使用if else语句的输出创建新列会导致错误 [英] Creating new column using output of if else statement causes error

问题描述

我正在使用以下代码，

if(df.month == 3 or df.month == 4 or df.month == 5):
    df.test = 'A'
elif(df.month == 6 or df.month == 7 or df.month == 8):
    df.test = 'B'
else:
    df.test = 'C'

但是使用此方法时，出现以下错误，

But while using this, I am getting the following error,

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

更新：

print df.columns

Unnamed: 0      int64
year            int64
month           int64
day             int64
dep_time      float64
dep_delay     float64
arr_time      float64
arr_delay     float64
carrier        object
tailnum        object
flight          int64
origin         object
dest           object
air_time      float64
distance        int64
hour          float64
minute        float64


print df.dtypes

dtype: object

有人可以帮助我在这里找到错误吗？

Can anybody help me in finding the error here?

推荐答案

我认为最好是使用 loc 和 isin ，因为您无法使用 if 将标量与类似数组的标量进行比较或 elif 变得模棱两可：

I think the best is use loc and isin, because you can't compare a scalar with an array like that using if or elif it becomes ambiguous:

print df

   year  month  day
0  2005      3   20
1  2005      4   20
2  2005      5   20
3  2005      6   20
4  2005      7   20
5  2005      8   20
6  2005      9   20

df['test'] = 'C'
df.loc[df['month'].isin([3,4,5]) , 'test'] = 'A'
df.loc[df['month'].isin([6,7,8]) , 'test'] = 'B'

print df  

   year  month  day test
0  2005      3   20    A
1  2005      4   20    A
2  2005      5   20    A
3  2005      6   20    B
4  2005      7   20    B
5  2005      8   20    B
6  2005      9   20    C

或者您可以通过以下方式用值 C 填充列 test ：

Or you can fill column test by value C this way:

df.loc[df['month'].isin([3,4,5]) , 'test'] = 'A'
df.loc[df['month'].isin([6,7,8]) , 'test'] = 'B'
df.loc[df['month'].isin([1,2,9,10,11,12]) , 'test'] = 'C'

print df    

   year  month  day test
0  2005      3   20    A
1  2005      4   20    A
2  2005      5   20    A
3  2005      6   20    B
4  2005      7   20    B
5  2005      8   20    B
6  2005      9   20    C

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