ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.
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 pddata = {'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)
dfdf_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) <ipython-input-11-1f338a747fac> in <module> ----> 1 df_filtered = df[(df['Shares']>=100) and (df['Shares']<=150)]2 df_filtered3 # 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().
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