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

绝地灬酷狼 2023-09-28 21:31 13阅读 0赞

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

例：

data = {
        'Name': ['Microsoft', 'Google', 'huawei','Apple', 'Andriod'],'Shares': [63, 50, 71, 62, 65]}
    data

我们的数据展示如下：

{
        'Name': ['Microsoft', 'Google', 'huawei', 'Apple', 'Andriod'],
     'Shares': [63, 50, 71, 62, 65]}

我最开始的目的是要找到`'Shares'`的取值范围在【60，75】之间的数据：

df = pd.DataFrame(data)
    df[df['Shares']>60 & df['Shares']<75]

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

我们看一下完整的错误说明：

---------------------------------------------------------------------------
    ValueError                                Traceback (most recent call last)
    Input In [34], in <cell line: 1>()
    ----> 1 df[df['Shares']>60 & df['Shares']<75]
    
    File F:\anaconda\envs\sklearn-env\lib\site-packages\pandas\core\generic.py:1442, in NDFrame.__nonzero__(self)
       1440 @final
       1441 def __nonzero__(self):
    -> 1442     raise ValueError(
       1443         f"The truth value of a {
          type(self).__name__} is ambiguous. "
       1444         "Use a.empty, a.bool(), a.item(), a.any() or a.all()."
       1445     )
    
    ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

### 问题思考 ###

如果不使用圆括号（）对条件进行分组，Python将根据运算符优先级计算表达式，这可能会给出运算符&和~的意外结果。

`df[df['Shares']>60 & df['Shares']<75]`可能会理解成`df['Shares']>（60 & df['Shares']）<75`

### 问题解决 ###

为条件关系添加括号即可！

df[(df['Shares']>60) & (df['Shares']<75)]

![5296eeeb360f483bb1b26470e25e37d7.png][]

[5296eeeb360f483bb1b26470e25e37d7.png]: https://img-blog.csdnimg.cn/5296eeeb360f483bb1b26470e25e37d7.png

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

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