python ， Pandas : tz_localize AmbiguousTimeError: Cannot infer dst time with non DST dates

Question

我正在尝试导入一些时间序列数据并将其转换为 UTC，以便我可以将其与另一个数据集合并。此数据似乎有 24 小时数据且没有 DST 调整。 This post给出了类似的答案，但他们只是放弃了这一行。我需要移动它，以便我可以将它与我的其他数据合并。

当我运行我的代码时:

df = pd.read_csv('http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2010/data/hourly/{}/{}_{}_solar.csv'.format(723898,723898,1998), usecols=["YYYY-MM-DD", "HH:MM (LST)","Meas Glo (Wh/m^2)","Meas Dir (Wh/m^2)","Meas Dif (Wh/m^2)"])

def clean_time(obj):
    hour = int(obj[0:-3])
    hour = str(hour - 1)
    if len(str(hour)) == 2:
        return hour+":00"
    else:
        return "0" + hour + ":00"

df['HH:MM (LST)'] = df['HH:MM (LST)'].apply(clean_time)
df['DateTime'] = df['YYYY-MM-DD'] + " " + df['HH:MM (LST)']
df = df.set_index(pd.DatetimeIndex(df['DateTime']))
df.drop(["YYYY-MM-DD", "HH:MM (LST)",'DateTime'],axis=1,inplace=True)
df.index = df.index.tz_localize('US/Pacific', ambiguous='infer')

我得到:

pytz.exceptions.AmbiguousTimeError: Cannot infer dst time from 1998-10-25 01:00:00 as there are no repeated times

如果我离开 ambiguous='raise'(默认值)，它会给我:

pytz.exceptions.NonExistentTimeError: 1998-04-05 02:00:00

所以我被困在夏令时的开始或结束。

我需要合并很多这些数据集(多年的多个站点)，所以我不想手动编写特定的时间来转移，但我仍然是新手，无法弄清楚我的下一步这里。

感谢帮助!

Answer 1

最小复制场景:

from datetime import datetime, timedelta

import pandas as pd


df = pd.DataFrame([[datetime(2019, 10, 27, 0) + timedelta(hours=i), i] for i in range(24)], columns=['dt', 'i']).set_index('dt')
df.index.tz_localize('Europe/Amsterdam', ambiguous='infer')

pytz.exceptions.AmbiguousTimeError: Cannot infer dst time from 2019-10-27 02:00:00 as there are no repeated times

解决方案:手动指定哪些日期时间对象必须被视为 DT(夏令时)或 DST(夏令时)。另见: https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.tz_localize.html

from datetime import datetime, timedelta
import numpy as np
import pandas as pd


df = pd.DataFrame([[datetime(2019, 10, 27, 0) + timedelta(hours=i), i] for i in range(24)], columns=['dt', 'i']).set_index('dt')
infer_dst = np.array([False] * df.shape[0])  # all False -> every row considered DT, alternative is True to indicate DST. The array must correspond to the iloc of df.index
df.index.tz_localize('Europe/Amsterdam', ambiguous=infer_dst)  # no error