Question

我正在构建一种新方法来将DataFrame解析为与Vincent兼容的格式。这需要标准Index（Vincent无法解析MultiIndex）。

有没有办法检测大熊猫DataFrame是否有MultiIndex？

In: type(frame)
Out: pandas.core.index.MultiIndex

我试过了：

In: if type(result.index) is 'pandas.core.index.MultiIndex':
        print True
    else:
        print False
Out: False

如果我试着没有引用，我会得到：

NameError: name 'pandas' is not defined

任何帮助表示感谢。

（一旦我有MultiIndex，我就会重置索引并将两列合并为一个表示阶段的单个字符串值。）

Answer 1

您可以使用isinstance检查对象是否是类（或其子类）：

if isinstance(result.index, pandas.core.index.MultiIndex):

Answer 2

您可以使用nlevels来检查有多少个级别：

df.index.nlevels 
df.columns.nlevels

如果为nlevels > 1，则您的数据框肯定具有多个索引。

Answer 3

还有

len(result.index.names) > 1

但它比isinstance或者类型慢得多：

timeit(len(result.index.names) > 1)
The slowest run took 10.95 times longer than the fastest. This could mean that an intermediate result is being cached.
1000000 loops, best of 3: 1.12 µs per loop
In [254]:

timeit(isinstance(result.index, pd.MultiIndex))
The slowest run took 30.53 times longer than the fastest. This could mean that an intermediate result is being cached.
10000000 loops, best of 3: 177 ns per loop
In [252]:

)
timeit(type(result.index) == pd.MultiIndex)
The slowest run took 22.86 times longer than the fastest. This could mean that an intermediate result is being cached.
1000000 loops, best of 3: 200 ns per loop

Answer 4

也许最短的方式是if type(result.index)==pd.MultiIndex:

检测数据帧是否具有MultiIndex

4 个答案: