python - 从每行的最大值中减去最小值，Python Pandas DataFrame

Question

我有一个按州名和县名索引的人口普查数据集，我想遍历每一行以查找标记为“每年的人口估计数”的所有列的最大值和最小值，然后减去这两个值。我希望该函数返回一个带有索引和值的 Pandas 系列。

这是我当前的代码:

columns_to_keep=[
    'STNAME',
    'CTYNAME',
    'POPESTIMATE2010',
    'POPESTIMATE2011',
    'POPESTIMATE2012',
    'POPESTIMATE2013',
    'POPESTIMATE2014',
    'POPESTIMATE2015' 
]
df=census_df[columns_to_keep]

def answer_seven(lst):
    lst=[df['POPESTIMATE2010'],df['POPESTIMATE2011'],df['POPESTIMATE2012'],
             df['POPESTIMATE2013'],df['POPESTIMATE2014'],df['POPESTIMATE2015']]

    return max(lst)-min(lst)

answer_seven(lst)

错误信息:

ValueError                                Traceback (most recent call last)
<ipython-input-110-845350b0b5f7> in <module>()
     18     return max(lst)-min(lst)
     19 
---> 20 answer_seven(lst)
     21 

<ipython-input-110-845350b0b5f7> in answer_seven(lst)
     16              df['POPESTIMATE2013'],df['POPESTIMATE2014'],df['POPESTIMATE2015']]
     17 
---> 18     return max(lst)-min(lst)
     19 
     20 answer_seven(lst)

/opt/conda/lib/python3.5/site-packages/pandas/core/generic.py in __nonzero__(self)
    890         raise ValueError("The truth value of a {0} is ambiguous. "
    891                          "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
--> 892                          .format(self.__class__.__name__))
    893 
    894     __bool__ = __nonzero__

ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

Answer 1

Pandas 可以直接这样做:

cols_of_interest = ['POPESTIMATE2010', 'POPESTIMATE2011', 'POPESTIMATE2012', 'POPESTIMATE2013', 'POPESTIMATE2014' , 'POPESTIMATE2015']
df[cols_of_interest].max(axis=1) - df[cols_of_interest].min(axis=1)

这将返回一个由数据框的原始索引和每行的最大值减去最小值索引的系列