问题描述
我是编程新手.我有一个 Pandas 数据框，其中存在两个字符串列.
I am new to programming.I have a pandas data frame in which two string columns are present.
数据框如下:
Col-1 Col-2
Update have a account
Account account summary
AccountDTH Cancel
Balance Balance Summary
Credit Card Update credit card
这里我需要检查 Col-2 元素与 Col-1 的每个元素的相似性.这意味着我必须将 have a account 与 Col-1 的所有元素进行比较.然后找到前3个相似的.假设相似度分数为:Account(85),AccountDTH(80),Balance(60),Update(45),Credit Card(35).
Here i need to check the similarity of Col-2 elements with each element of Col-1.It Means i have to compare have a account with all the elements of Col-1.Then find the top 3 similar one. Suppose the similarity scores are :Account(85),AccountDTH(80),Balance(60),Update(45),Credit Card(35).
预期输出为:
Col-2 Output
have a account Account(85),AccountDTH(80),Balance(60)
推荐答案
您可以使用 Python 库，例如 在这里，fuzzywuzzy 支持这种类型的任务:
You can use a Python library like fuzzywuzzy here, which has support for this type of task:
from fuzzywuzzy import process
df.assign(Output=[process.extract(i, df['Col-1'], limit=3) for i in df['Col-2']])
使用process 方法，我们可以得到字符串的相似度分数，然后选择前 3 个，如果 3 个存在:
Using the process method, we can get string similary scores, and then pick the top 3, if 3 exist:
以上代码的输出:
Col-1 Col-2 Output
0 Update have a account [(Account, 90, 1), (AccountDTH, 64, 2), (Update, 40, 0)]
1 Account account summary [(Account, 90, 1), (AccountDTH, 63, 2), (Credit Card, 38, 4)]
2 AccountDTH Cancel [(Balance, 62, 3), (Credit Card, 43, 4), (Update, 33, 0)]
3 Balance Balance Summary [(Balance, 90, 3), (Credit Card, 38, 4), (Update, 30, 0)]
4 Credit Card Update credit card [(Update, 90, 0), (Credit Card, 90, 4), (AccountDTH, 27, 2)]
为了加快比较速度(它本身使用 Python 的序列匹配器)，我建议安装 python-Levenshtein
To speed this comparison up (natively it uses Python's sequence matcher), I would recommend installing python-Levenshtein
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