尝试用PythonPy相似性或DamerauLevenshtein检查2列的字符串相似性

Question

我试着用总结器来总结文本！问题是，我想看看这些文本是否太相似，要做到这一点，我可以在谷歌上看到，我可以使用软件包，如problem或fastDamerauLevenstein.问题和他们似乎只工作一个文本，只有.您知道如何做吗，例如4文本或更多？

from summarizers import Summarizers 
summ = Summarizers() 
data = ["The NN-CS89L offers next-level cooking convenience. Its four distinct cooking methods - steaming, baking, grilling and microwaving ensure your meals are cooked or reheated to perfection. Its multi-function capabilities can be combined to save time without compromising taste, texture or nutritional value. It’s the all-in-one kitchen companion designed for people with a busy lifestyle.", "These slim and stylish bodies are packed with high performance. The attractive compact designs and energy-saving functions help Panasonic Blu-ray products consume as little power as possible. You can experience great movie quality with this ultra-fast booting DMP-BD89 Full HD Blu-ray disc player. After starting the player, the time it takes from launching the menu to playing a disc is much shorter than in conventional models. The BD89 also allows for smart home networking (DLNA) and provides access to video on demand, so that home entertainment is more intuitive, more comfortable, and lots more fun."] 

df = pd.DataFrame(data, columns=['summaries'])
df['abstracts'] = df['summaries'].apply(summ)


compare(df.summaries, df.abstracts) ``` 




I have this : 
TypeError                                 Traceback (most recent call last)
<ipython-input-14-d1d78dc1f358> in <module>
----> 1 compare(df.summaries, df.abstracts)

~\Anaconda3\lib\site-packages\pysimilar\__init__.py in compare(self, string_i, string_j, isfile)
     89 
     90         if not isinstance(string_i, (str, Path)) or not isinstance(string_j, (str, Path)):
---> 91             raise TypeError(
     92                 'Both string i and string j must be of type either string or Path')
     93 

TypeError: Both string i and string j must be of type either string or Path

Thanks in advance !

Answer 1

您需要创建一个包含两列值的行的函数，并对这两个列调用compare，然后将其应用于dataframe。

def compare_row_wise(row):
    return compare(row['summaries'], row['abstracts'])

df.apply(compare_row_wise, axis=1)