python到pandas_python-将 pandas 值映射到分类级别

pandas 新手. R用户使用拆分,应用,合并模式来分析子群体.例如性别,1 =“男性”,2 =“女性”,9 =“未知”.

我有一个 dataframe ,其中有一个天列,其20,000的值是从1到7的整数,对应于“ Mon”,“ Tue”等.我需要使用标签而不是它们的原始int值进行分类.

我的第一次尝试是尝试.astype(“ category”)：

import numpy as np

import pandas as pd

dow = pd.DataFrame({'labels': ("Sunday","Monday","Tuesday",

"Wednesday", "Thursday", "Friday", "Saturday")})

data = pd.DataFrame({'value': [1, 1, 2, 3, 4, 7, 8, 9, 0]})

data['formtatted'] = dow['labels'].astype('category')

data

value formtatted

0 1 Sunday

1 1 Monday

2 2 Tuesday

3 3 Wednesday

4 4 Thursday

5 7 Friday

6 8 Saturday

7 9 NaN

8 0 NaN

我希望标签映射到两次给定“ Sunday”的整数值,而不是获得循环列表的行为.

接下来,我尝试使用.factorize属性,例如：

data2 = pd.DataFrame({'values': [1, 1, 2, 3, 4, 7, 8, 9, 0]})

dow2 = pd.DataFrame({'labels': ["Sunday","Monday","Tuesday",

"Wednesday", "Thursday", "Friday", "Saturday"]})

dow_cat = pd.factorize(dow2['labels'])

dow_cat

(array([0, 1, 2, 3, 4, 5, 6]),

Index(['Sunday', 'Monday', 'Tuesday', 'Wednesday', 'Thursday', 'Friday',

'Saturday'], dtype='object'))

看起来很有希望.

data2['labels'] = dow_cat[0]

但是会引发错误：值的长度与索引的长度不匹配

说明：无法在创建时指定标签.之后使用s.cat.rename_categories(new_labels).

很公平：

dow3 = pd.DataFrame({'values': [1, 2, 3, 4, 5, 6, 7]},

dtype="category")

dow3.values = dow3['values'].cat.rename_categories(["Sunday",

"Monday","Tuesday","Wednesday",

"Thursday", "Friday", "Saturday"])

df3['formatted'] = dow3["values"]

df3

values formatted

0 1 Sunday

1 1 Monday

2 2 Tuesday

3 3 Wednesday

4 4 Thursday

5 7 Friday

6 8 Saturday

7 9 NaN

8 0 NaN

我从哪儿开始的,具有循环列表的行为.

我敢打赌,我已经忽略了显而易见的事情,但这使我难以理解.关于我从这里去哪里的建议？