我有 2 个数据框。第一个数据框有数字作为索引。第二个数据框以日期时间作为索引。切片运算符 (:) 在这些数据帧上的行为不同。
案例一
>>> df = pd.DataFrame({'A':[1,2,3]}, index=[0,1,2])
>>> df
A
0 1
1 2
2 3
>>> df [0:2]
A
0 1
1 2
案例二
>>> a = dt.datetime(2000,1,1)
>>> b = dt.datetime(2000,1,2)
>>> c = dt.datetime(2000,1,3)
>>> df = pd.DataFrame({'A':[1,2,3]}, index = [a,b,c])
>>> df
A
2000-01-01 1
2000-01-02 2
2000-01-03 3
>>> df[a:b]
A
2000-01-01 1
2000-01-02 2
为什么最后一行在情况 1 中被排除在外，而在情况 2 中却没有？
请您参考如下方法:
不要使用它，最好使用 loc 来保持一致性:
df = pd.DataFrame({'A':[1,2,3]}, index=[0,1,2])
print (df.loc[0:2])
A
0 1
1 2
2 3
a = datetime.datetime(2000,1,1)
b = datetime.datetime(2000,1,2)
c = datetime.datetime(2000,1,3)
df = pd.DataFrame({'A':[1,2,3]}, index = [a,b,c])
print (df.loc[a:b])
A
2000-01-01 1
2000-01-02 2
为什么省略最后一行的原因可能在 docs 中找到:
With DataFrame, slicing inside of [] slices the rows. This is provided largely as a convenience since it is such a common operation.
print (df[0:2])
A
0 1
1 2
用于按日期时间选择 exact indexing被使用:
... In contrast, indexing with Timestamp or datetime objects is exact, because the objects have exact meaning. These also follow the semantics of including both endpoints.
