python - 如何使用循环从 Pandas 数据框中获取值？

Question

我想循环遍历 startDayValStr、endDayValStr、startTimeValStr、endTimeValStr 中的每个值并使用值作为 URL 字符串中的参数。我使用所有其他值作为我的 end 变量，即 06:00:00 是 startTimeValStr 值，07:00: 00 是一个 endTimeValStr 值。

如何正确构建循环以在 time_param 中使用这些变量？

我希望 time_param 看起来像这样 ?start=05-05-2019T06:00:00Z&end=05-05-2019T07:00:00Z

这是我当前的代码:

import pandas as pd

rng = pd.date_range(pd.Timestamp('2019-05-05' + ' ' + "'06:00:00'"),periods=25, freq='H')

 dtSeries =  pd.Series(rng.format())

 ddf = dtSeries.to_frame(name='Date')
 ddf['time'] = pd.to_datetime(ddf['Date'])
 dateDF = ddf['dates'] = ddf['time'].dt.date
 timeDF = ddf['dates'] = ddf['time'].dt.time

 startDayVal= dateDF[::2]
 endDayVal = dateDF[1::2]

 startTimeVal= timeDF[::2]
 endTimeVal = timeDF[1::2]

 startDayValStr = (startDayVal.to_string())
 endDayValStr =(endDayVal.to_string())

 startTimeValStr = (startTimeVal.to_string())
 endTimeValStr = (endTimeVal.to_string())

 for startDate, endDate, startTime, endTime in zip (startDayValStr, endDayValStr, startTimeValStr, endTimeValStr):
          time_param = '?start='+ startDate  +'T'+startTime + 'Z' + '&end='+ endDate  + endTime + 'Z'
          print time_param

Answer 1

如果使用 Python 3.x，请尝试 string.format方法，用 date.strftime :

rng = pd.date_range(pd.Timestamp('2019-05-05' + ' ' + "'06:00:00'"),
                    periods=25, freq='H')

for start, end in zip(rng[::2], rng[1::2]):
    time_param = '?start={}&end={}'.format(start.strftime('%d-%m-%YT%H:%M:%SZ'),
                                           end.strftime('%d-%m-%YT%H:%M:%SZ'))
    print(time_param)

[输出]

?start=05-05-2019T06:00:00Z&end=05-05-2019T07:00:00Z
?start=05-05-2019T08:00:00Z&end=05-05-2019T09:00:00Z
?start=05-05-2019T10:00:00Z&end=05-05-2019T11:00:00Z
?start=05-05-2019T12:00:00Z&end=05-05-2019T13:00:00Z
?start=05-05-2019T14:00:00Z&end=05-05-2019T15:00:00Z
?start=05-05-2019T16:00:00Z&end=05-05-2019T17:00:00Z
?start=05-05-2019T18:00:00Z&end=05-05-2019T19:00:00Z
?start=05-05-2019T20:00:00Z&end=05-05-2019T21:00:00Z
?start=05-05-2019T22:00:00Z&end=05-05-2019T23:00:00Z
?start=06-05-2019T00:00:00Z&end=06-05-2019T01:00:00Z
?start=06-05-2019T02:00:00Z&end=06-05-2019T03:00:00Z
?start=06-05-2019T04:00:00Z&end=06-05-2019T05:00:00Z