pandas 熊猫：转换多索引数据帧中的索引类型
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pandas: convert index type in multiindex dataframe
提问by Boosted_d16
Hi have a multiindex dataframe:
嗨，有一个多索引数据框：
tuples = [('YTA_Q3', 1), ('YTA_Q3', 2), ('YTA_Q3', 3), ('YTA_Q3', 4), ('YTA_Q3', 99), ('YTA_Q3', 96)]
# Index
index = pd.MultiIndex.from_tuples(tuples, names=['Questions', 'Values'])
# Columns
columns = pd.MultiIndex.from_tuples([('YTA_Q3', '@')], names=['Questions', 'Values'])
# Data
data = [29.014949,5.0260590000000001,
6.6269119999999999,
1.3565260000000001,
41.632221999999999,
21.279499999999999]
df1 = pd.DataFrame(data=data, index=index, columns=columns)
How do I convert the inner values of the df's index to str?
如何将 df 索引的内部值转换为 str？
My attempt:
我的尝试：
df1.index.astype(str)
returns a TypeError
返回一个类型错误
回答by Anton Protopopov
IIUC you need the last level of Multiindex. You could access it with levels:
IIUC 你需要最后一级的 Multiindex。您可以通过以下方式访问它levels：
df1.index.levels[-1].astype(str)
In [584]: df1.index.levels[-1].astype(str)
Out[584]: Index(['1', '2', '3', '4', '96', '99'], dtype='object', name='Values')
EDIT
编辑
You could set your inner level with set_levelsmethod of multiIndex:
您可以使用set_levelsmultiIndex 方法设置您的内部级别：
idx = df1.index
df1.index = df1.index.set_levels([idx.levels[:-1], idx.levels[-1].astype(str)])
回答by FuzzyDuck
I find the current pandas implementation a bit cumbersome, so I use this:
我发现当前的 Pandas 实现有点麻烦，所以我使用这个：
df1.index = pd.MultiIndex.from_tuples([(ix[0], str(ix[1])) for ix in df1.index.tolist()])
df1.index = pd.MultiIndex.from_tuples([(ix[0], str(ix[1])) for ix in df1.index.tolist()])
回答by Tajni
There was change in pandas and old way doesn't work properly.
大Pandas发生了变化，旧方式无法正常工作。
For me this worked.
对我来说这有效。
level_to_change = 1
df.index = df.index.set_levels(df.index.levels[level_to_change].astype(int), level=level_to_change)
