设置值多索引 Pandas
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Set value multiindex Pandas
提问by mortysporty
I'm a newbie to both Python and Pandas.
我是 Python 和 Pandas 的新手。
I am trying to construct a dataframe, and then later populate it with values.
我正在尝试构建一个数据框，然后用值填充它。
I have constructed my dataframe
我已经构建了我的数据框
from pandas import *
ageMin = 21
ageMax = 31
ageStep = 2
bins_sumins = [0, 10000, 20000]
bins_age = list(range(ageMin, ageMax, ageStep))
indeks_sex = ['M', 'F']
indeks_age = ['[{0}-{1})'.format(bins_age[i-1], bins_age[i]) for i in range(1, len(bins_age))]
indeks_sumins = ['[{0}-{1})'.format(bins_sumins[i-1], bins_sumins[i]) for i in range(1, len(bins_sumins))]
indeks = MultiIndex.from_product([indeks_age, indeks_sex, indeks_sumins], names=['Age', 'Sex', 'Sumins'])
cols = ['A', 'B', 'C', 'D']
df = DataFrame(data = 0, index = indeks, columns = cols)
So far all is well. I am able to assign value to a whole set of values
到目前为止一切都很好。我能够为一整套值赋值
>>> df['A']['[21-23)']['M'] = 1
>>> df
A B C D
Age Sex Sumins
[21-23) M [0-10000) 1 0 0 0
[10000-20000) 1 0 0 0
F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[23-25) M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[25-27) M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[27-29) M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
however, setting the value of one position only is a no go...
然而，只设置一个位置的值是不行的......
>>> df['B']['[21-23)']['M']['[10000-20000)'] = 2
>>> df
A B C D
Age Sex Sumins
[21-23) M [0-10000) 1 0 0 0
[10000-20000) 1 0 0 0
F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[23-25) M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[25-27) M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[27-29) M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[16 rows x 4 columns]
What is going on here? I am open to the idea that i have completely misunderstood how multiindexing works. Anyone?
这里发生了什么？我对我完全误解了多索引如何工作的想法持开放态度。任何人？
采纳答案by TomAugspurger
First off, have a look at the docs on chained indexing
首先，查看有关链式索引的文档
Second, read this about needing to sort MultiIndices.
其次，阅读有关需要对 MultiIndices 进行排序的内容。
That will get you to this solution:
这将使您获得此解决方案：
In [46]: df = df.sort_index()
In [47]: df.loc['[21-23)', 'M', '[10000-20000)'] = 2
In [48]: df
Out[48]:
A B C D
Age Sex Sumins
[21-23) F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
M [0-10000) 0 0 0 0
[10000-20000) 2 2 2 2
[23-25) F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[25-27) F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[27-29) F [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
M [0-10000) 0 0 0 0
[10000-20000) 0 0 0 0
[16 rows x 4 columns]
pandas .14will have some additional ways for slicing a MultiIndex.
pandas.14将有一些额外的方法来切片 MultiIndex。
