python实现模糊逻辑_python动态模糊逻辑连接

科技前沿 • 2025-01-28 23:25 • 阅读 46

大家好，我是讯享网，很高兴认识大家。

我试图为两个表建立一个动态模糊逻辑连接。我所说的动态是允许参数指定允许两个表联接的变量。

以下代码是以下链接下静态代码的修改版本：

Python Pandas fuzzy merge/match with duplicates

我编译了以下动态代码：import pandas as pd

import datetime

from fuzzywuzzy import fuzz

import difflib

donors = pd.DataFrame({"name": pd.Series(["John Doe","John Doe","Tom Smith","Jane Doe","Jane Doe","Kat test"]), "Email": pd.Series(['','','','','','']),"Date": (["27/03/2013 10:00:00 AM","1/03/2013 10:39:00 AM","2/03/2013 10:39:00 AM","3/03/2013 10:39:00 AM","4/03/2013 10:39:00 AM","27/03/2013 10:39:00 AM"])})

fundraisers = pd.DataFrame({"name": pd.Series(["John Doe","John Doe","Kathy test","Tes Ester", "Jane Doe"]),"Email": pd.Series(['','','','','']),"Date": pd.Series(["2/03/2013 10:39:00 AM","27/03/2013 11:39:00 AM","3/03/2013 10:39:00 AM","4/03/2013 10:40:00 AM","27/03/2013 10:39:00 AM"])})

donors["Date"] = pd.to_datetime(donors["Date"], dayfirst=True)

fundraisers["Date"] = pd.to_datetime(donors["Date"], dayfirst=True)

donors["code"] = donors.apply(lambda row: str(row['name'])+' '+str(row['Email']), axis=1)

idx = donors.groupby('code')["Date"].transform(min) == donors['Date']

donors = donors[idx].reset_index().drop('index',1)

def get_donors_v1(fund_var,don_var, don_tab,row=None):

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d = don_tab.apply(lambda x: fuzz.ratio(x["%s" % don_var], 'row["%s" %fund_var]') * 2, axis=1)

d = d[d >= 75]

if len(d) == 0:

v = ['']*3

else:

v = don_tab.ix[d.idxmax(), ["%s"% don_var ,'Email','Date']].values

return pd.Series(v, index=['donor name', 'donor email', 'donor date'])

trial=pd.concat((fundraisers, fundraisers.apply(get_donors_v1(fund_var="name",don_var="name",don_tab=donors), axis=1)), axis=1)

我得到以下错误：TypeError: get_donors_v1() takes exactly 4 arguments (3 given)

是否应将函数替换为：

^{pr2}$

然后我得到以下错误：TypeError: ("'NoneType' object has no attribute 'getitem'",

u'occurred at index 0')

请帮忙。在

python实现模糊逻辑_python动态模糊逻辑连接

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