Question

def age_range(age):
    if  age <= 18:
        return 'Minors'
    elif age >= 19 & age < 63:
        return 'Adults'
    elif age >= 63 & age < 101:
        return 'Senior Citizen'
    else:
        return 'Age Unknown'

titanic_data_df["PassengerType"] = titanic_data_df[['Age']].apply(age_range, axis = 1)

titanic_data_df.head()

当我尝试向现有数据框（titanic_data_df）添加新列时出现以下错误：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-466-741f5646101e> in <module>()
      1 #create a new df with just age and distinguish each passenger as minor, adult or senior citizen
----> 2 titanic_data_df["PassengerType"] =     titanic_data_df[['Age']].apply(age_range, axis = 1)
      3 
      4 titanic_data_df.head()

C:\Users\test\Anaconda2\envs\py27DAND\lib\site-packages\pandas\core\frame.pyc in apply(self, func, axis, broadcast, raw, reduce, args, **kwds)
   4161                     if reduce is None:
   4162                         reduce = True
-> 4163                     return self._apply_standard(f, axis, reduce=reduce)
   4164             else:
   4165                 return self._apply_broadcast(f, axis)

C:\Users\test\Anaconda2\envs\py27DAND\lib\site-packages\pandas\core\frame.pyc in _apply_standard(self, func, axis, ignore_failures, reduce)
   4257             try:
   4258                 for i, v in enumerate(series_gen):
  -> 4259                     results[i] = func(v)
   4260                     keys.append(v.name)
   4261             except Exception as e:

 <ipython-input-465-e62ccbeee80e> in age_range(age)
      1 def age_range(age):
----> 2     if  age <= 18:
      3         return 'Minors'
      4     elif age >= 19 & age < 63:
      5         return 'Adults'

C:\Users\test\Anaconda2\envs\py27DAND\lib\site-packages\pandas\core\generic.pyc in __nonzero__(self)
    915         raise ValueError("The truth value of a {0} is ambiguous. "
    916                          "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
--> 917                          .format(self.__class__.__name__))
    918 
    919     __bool__ = __nonzero__

 ValueError: ('The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().', u'occurred at index 0')

从我到目前为止所读到的内容，它与我上面方法中的if ... else语句有关。我无法弄清楚它是什么。任何帮助表示赞赏。谢谢。

Answer 1

当您选择列titanic_data_df[['Age']]时（请注意双方括号），您实际上正在获取包含单个列的DataFrame。在这种情况下，apply()函数将单个元素Series传递给函数age_range。

请改为尝试：

titanic_data_df["PassengerType"] = titanic_data_df['Age'].apply(age_range)

Answer 2

Pandas cut功能可以让您更轻松。首先，我将构建一个数据框来演示cut函数。

titanic_data_df = pd.DataFrame(data=[[13, 'Male'], [14, 'Female'], [38, 'Female'], [72, 'Male'], [33, 'Female'], [80, 'Male'], [34, 'Male'], [15, 'Female'], [27, 'Female'],[23, 'Male'], [64, 'Female'], [38, 'Female'], [12, 'Male'], [32, 'Female'], [21, 'Male'], [66, 'Male'], [73, 'Female'], [22, 'Female']], columns=['Age', 'Sex'])
print(titanic_data_df)
     Age     Sex
0    13    Male
1    14  Female
2    38  Female
3    72    Male
4    33  Female
5    80    Male
6    34    Male
7    15  Female
8    27  Female
9    23    Male
10   64  Female
11   38  Female
12   12    Male
13   32  Female
14   21    Male
15   66    Male
16   73  Female
17   22  Female

然后，我只需应用cut函数：

bins = ['Minors', 'Adults', 'Senior Citizens']
titanic_data_df["PassengerType"] = pd.cut(titanic_data_df.Age, [0, 18, 63, 101], labels=bins)
print(titanic_data_df)
     Age     Sex       PassengerType
0    13    Male          Minors
1    14  Female          Minors
2    38  Female          Adults
3    72    Male  Senior Citizen
4    33  Female          Adults
5    80    Male  Senior Citizen
6    34    Male          Adults
7    15  Female          Minors
8    27  Female          Adults
9    23    Male          Adults
10   64  Female  Senior Citizen
11   38  Female          Adults
12   12    Male          Minors
13   32  Female          Adults
14   21    Male          Adults
15   66    Male  Senior Citizen
16   73  Female  Senior Citizen
17   22  Female          Adults

使用apply（）方法时的ValueError

2 个答案: