如何从索引中删除数据点

Question

我是 Python 的新手，我有一个包含日期的数据集 S2。当我使用命令时：

available_datapoints = S2.index,

然后

print(available_datapoints)

产量：

<class 'pandas.tseries.index.DatetimeIndex'>
[2017-05-07 00:00:00+00:00, ..., 2017-07-27 23:50:00+00:00]
Length: 11808, Freq: 10T, Timezone: UTC stop

但是，我想开始 2017-11-07 00:00:00+00:00 而不是 2017-05-07 00:00:00+00:00，而不是 2017-07-27 23:50:00+00:00，我想停止 2017-07-22 23:50:00+00:00。

有人知道我怎么改吗？

Answer 1

我想你可以使用 DataFrame.truncate:

#Sample data
S2 = pd.DataFrame({'a': range(11808)}, 
                   index=pd.date_range(start='2017-05-07',periods=11808, freq='10T'))
print (S2.head())
                     a
2017-05-07 00:00:00  0
2017-05-07 00:10:00  1
2017-05-07 00:20:00  2
2017-05-07 00:30:00  3
2017-05-07 00:40:00  4

print (S2.tail())
                         a
2017-07-27 23:10:00  11803
2017-07-27 23:20:00  11804
2017-07-27 23:30:00  11805
2017-07-27 23:40:00  11806
2017-07-27 23:50:00  11807

S2 = S2.truncate(before='2017-07-11', after='2017-07-22 23:50:00')
print (S2.head())
                        a
2017-07-11 00:00:00  9360
2017-07-11 00:10:00  9361
2017-07-11 00:20:00  9362
2017-07-11 00:30:00  9363
2017-07-11 00:40:00  9364

print (S2.tail())
                         a
2017-07-22 23:10:00  11083
2017-07-22 23:20:00  11084
2017-07-22 23:30:00  11085
2017-07-22 23:40:00  11086
2017-07-22 23:50:00  11087

Answer 2

假设您真的想从“2017-07-11”开始而不是“2017-11-07”（在您的结束日期“2017-07-23”之后），您可以使用 Partial String Indexing:

设置

df = pd.DataFrame(index = pd.date_range('2017-05-07 00:00:00+00:00','2017-07-27 23:50:00+00:00', freq='10T'))
print(df.index)

DatetimeIndex(['2017-05-07 00:00:00+00:00', '2017-05-07 00:10:00+00:00',
               '2017-05-07 00:20:00+00:00', '2017-05-07 00:30:00+00:00',
               '2017-05-07 00:40:00+00:00', '2017-05-07 00:50:00+00:00',
               '2017-05-07 01:00:00+00:00', '2017-05-07 01:10:00+00:00',
               '2017-05-07 01:20:00+00:00', '2017-05-07 01:30:00+00:00',
               ...
               '2017-07-27 22:20:00+00:00', '2017-07-27 22:30:00+00:00',
               '2017-07-27 22:40:00+00:00', '2017-07-27 22:50:00+00:00',
               '2017-07-27 23:00:00+00:00', '2017-07-27 23:10:00+00:00',
               '2017-07-27 23:20:00+00:00', '2017-07-27 23:30:00+00:00',
               '2017-07-27 23:40:00+00:00', '2017-07-27 23:50:00+00:00'],
              dtype='datetime64[ns, UTC]', length=11808, freq='10T')

现在，使用带切片的部分字符串索引：

df1 = df['2017-07-11':'2017-07-22 23:50:00']
print(df_1.index)

输出：一个较小的数据帧，时间在 2017-07-11 之前和 2017-07-22 之后 23:50 丢弃：

DatetimeIndex(['2017-07-11 00:00:00+00:00', '2017-07-11 00:10:00+00:00',
               '2017-07-11 00:20:00+00:00', '2017-07-11 00:30:00+00:00',
               '2017-07-11 00:40:00+00:00', '2017-07-11 00:50:00+00:00',
               '2017-07-11 01:00:00+00:00', '2017-07-11 01:10:00+00:00',
               '2017-07-11 01:20:00+00:00', '2017-07-11 01:30:00+00:00',
               ...
               '2017-07-22 22:20:00+00:00', '2017-07-22 22:30:00+00:00',
               '2017-07-22 22:40:00+00:00', '2017-07-22 22:50:00+00:00',
               '2017-07-22 23:00:00+00:00', '2017-07-22 23:10:00+00:00',
               '2017-07-22 23:20:00+00:00', '2017-07-22 23:30:00+00:00',
               '2017-07-22 23:40:00+00:00', '2017-07-22 23:50:00+00:00'],
              dtype='datetime64[ns, UTC]', length=1728, freq='10T')

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