pandas 将类别列表打印为列
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printing list of categories as a column
提问by PagMax
I am taking example from pandas documentation. Let us say I have a series after reading an excel file
我正在以Pandas文档为例。假设我在阅读了一个 excel 文件后有一个系列
import pandas as pd
s = pd.Series(["a","b","c","a"], dtype="category")
I know I can get different categories by
我知道我可以通过以下方式获得不同的类别
scat=s.cat.categories
print scat
For which I get
我得到
Index([u'a', u'b', u'c'], dtype='object')
I was wondering what is a good way to make this list appear as a column. Something like
我想知道什么是使此列表显示为列的好方法。就像是
a
b
c
I could get rid of u'by doing np.asarraybut still do not get the format I need.
我可以u'通过这样做来摆脱，np.asarray但仍然没有得到我需要的格式。
回答by Alexander
I'm not sure by what you mean when you say 'appear' as a column.
当您说“作为列出现”时，我不确定您的意思。
You can create a list instead of an index via:
您可以通过以下方式创建列表而不是索引：
>>> s.cat.categories.tolist()
['a', 'b', 'c']
Or you can simply print them out in a column structure using a for loop:
或者您可以使用 for 循环简单地将它们打印在列结构中：
for c in s.cat.categories:
print c
a
b
c
Or you could create a series (or dataframe):
或者您可以创建一个系列（或数据框）：
>>> pd.Series(s.cat.categories)
0 a
1 b
2 c
dtype: object
>>> pd.DataFrame(s.cat.categories)
0
0 a
1 b
2 c
回答by jezrael
I think it is no problem - 'u'means unicodestring:
我认为没问题 -'u'表示unicode字符串：
s = pd.Series(["a","b","c","a"], dtype="category")
print s
0 a
1 b
2 c
3 a
dtype: category
Categories (3, object): [a, b, c]
scat=s.cat.categories
print scat
Index([u'a', u'b', u'c'], dtype='object')
print scat[0]
a
print type(scat[0])
<type 'str'>
If you want print column without loop use numpy reshape:
如果您想打印没有循环的列，请使用numpy reshape：
print len(scat)
3
print scat.values.reshape(len(scat),1)
[['a']
['b']
['c']]
