列包含第2列 [英] Column contains column 2

问题描述

我有一个数据框.我想测试(C)在每一行中(B)列中的数字是否在字符串(A)列中.

I have a dataframe. I would like to test whether, (C), on each row, the number in column (B) is in the string, column (A).

df = pd.DataFrame({'A': ["me 123", "me-123", "1234", "me 12", "123 and"],
                   'B': [123,       123,      123,    123,     6]})

我想得到:

         A    B  C
0   me 123  123  1
1   me-123  123  1
2     1234  123  0
3    me 12  123  0
4  123 and    6  0

各种方法几乎可以解决这个问题(1):

Various approaches nearly manage this (1):

df['C'] = [str(y) in x for x , y in zip(df.A.str.split(' '),df.B)]

         A    B      C
0   me 123  123   True
1   me-123  123  False
2     1234  123  False
3    me 12  123  False
4  123 and    6  False

或(2):

df['C'] = [str(y) in x for x , y in zip(df.A,df.B)]

         A    B      C
0   me 123  123   True
1   me-123  123   True
2     1234  123   True
3    me 12  123  False
4  123 and    6  False

或(3):

df['C']=df.A.str.contains(r'\b(?:{})\b'.format('|'.join(df.B.astype(str)))).astype(int)

         A    B  C
0   me 123  123  1
1   me-123  123  1
2     1234  123  0
3    me 12  123  0
4  123 and    6  1

或(4):

def fun (A,B):
    return str(B) in str(A)
f = np.vectorize(fun, otypes=[int])
df["C"] = f(df['A'], df['B'])

         A    B  C
0   me 123  123  1
1   me-123  123  1
2     1234  123  1
3    me 12  123  0
4  123 and    6  0

或(5):

df['A1'] = df['A'] .apply(word_tokenize)

无法识别-是空格.请问如何获得顶部的结果?

Doesn't recognise - as a space. How can I get the result at the top please?

推荐答案

从extract

df.A.str.extract('(\d+)', expand=False).astype(int).eq(df.B,0).astype(int)
Out[347]: 
   0
0  1
1  1
2  0
3  0
4  0

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