大 pandas 超出边界毫秒时间戳后偏移前滚加上一个月的偏移 [英] pandas out of bounds nanosecond timestamp after offset rollforward plus adding a month offset

问题描述

我很困惑，大熊猫如何从datetime对象中排除这些行：

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％m％d'）设置的日期时间和 INDATUMA 是格式为 20070125 的日期信息。

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），所以当我无法再现时，它失败在我的整个数据中出现以下错误：

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

由于熊猫代表时间戳，以纳秒为单位分辨率，可以使用64位整数表示的时间限制限制在大约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')

你的价值不在这个范围是2262-05-01 00:00:00，因此outofbounds错误

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

直接出来： http://pandas-docs.github.io/pandas-docs-travis/timeseries.html#timestamp-limitations

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