熊猫：比较来自不同大小的两个不同数据帧的字符串列

如何解决熊猫：比较来自不同大小的两个不同数据帧的字符串列

我有两个不同大小的数据框，每个都有一列句子，如下：

import pandas as pd

data1 = {'text':  ['the old man is here','the young girl is there','the old woman is here','the young boy is there','the young girl is here','the old girl is here']}

df1 = pd.DataFrame (data,columns = ['text'])

和第二个数据框：

data2 = {'text':  ['the old man is here','the old girl is there','the young woman is here','the young boy is there']}

df2 = pd.DataFrame (data,columns = ['text'])

如您所见，两个数据框中都有一些相似的句子。我想要的输出是 df1 中的一列，如果两个字符串相似则表示为真，否则为假：

desired output:
text                        result
'the old man is here'       True
'the young girl is there'   False
'the old woman is here'     False
'the young boy is there'    True
'the young girl is here'    False
'the old girl is here'      False

我试过了：

df1['result'] = np.where(df1['text'].str == df2['text'].str,'True','False')

但是当我检查时，它只返回 false 而没有 'true'

解决方法

如果需要布尔值 True/False，请使用 Series.isin：

df1['result'] = df1['text'].isin(df2['text'])
print (df1)
                      text  result
0      the old man is here    True
1  the young girl is there   False
2    the old woman is here   False
3   the young boy is there    True
4   the young girl is here   False
5     the old girl is here   False

工作方式：

#removed '' from 'True','False' for boolean
df1['result'] = np.where(df1['text'].isin(df2['text']),True,False)

您的解决方案创建字符串，因此如果需要用于过滤它会失败：

df1['result'] = np.where(df1['text'].isin(df2['text']),'True','False')