pandas :从GMT中的CSV读取时间戳，然后重新采样

问题描述

我有一个带有纪元GMT时间戳的CSV，它以不规则的间隔与值配对.我尝试从CSV读取它，但是所有时区都转移到了本地时区.如何使其按原样(在GMT中)阅读?然后，我想以一分钟为间隔重新采样，但是，我想跳过大于用户指定值的间隙.如果无法做到这一点，是否可以将采样重采样到一分钟，但是请在空白处输入0.0之类的任意值?

I have a CSV with epoch GMT timestamp at irregular intervals paired with a value. I tried reading it from the CSV but all the times zones are shifted to my local timezone. How can I make it read in as-is (in GMT)? Then I would like the resample to one minute intervals, HOWEVER, I would like to skip gaps which are larger than a user specified value. If this is not possible, is there way to resample to one minute, but in the gaps, put in an arbitrary value like 0.0?

 Data:
 Time,Data
 1354979750250,0.2343
 1354979755250,2.3433
 1354979710250,1.2343

 def date_utc(s):
     return parse(s, tzinfos=tzutc)

 x = read_csv("time2.csv", date_parser=date_utc, converters={'Time': lambda x:datetime.fromtimestamp(int(x)/1000.)}).set_index('Time')

推荐答案

将本地日期时间转换为GMT日期时间，如下所示:

Convert local datetime to GMT datetime like this:

gmtDatetime = localdatetime - datetime.timedelta(hours=8)

时区为+08(中国).

The time zone is +08 (China).

或使用"datetime.utcfromtimestamp":

Or using 'datetime.utcfromtimestamp':

classmethod datetime.utcfromtimestamp(timestamp)
classmethod datetime.fromtimestamp(timestamp, tz=None)

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