Pandas 以索引列为条件

我有一个数据框，并将索引设置为DateTime列：

data['DateTime'] = pandas.to_datetime (data['DateTime'])
data = data.set_index('DateTime')

我需要对数据进行插值。然而，这个索引后来阻止了我这样做

data = data[pandas.to_datetime (data['DateTime']) <= cutoff]

---

data=data[pandas.to_datetime（data['datetime']）似乎您需要
.index
进行比较
DatetimeIndex
：

data['DateTime'] = pandas.to_datetime (data['DateTime'])
data = data.set_index('DateTime')
data = data[data.index <= cutoff]

样本：

rng = pd.date_range('2017-04-03', periods=10)
data = pd.DataFrame({'a': range(10)}, index=rng)  
print (data)
            a
2017-04-03  0
2017-04-04  1
2017-04-05  2
2017-04-06  3
2017-04-07  4
2017-04-08  5
2017-04-09  6
2017-04-10  7
2017-04-11  8
2017-04-12  9

cutoff = '2017-04-08'
data1 = data[data.index <= cutoff]
print (data1)
            a
2017-04-03  0
2017-04-04  1
2017-04-05  2
2017-04-06  3
2017-04-07  4
2017-04-08  5

data1 = data1.loc[:cutoff]
print (data1)
            a
2017-04-03  0
2017-04-04  1
2017-04-05  2
2017-04-06  3
2017-04-07  4
2017-04-08  5

太棒了。这会花我好几天的时间，我仍然不会尝试。我会在10分钟内接受答案。谢谢，@piRSquared。两种方法的性能有差异吗？@John没有。它们应该差不多。
rng = pd.date_range('2017-04-03', periods=10)
data = pd.DataFrame({'a': range(10)}, index=rng)  
print (data)
            a
2017-04-03  0
2017-04-04  1
2017-04-05  2
2017-04-06  3
2017-04-07  4
2017-04-08  5
2017-04-09  6
2017-04-10  7
2017-04-11  8
2017-04-12  9

cutoff = '2017-04-08'
data1 = data[data.index <= cutoff]
print (data1)
            a
2017-04-03  0
2017-04-04  1
2017-04-05  2
2017-04-06  3
2017-04-07  4
2017-04-08  5

data1 = data1.loc[:cutoff]
print (data1)
            a
2017-04-03  0
2017-04-04  1
2017-04-05  2
2017-04-06  3
2017-04-07  4
2017-04-08  5

data1 = data1[:cutoff]
print (data1)
            a
2017-04-03  0
2017-04-04  1
2017-04-05  2
2017-04-06  3
2017-04-07  4
2017-04-08  5