错误:系列的真实值不明确-Python pandas [英] Error: The truth value of a Series is ambiguous - Python pandas

问题描述

我知道之前曾有人问过这个问题，但是当我尝试执行if语句时却遇到错误.我看着这个

I know this question has been asked before, however, when I am trying to do an if statement and I am getting an error. I looked at this link , but did not help much in my case. My dfs is a list of DataFrames.

我正在尝试以下方法，

for i in dfs:
    if (i['var1'] < 3.000):
       print(i)

给出以下错误:

ValueError:系列的真值不明确.使用a.empty，a.bool()，a.item()，a.any()或a.all().

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

AND 我尝试了以下操作，并得到了相同的错误.

AND I tried the following and getting the same error.

for i,j in enumerate(dfs):
    if (j['var1'] < 3.000):
       print(i)

我的var1数据类型是float32.我没有使用任何其他logical运算符和&或|.在上面的链接中，这似乎是因为使用了逻辑运算符.为什么我会得到ValueError?

My var1 data type is float32. I am not using any other logical operators and & or |. In the above link it seemed to be because of using logical operators. Why do I get ValueError?

推荐答案

下面是一个小演示，它说明了为什么发生这种情况:

Here is a small demo, which shows why this is happenning:

In [131]: df = pd.DataFrame(np.random.randint(0,20,(5,2)), columns=list('AB'))

In [132]: df
Out[132]:
    A   B
0   3  11
1   0  16
2  16   1
3   2  11
4  18  15

In [133]: res = df['A'] > 10

In [134]: res
Out[134]:
0    False
1    False
2     True
3    False
4     True
Name: A, dtype: bool

当我们尝试检查此类系列是否为True时-熊猫不知道该怎么做:

when we try to check whether such Series is True - Pandas doesn't know what to do:

In [135]: if res:
     ...:     print(df)
     ...:
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
...
skipped
...
ValueError: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

解决方法:

我们可以决定如何处理一系列布尔值-例如，如果所有值为True，则if应该返回True:

we can decide how to treat Series of boolean values - for example if should return True if all values are True:

In [136]: res.all()
Out[136]: False

或至少一个值为True时:

In [137]: res.any()
Out[137]: True

In [138]: if res.any():
     ...:     print(df)
     ...:
    A   B
0   3  11
1   0  16
2  16   1
3   2  11
4  18  15

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