Pandas：在两个日期之间选择 DataFrame 行（日期时间索引）
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Pandas: Selecting DataFrame rows between two dates (Datetime Index)
提问by user3142067
I have a Pandas DataFrame with a DatetimeIndex and one column MSE Lossthe index is formatted as follows:
我有一个带有 DatetimeIndex 的 Pandas DataFrame 和一列MSE Loss索引的格式如下：
DatetimeIndex(['2015-07-16 07:14:41', '2015-07-16 07:14:48',
'2015-07-16 07:14:54', '2015-07-16 07:15:01',
'2015-07-16 07:15:07', '2015-07-16 07:15:14',...]
It includes several days.
它包括几天。
I want to select all the rows (all times) of a particular days without specifically knowing the actual time intervals.
For example: Between 2015-07-16 07:00:00and 2015-07-16 23:00:00
我想选择特定日期的所有行（所有时间），而无需特别了解实际时间间隔。例如：介于2015-07-16 07:00:00和之间2015-07-16 23:00:00
I tried the approach outlined here: here
我尝试了此处概述的方法：here
But df[date_from:date_to]
但 df[date_from:date_to]
outputs:
输出：
KeyError: Timestamp('2015-07-16 07:00:00')
So it wants exact indices. Furthermore, I don't have a datecolumn. Only an index with the dates.
所以它需要精确的索引。此外，我没有date专栏。只有带有日期的索引。
What is the best way to select a whole day by just providing a date 2015-07-16and then how could I select a specific time range within a particular day?
仅通过提供日期来选择一整天的最佳方法是什么2015-07-16，然后如何选择特定日期内的特定时间范围？
采纳答案by Andrew L
Option 1:
选项 1：
Sample df:
示例 df：
df
a
2015-07-16 07:14:41 12
2015-07-16 07:14:48 34
2015-07-16 07:14:54 65
2015-07-16 07:15:01 34
2015-07-16 07:15:07 23
2015-07-16 07:15:14 1
It looks like you're trying this without .loc(won't work without it):
看起来您正在尝试此操作.loc（没有它就无法工作）：
df.loc['2015-07-16 07:00:00':'2015-07-16 23:00:00']
a
2015-07-16 07:14:41 12
2015-07-16 07:14:48 34
2015-07-16 07:14:54 65
2015-07-16 07:15:01 34
2015-07-16 07:15:07 23
2015-07-16 07:15:14 1
Option 2:
选项2：
You can use boolean indexing on the index:
您可以在索引上使用布尔索引：
df[(df.index.get_level_values(0) >= '2015-07-16 07:00:00') & (df.index.get_level_values(0) <= '2015-07-16 23:00:00')]
回答by JrtPec
You can use truncate:
您可以使用truncate：
begin = pd.Timestamp('2015-07-16 07:00:00')
end = pd.Timestamp('2015-07-16 23:00:00')
df.truncate(before=begin, after=end)
