偏移前滚加上一个月的偏移后， pandas 越界纳秒时间戳 [英] pandas out of bounds nanosecond timestamp after offset rollforward plus adding a month offset

问题描述

我很困惑熊猫是如何用这些行超出日期时间对象的范围的:

I am confused how pandas blew out of bounds for datetime objects with these lines:

import pandas as pd
BOMoffset = pd.tseries.offsets.MonthBegin()
# here some code sets the all_treatments dataframe and the newrowix, micolix, mocolix counters
all_treatments.iloc[newrowix,micolix] = BOMoffset.rollforward(all_treatments.iloc[i,micolix] + pd.tseries.offsets.DateOffset(months = x))
all_treatments.iloc[newrowix,mocolix] = BOMoffset.rollforward(all_treatments.iloc[newrowix,micolix]+ pd.tseries.offsets.DateOffset(months = 1))

这里 all_treatments.iloc[i,micolix] 是由 pd.to_datetime(all_treatments['INDATUMA'], errors='coerce',format='%Y% 设置的日期时间m%d')，INDATUMA是日期信息，格式为20070125.

Here all_treatments.iloc[i,micolix] is a datetime set by pd.to_datetime(all_treatments['INDATUMA'], errors='coerce',format='%Y%m%d'), and INDATUMA is date information in the format 20070125.

这个逻辑似乎适用于模拟数据(没有错误，日期有意义)，所以目前我无法重现，因为它在我的整个数据中失败并出现以下错误:

This logic seems to work on mock data (no errors, dates make sense), so at the moment I cannot reproduce while it fails in my entire data with the following error:

pandas.tslib.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 2262-05-01 00:00:00

推荐答案

由于 pandas 以纳秒分辨率表示时间戳，因此可以使用 64 位整数表示的时间跨度被限制为大约 584 年

Since pandas represents timestamps in nanosecond resolution, the timespan that can be represented using a 64-bit integer is limited to approximately 584 years

pd.Timestamp.min
Out[54]: Timestamp('1677-09-22 00:12:43.145225')

In [55]: pd.Timestamp.max
Out[55]: Timestamp('2262-04-11 23:47:16.854775807')

并且您的值超出此范围 2262-05-01 00:00:00，因此出现越界错误

And your value is out of this range 2262-05-01 00:00:00 and hence the outofbounds error

直接来自:http://pandas-docs.github.io/pandas-docs-travis/user_guide/timeseries.html#timeseries-timestamp-limits

解决方法:

这将强制超出范围的日期NaT

This will force the dates which are outside the bounds to NaT

pd.to_datetime(date_col_to_force, errors = 'coerce')

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