
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2018-05-28 19:01:00 100 200
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2018-05-29 18:01:00 100 200
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2018-05-29 18:05:00 100 200
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2018-05-29 19:08:00 100 200
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2018-05-29 19:01:00 100 200
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"""
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df = pd.read_table(io.StringIO(data), header=None, index_col=0)
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df.index = pd.to_datetime(df.index)
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# 回答
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print(df.groupby(lambda x:datetime.time(hour=x.hour)).sum())
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""" =>
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1 2
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18:00:00 400 800
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19:00:00 400 800
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"""
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```
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結果を書いておこう
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@@ -44,7 +44,21 @@
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print(df.groupby(lambda x:x.hour).sum())
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""" =>
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1 2
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18 400 800
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19 400 800
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"""
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```
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これだとindexがintなのが微妙といえば微妙かも・・・
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