使用pandas [duplicate]对重复列进行分组并对相应的列值求和

问题描述 投票:1回答:1

这个问题在这里已有答案:

我正在预处理apache服务器日志数据。我有3列ID,TIME和BYTES。例:

ID&nbsp&nbsp TIME&nbsp&nbsp BYTES

1&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp

2&nbsp&nbsp&nbsp 13:02&nbsp&nbsp 30

3&nbsp&nbsp&nbsp 13:03&nbsp&nbsp 40

4&nbsp&nbsp&nbsp 13:02&nbsp&nbsp 50

5&nbsp&nbsp&nbsp 13:03&nbsp&nbsp 70

我希望实现这样的目标:

ID&nbsp&nbsp TIME&nbsp&nbsp BYTES

1&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp&nbsp

2&nbsp&nbsp&nbsp 13:02&nbsp&nbsp 80

3&nbsp&nbsp&nbsp 13:03&nbsp&nbsp 110

python-3.x pandas pandas-groupby data-scrubbing
1个回答
1
投票

我们试试吧:

df['TIME'] = pd.to_datetime(df['TIME'])
ax = df.groupby('TIME')['BYTES'].sum().plot()
ax.set_xlim('13:00:00','13:03:00')

输出:

enter image description here

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