转换时区 pandas 数据框 [英] Converting time zone pandas dataframe
本文介绍了转换时区 pandas 数据框的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有数据:
Symbol bid ask
Timestamp
2014-01-01 21:55:34.378000 EUR/USD 1.37622 1.37693
2014-01-01 21:55:40.410000 EUR/USD 1.37624 1.37698
2014-01-01 21:55:47.210000 EUR/USD 1.37619 1.37696
2014-01-01 21:55:57.963000 EUR/USD 1.37616 1.37696
2014-01-01 21:56:03.117000 EUR/USD 1.37616 1.37694
时间戳记为格林尼治标准时间.有没有办法将其转换为东部?
The timestamp is of GMT. Is there a way to convert that to Eastern?
请注意,当我这样做:
data.index
我得到输出:
<class 'pandas.tseries.index.DatetimeIndex'>
[2014-01-01 21:55:34.378000, ..., 2014-01-01 21:56:03.117000]
Length: 5, Freq: None, Timezone: None
推荐答案
将索引(使用tz_localize
)本地化为UTC(以使Timestamps可以识别时区),然后转换为Eastern(使用tz_convert
):
Localize the index (using tz_localize
) to UTC (to make the Timestamps timezone-aware) and then convert to Eastern (using tz_convert
):
import pytz
eastern = pytz.timezone('US/Eastern')
df.index = index.tz_localize(pytz.utc).tz_convert(eastern)
例如:
For example:
import pandas as pd
import pytz
index = pd.date_range('20140101 21:55', freq='15S', periods=5)
df = pd.DataFrame(1, index=index, columns=['X'])
print(df)
# X
# 2014-01-01 21:55:00 1
# 2014-01-01 21:55:15 1
# 2014-01-01 21:55:30 1
# 2014-01-01 21:55:45 1
# 2014-01-01 21:56:00 1
# [5 rows x 1 columns]
print(df.index)
# <class 'pandas.tseries.index.DatetimeIndex'>
# [2014-01-01 21:55:00, ..., 2014-01-01 21:56:00]
# Length: 5, Freq: 15S, Timezone: None
eastern = pytz.timezone('US/Eastern')
df.index = index.tz_localize(pytz.utc).tz_convert(eastern)
print(df)
# X
# 2014-01-01 16:55:00-05:00 1
# 2014-01-01 16:55:15-05:00 1
# 2014-01-01 16:55:30-05:00 1
# 2014-01-01 16:55:45-05:00 1
# 2014-01-01 16:56:00-05:00 1
# [5 rows x 1 columns]
print(df.index)
# <class 'pandas.tseries.index.DatetimeIndex'>
# [2014-01-01 16:55:00-05:00, ..., 2014-01-01 16:56:00-05:00]
# Length: 5, Freq: 15S, Timezone: US/Eastern
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