[英]Pandas dataframe with column of timestamps and timezones
I have a pandas dataframe with a column of timestamps and a column of timezones the timestamps are in. What's the best way to convert all these timestamps to UTC time? 我有一个pandas数据帧,其中包含一列时间戳和一组时间戳所在的时区。将所有这些时间戳转换为UTC时间的最佳方法是什么?
Sample data in csv: csv中的示例数据:
0,2000-01-28 16:47:00,America/Chicago
1,2000-01-29 16:48:00,America/Chicago
2,2000-01-30 16:49:00,America/Los_Angeles
3,2000-01-31 16:50:00,America/Chicago
4,2000-01-01 16:50:00,America/New_York
This can be efficiently done by converting a single tz at a time (but since we have many, groupby already separates these out). 这可以通过一次转换一个tz来有效地完成(但由于我们有很多,groupby已经将它们分开)。 These are local times (IOW in the given timezone), so
tz_localize
makes these tz-aware. 这些是本地时间(在给
tz_localize
IOW),因此tz_localize
使这些tz感知。 Then when we combine them these are auto-magically converted to UTC. 然后,当我们将它们组合在一起时,它们会自动神奇地转换为UTC。
Note this is on master/0.17.0, releasing soon. 请注意,这是在master / 0.17.0上,很快就会发布。 Soln for < 0.17.0 is below
溶解<0.17.0以下
In [19]: df = read_csv(StringIO(data),header=None, names=['value','date','tz'])
In [20]: df.dtypes
Out[20]:
value int64
date object
tz object
dtype: object
In [21]: df
Out[21]:
value date tz
0 0 2000-01-28 16:47:00 America/Chicago
1 1 2000-01-29 16:48:00 America/Chicago
2 2 2000-01-30 16:49:00 America/Los_Angeles
3 3 2000-01-31 16:50:00 America/Chicago
4 4 2000-01-01 16:50:00 America/New_York
In [22]: df['utc'] = df.groupby('tz').date.apply(
lambda x: pd.to_datetime(x).dt.tz_localize(x.name))
In [23]: df
Out[23]:
value date tz utc
0 0 2000-01-28 16:47:00 America/Chicago 2000-01-28 22:47:00
1 1 2000-01-29 16:48:00 America/Chicago 2000-01-29 22:48:00
2 2 2000-01-30 16:49:00 America/Los_Angeles 2000-01-31 00:49:00
3 3 2000-01-31 16:50:00 America/Chicago 2000-01-31 22:50:00
4 4 2000-01-01 16:50:00 America/New_York 2000-01-01 21:50:00
In [24]: df.dtypes
Out[24]:
value int64
date object
tz object
utc datetime64[ns]
dtype: object
In < 0.17.0, need to: 在<0.17.0,需要:
df['utc'] = df['utc'].dt.tz_localize(None)
to convert to UTC 转换为UTC
In general: combine the 2 csv time columns during the import (or before). 通常: 在导入期间 (或之前)组合2个csv 时间列。 This can be done with a small lambda-function.
这可以通过一个小的lambda函数来完成。
To convert (parse) that combined info, several options exist. 要转换(解析)组合信息,存在多个选项。 Most are described here or in the pandas-docs.
大多数都在这里或pandas-docs中描述。 Personally I like the
utils.parse
one. 我个人喜欢
utils.parse
。
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