转换列的数据列举字典键值

Question

有没有更好的方法（以最少的代码的意义），它可以做如下：一列转换为枚举数值，所以应该去有点这样：

1. 得到设置项目在列
2. 做出enumrated字典与键值
3. 恢复与价值的关键
4. 使用键值的结果，而不是新数据列中的数据。

所以这里就是我今天做的，不知道是否有人能显示一个经典的方式做到这一点，所以我能避免写功能get_color_val：

import pandas as pd 
cars = pd.DataFrame({"car_name": ["BMW","BMW","ACCURA","ACCURA","ACCURA","BMW","BMW","BMW"],"color":["RED","RED","RED","RED","GREEN","BLACK","BLUE","BLUE"]}) 

color_dict = dict(enumerate(set(cars["color"]))) 
color_dict = dict((y,x) for x,y in color_dict.iteritems()) 

def get_color_val(row): 
    my_key = row["color"] 
    my_value = color_dict.get(my_key) 
    return my_value 

cars["color_val"] = cars.apply(get_color_val, axis=1) 
cars = cars.drop("color",1) 
print cars 

结果

Before------------ 
car_name color 
0  BMW RED 
1  BMW RED 
2 ACCURA RED 
3 ACCURA RED 
4 ACCURA GREEN 
5  BMW BLACK 
6  BMW BLUE 
7  BMW BLUE 


After------------ 
car_name color_val 
0  BMW   3 
1  BMW   3 
2 ACCURA   3 
3 ACCURA   3 
4 ACCURA   2 
5  BMW   1 
6  BMW   0 
7  BMW   0 

Answer 1

我会在这种情况下使用pd.factorize()：

In [8]: cars['color_val'] = pd.factorize(cars.color)[0] 

In [9]: cars 
Out[9]: 
    car_name color color_val 
0  BMW RED   0 
1  BMW RED   0 
2 ACCURA RED   0 
3 ACCURA RED   0 
4 ACCURA GREEN   1 
5  BMW BLACK   2 
6  BMW BLUE   3 
7  BMW BLUE   3