pandas :将YYYYQQ值的索引转换为日期时间对象 [英] Pandas: Converting index of YYYYQQ values to datetime object

问题描述

我有以下DataFrame:

I have the following DataFrame:

df = pd.DataFrame({'A':[1,2,3],'B':[4,3,2]},index = ['201701','201702','201703'])

其中字符串值的索引是日期，格式为YYYYQQ(季度数据).

where the index of string values are dates in the format YYYYQQ (quarterly data).

当我尝试将其转换为日期时间对象时，出现错误:

When I try to convert this into a datetime object, I got the error:

pd.to_datetime(df.index)
....
ValueError: month must be in 1...12

我认为这必须归因于to_datetime推断df.index的格式，但我找不到解决方法.有帮助吗?

I feel this has to be due to the format the to_datetime is inferring df.index is, but I can't find a work around. Any help?

更新:@Zero的答案也有效，但这也最终成为一种解决方案:

Update: @Zero's answer also works, but this ended up being a solution too:

pd.to_datetime([x[:-2] + str(int(x[-2:])*3) for x in df.index], format = '%Y%m')

推荐答案

使用

In [2325]: [pd.to_datetime(x[:4]) + pd.offsets.QuarterBegin(int(x[5:])) for x in df.index]
Out[2325]:
[Timestamp('2017-03-01 00:00:00'),
 Timestamp('2017-06-01 00:00:00'),
 Timestamp('2017-09-01 00:00:00')]

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