python - 在条件语句后设置数据框

Question

我有一个 pandas 数据框

矩阵["dist"]

       1       2
1     2.92    70.75
2     71.34   5.23

我尝试使用apply替换值

matrices["dist"].apply(lambda x: 1 if x >= 50 else 0)

但我收到错误

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-272-bb796b629822> in <module>()
----> 1 matrices["dist"].apply(lambda x: 1 if x >= 1 else 0)

C:\Anaconda\lib\site-packages\pandas\core\frame.pyc in apply(self, func, axis, broadcast, raw, reduce, args, **kwds)
   4150                     if reduce is None:
   4151                         reduce = True
-> 4152                     return self._apply_standard(f, axis, reduce=reduce)
   4153             else:
   4154                 return self._apply_broadcast(f, axis)

C:\Anaconda\lib\site-packages\pandas\core\frame.pyc in _apply_standard(self, func, axis, ignore_failures, reduce)
   4246             try:
   4247                 for i, v in enumerate(series_gen):
-> 4248                     results[i] = func(v)
   4249                     keys.append(v.name)
   4250             except Exception as e:

<ipython-input-272-bb796b629822> in <lambda>(x)
----> 1 matrices["dist"].apply(lambda x: 1 if x >= 1 else 0)

C:\Anaconda\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 1')

根据条件替换值的最佳方法是什么？

Answer 1

更新:

In [121]: ((df >= 50) & (df <= 71))  * 1
Out[121]:
   1  2
1  0  1
2  0  0

试试这个:

In [106]: (df>=50).astype(int)
Out[106]:
   1  2
1  0  1
2  1  0

或

In [107]: (df>=50) * 1
Out[107]:
   1  2
1  0  1
2  1  0