pandas groupby导致keyerror
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pandas groupby causing keyerror
提问by oammon
I'm trying transform monthly time series data to quarterly then aggregate sums per quarter. I get a KeyError: 'date' when I run the following.
我正在尝试将月度时间序列数据转换为季度，然后每季度汇总总和。运行以下命令时出现 KeyError: 'date' 。
abc= abc.set_index('date').to_period('Q').groupby(['origin',
'date']).agg(sum)
However, when I reset the index as shown below, the code works. Why do I need to reset the index in order to use groupby on the origin and date fields? Is there a way to group without resetting the index?
但是，当我如下所示重置索引时，代码有效。为什么我需要重置索引才能在原点和日期字段上使用 groupby？有没有办法在不重置索引的情况下分组？
abc= abc.set_index('date').to_period('Q').reset_index().groupby(['origin',
'date']).agg(sum)
采纳答案by Allen
Because when you do:
因为当你这样做时：
abc= abc.set_index('date').to_period('Q')
You've changed 'date' to a index.
您已将“日期”更改为索引。
Later you try to access 'date' as a column which doesn't exist any more, hence the error. a reset_index operation restores 'date' as a column so it works again.
稍后您尝试将“日期”作为不再存在的列访问，因此出现错误。reset_index 操作将“日期”恢复为一列，以便它再次工作。
You can retain 'date' as column while setting it as index by doing:
您可以通过执行以下操作将“日期”保留为列，同时将其设置为索引：
abc= abc.set_index('date', drop=False).to_period('Q').groupby(['origin',
'date']).agg(sum)
