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

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

 

目录

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

问题：

解决：

完整错误：

---

问题：

出现此错误是因为Python的逻辑运算符(and、or、not)是用来与布尔值（boolean）一起使用的，所以当试图将它们与序列或数组一起使用时，系统程序不清楚如何确定它是真的还是假的，因此会导致ValueError。

import pandas as pd

data = {
    'Name': ['Microsoft Corporation', 'Google, LLC', 'Tesla, Inc.',\
             'Apple Inc.', 'Netflix, Inc.'],
    'Symbol': ['MSFT', 'GOOG', 'TSLA', 'AAPL', 'NFLX'],
    'Industry': ['Tech', 'Tech', 'Automotive', 'Tech', 'Entertainment'],
    'Shares': [100, 50, 150, 200, 80]
}

df = pd.DataFrame(data)
# print(df)
df


df_filtered = df[(df['Shares']>=100) and (df['Shares']<=150)]
df_filtered
# print(df_filtered)

解决：

将and改为&

df_filtered = df[(df['Shares']>=100) & (df['Shares']<=150)]
df_filtered
# print(df_filtered)

 

完整错误：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
 in 
----> 1 df_filtered = df[(df['Shares']>=100) and (df['Shares']<=150)]
      2 df_filtered
      3 # print(df_filtered)

D:\anaconda\lib\site-packages\pandas\core\generic.py in __nonzero__(self)
   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().

参考：pandas

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