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python - 检测日期浓度（python中的列表）

问题描述

我有一个名为 Python 的列表，array_my_date我需要检测日期的浓度。

标准是：

array_my_date = []
array_my_date.append(pd.to_datetime('2013-06-24 00:00:00'))
array_my_date.append(pd.to_datetime('2013-06-26 00:00:00'))
array_my_date.append(pd.to_datetime('2013-06-27 00:00:00'))
array_my_date.append(pd.to_datetime('2013-06-29 00:00:00'))
array_my_date.append(pd.to_datetime('2013-07-01 00:00:00'))
array_my_date.append(pd.to_datetime('2013-07-03 00:00:00'))
array_my_date.append(pd.to_datetime('2013-07-04 00:00:00'))
array_my_date.append(pd.to_datetime('2013-07-06 00:00:00'))
array_my_date.append(pd.to_datetime('2013-07-07 00:00:00'))
array_my_date.append(pd.to_datetime('2013-07-08 00:00:00'))

array_my_date.append(pd.to_datetime('2015-03-01 00:00:00'))
array_my_date.append(pd.to_datetime('2015-03-04 00:00:00'))

array_my_date.append(pd.to_datetime('2017-09-29 00:00:00'))
array_my_date.append(pd.to_datetime('2017-10-02 00:00:00'))
array_my_date.append(pd.to_datetime('2017-10-06 00:00:00'))
array_my_date.append(pd.to_datetime('2017-10-07 00:00:00'))
array_my_date.append(pd.to_datetime('2017-10-08 00:00:00'))
array_my_date.append(pd.to_datetime('2017-10-09 00:00:00'))

array_my_date.append(pd.to_datetime('2018-12-09 00:00:00'))

预期的输出是第一个集中的日期。那是：

[Timestamp('2013-06-24 00:00:00'), Timestamp('2017-09-29 00:00:00')]

标签： python

解决方案

首先，确保日期列表已排序：

dates = sorted(array_my_date)

然后，逐渐建立一个浓度列表：

concentrations = [[dates[0]]]                        # initialize our memory with the first date
for date in dates[1:]:                               # iterate through the rest of the dates
    last_date = concentrations[-1][-1]               # look at the last date we added
    if (date - last_date) <= pd.Timedelta(days=25):  # is it close enough to be in the same group?
        concentrations[-1].append(date)              # if so, then put it in the same group
    else:                                            # otherwise,
        concentrations.append([date])                # make a new group with it at the head

这会产生以下结果：

>>> pprint.pprint(concentrations)
[[Timestamp('2013-06-24 00:00:00'),
  Timestamp('2013-06-26 00:00:00'),
  Timestamp('2013-06-27 00:00:00'),
  Timestamp('2013-06-29 00:00:00'),
  Timestamp('2013-07-01 00:00:00'),
  Timestamp('2013-07-03 00:00:00'),
  Timestamp('2013-07-04 00:00:00'),
  Timestamp('2013-07-06 00:00:00'),
  Timestamp('2013-07-07 00:00:00'),
  Timestamp('2013-07-08 00:00:00')],
 [Timestamp('2015-03-01 00:00:00'), Timestamp('2015-03-04 00:00:00')],
 [Timestamp('2017-09-29 00:00:00'),
  Timestamp('2017-10-02 00:00:00'),
  Timestamp('2017-10-06 00:00:00'),
  Timestamp('2017-10-07 00:00:00'),
  Timestamp('2017-10-08 00:00:00'),
  Timestamp('2017-10-09 00:00:00')],
 [Timestamp('2018-12-09 00:00:00')]]

然后，您可以通过执行以下操作来获取每个时间段中的最早日期

earliest_of_each = [group[0] for group in concentrations]

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