python - Convert Pandas dateTime Index Values to Numpy Datetimes

Question

Starting with a pandas Dataframe with datetimes as the index, I create 2 lists:

• datetimes of all rows
• dates of all rows

My code below works but is slow. Is there a faster way of doing this? I have tried multiple approaches but all are slow.

dateTimeFormat = '%Y-%m-%dT%H:%M:%S'
barDates = []
barDateTimes = []
for numpyDatetime64 in bars.index.values: # 'bars' is a pandas dataframe
    dateTime = datetime.datetime.strptime(str(numpyDatetime64).split('.')[0], dateTimeFormat)
    date = dateTime.date()
    barDateTimes.append(dateTime)
    barDates.append(date)

Per Andrej's suggestion, here is an example of the input dataframe:

                            A         B        C  ...         T          U         V
dateTime                                          ...                               
2010-05-13 09:31:00   117.130   117.240   117.13  ...  121.2400   121.2500  172429.0
2010-05-13 09:32:00   117.180   117.220   117.16  ...  121.1800   121.2700   98480.0
2010-05-13 09:33:00   117.200   117.280   117.19  ...  121.2701   121.3100   41255.0
2010-05-13 09:34:00   117.200   117.220   117.01  ...  121.2700   121.3999  250893.0
2010-05-13 09:35:00   117.100   117.130   116.83  ...  121.2500   121.2505   69952.0
...                       ...       ...      ...  ...       ...        ...       ...
2019-10-04 15:56:00   294.330   294.560   294.33  ...  141.7713   141.7800   15407.0
2019-10-04 15:57:00   294.550   294.630   294.50  ...  141.7750   141.7900   16815.0
2019-10-04 15:58:00   294.515   294.520   294.40  ...  141.7950   141.8700   39316.0
2019-10-04 15:59:00   294.485   294.530   294.38  ...  141.8600   141.8800   46623.0
2019-10-04 16:00:00   294.515   294.515   294.31  ...  141.8500   141.9300   89639.0

标签： pythonpandasnumpydatetime

Answer 1

以下代码可能会起作用：

import pandas as pd
ix = pd.date_range(start="2010-05-13 09:31:00", end="2010-05-13 09:35:00", freq='min')
ix
DatetimeIndex(['2010-05-13 09:31:00', '2010-05-13 09:32:00',
               '2010-05-13 09:33:00', '2010-05-13 09:34:00',
               '2010-05-13 09:35:00'],
              dtype='datetime64[ns]', freq='T')

barDateTimes, barDates = ix.to_pydatetime().tolist(), ix.date.tolist()
barDateTimes, barDates
([datetime.datetime(2010, 5, 13, 9, 31),
  datetime.datetime(2010, 5, 13, 9, 32),
  datetime.datetime(2010, 5, 13, 9, 33),
  datetime.datetime(2010, 5, 13, 9, 34),
  datetime.datetime(2010, 5, 13, 9, 35)],
 [datetime.date(2010, 5, 13),
  datetime.date(2010, 5, 13),
  datetime.date(2010, 5, 13),
  datetime.date(2010, 5, 13),
  datetime.date(2010, 5, 13)])

您可能还需要考虑是否真的需要 Python 日期时间和 Pandas 时间戳。