在 pandas 中使用元组作为索引键时，如何“通过传入类别参数显式指定类别顺序”？

我一直在试图弄清楚如何使这些元组索引键pandas但我收到错误。

我如何使用错误中的建议pd.Categorical下面修复这个错误？

我知道我可以转换为字符串，但我很好奇错误消息中的建议是什么意思？

当我运行它时，效果非常好0.22.0。我已经开了一个GitHub问题 https://github.com/pandas-dev/pandas/issues/22832为此，如果有人想看到正确的输出0.22.0.

我想更新我的 pandas 并妥善处理这个问题。

import sys; sys.version
# '3.6.4 |Anaconda, Inc.| (default, Jan 16 2018, 12:04:33) \n[GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)]'
import pandas as pd; pd.__version__
# '0.23.4'
index = [(('criterion', 'gini'), ('max_features', 'log2'), ('min_samples_leaf', 1)), (('criterion', 'gini'), ('max_features', 'log2'), ('min_samples_leaf', 2)), (('criterion', 'gini'), ('max_features', 'log2'), ('min_samples_leaf', 3)), (('criterion', 'gini'), ('max_features', 'log2'), ('min_samples_leaf', 5)), (('criterion', 'gini'), ('max_features', 'log2'), ('min_samples_leaf', 8)), (('criterion', 'gini'), ('max_features', 'sqrt'), ('min_samples_leaf', 1)), (('criterion', 'gini'), ('max_features', 'sqrt'), ('min_samples_leaf', 2)), (('criterion', 'gini'), ('max_features', 'sqrt'), ('min_samples_leaf', 3)), (('criterion', 'gini'), ('max_features', 'sqrt'), ('min_samples_leaf', 5)), (('criterion', 'gini'), ('max_features', 'sqrt'), ('min_samples_leaf', 8)), (('criterion', 'gini'), ('max_features', None), ('min_samples_leaf', 1)), (('criterion', 'gini'), ('max_features', None), ('min_samples_leaf', 2)), (('criterion', 'gini'), ('max_features', None), ('min_samples_leaf', 3)), (('criterion', 'gini'), ('max_features', None), ('min_samples_leaf', 5)), (('criterion', 'gini'), ('max_features', None), ('min_samples_leaf', 8)), (('criterion', 'gini'), ('max_features', 0.382), ('min_samples_leaf', 1)), (('criterion', 'gini'), ('max_features', 0.382), ('min_samples_leaf', 2)), (('criterion', 'gini'), ('max_features', 0.382), ('min_samples_leaf', 3)), (('criterion', 'gini'), ('max_features', 0.382), ('min_samples_leaf', 5)), (('criterion', 'gini'), ('max_features', 0.382), ('min_samples_leaf', 8)), (('criterion', 'entropy'), ('max_features', 'log2'), ('min_samples_leaf', 1)), (('criterion', 'entropy'), ('max_features', 'log2'), ('min_samples_leaf', 2)), (('criterion', 'entropy'), ('max_features', 'log2'), ('min_samples_leaf', 3)), (('criterion', 'entropy'), ('max_features', 'log2'), ('min_samples_leaf', 5)), (('criterion', 'entropy'), ('max_features', 'log2'), ('min_samples_leaf', 8)), (('criterion', 'entropy'), ('max_features', 'sqrt'), ('min_samples_leaf', 1)), (('criterion', 'entropy'), ('max_features', 'sqrt'), ('min_samples_leaf', 2)), (('criterion', 'entropy'), ('max_features', 'sqrt'), ('min_samples_leaf', 3)), (('criterion', 'entropy'), ('max_features', 'sqrt'), ('min_samples_leaf', 5)), (('criterion', 'entropy'), ('max_features', 'sqrt'), ('min_samples_leaf', 8)), (('criterion', 'entropy'), ('max_features', None), ('min_samples_leaf', 1)), (('criterion', 'entropy'), ('max_features', None), ('min_samples_leaf', 2)), (('criterion', 'entropy'), ('max_features', None), ('min_samples_leaf', 3)), (('criterion', 'entropy'), ('max_features', None), ('min_samples_leaf', 5)), (('criterion', 'entropy'), ('max_features', None), ('min_samples_leaf', 8)), (('criterion', 'entropy'), ('max_features', 0.382), ('min_samples_leaf', 1)), (('criterion', 'entropy'), ('max_features', 0.382), ('min_samples_leaf', 2)), (('criterion', 'entropy'), ('max_features', 0.382), ('min_samples_leaf', 3)), (('criterion', 'entropy'), ('max_features', 0.382), ('min_samples_leaf', 5)), (('criterion', 'entropy'), ('max_features', 0.382), ('min_samples_leaf', 8))]
len(index)
# 40
pd.Index(index)
Traceback (most recent call last):
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/algorithms.py", line 635, in factorize
    order = uniques.argsort()
TypeError: '<' not supported between instances of 'NoneType' and 'str'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/sorting.py", line 451, in safe_sort
    sorter = values.argsort()
TypeError: '<' not supported between instances of 'NoneType' and 'str'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 345, in __init__
    codes, categories = factorize(values, sort=True)
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/util/_decorators.py", line 178, in wrapper
    return func(*args, **kwargs)
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/algorithms.py", line 643, in factorize
    assume_unique=True)
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/sorting.py", line 455, in safe_sort
    ordered = sort_mixed(values)
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/sorting.py", line 441, in sort_mixed
    nums = np.sort(values[~str_pos])
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/numpy/core/fromnumeric.py", line 847, in sort
    a.sort(axis=axis, kind=kind, order=order)
TypeError: '<' not supported between instances of 'NoneType' and 'str'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/indexes/base.py", line 449, in __new__
    data, names=name or kwargs.get('names'))
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/indexes/multi.py", line 1330, in from_tuples
    return MultiIndex.from_arrays(arrays, sortorder=sortorder, names=names)
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/indexes/multi.py", line 1274, in from_arrays
    labels, levels = _factorize_from_iterables(arrays)
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 2543, in _factorize_from_iterables
    return map(list, lzip(*[_factorize_from_iterable(it) for it in iterables]))
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 2543, in <listcomp>
    return map(list, lzip(*[_factorize_from_iterable(it) for it in iterables]))
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 2515, in _factorize_from_iterable
    cat = Categorical(values, ordered=True)
  File "/Users/jespinoz/anaconda/envs/py3_testing/lib/python3.6/site-packages/pandas/core/arrays/categorical.py", line 351, in __init__
    raise TypeError("'values' is not ordered, please "
TypeError: 'values' is not ordered, please explicitly specify the categories order by passing in a categories argument

我能找到的最接近你想做的事情是：pd.DataFrame(index, dtype='category').set_index([0, 1, 2]).index

返回以下内容：

MultiIndex(levels=[[('criterion', 'entropy'), ('criterion', 'gini')], [('max_features', 'log2'), ('max_features', 'sqrt'), ('max_features', None), ('max_features', 0.382)], [('min_samples_leaf', 1), ('min_samples_leaf', 2), ('min_samples_leaf', 3), ('min_samples_leaf', 5), ('min_samples_leaf', 8)]],
       labels=[[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3], [0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4]],
       names=[0, 1, 2])