Question

我有一个数据帧，我从中处理一些列以获取每个客户ID的地址与其他客户ID的地址的匹配百分比。如果某些地址与其他地址的百分比大于80的其他地址匹配，那么我想在新列中收集相应的客户ID

我编写了代码，其中得到了具有地址的元组列表以及每个元组中的相应分数。

import pandas as pd
from fuzzywuzzy import process


def pat_match(id,address):

    length01=len(id)    # normal integer sequence 1 to 10


    for y in range(0,length01):
        score=process.extractBests(address[y],address,score_cutoff=80)
        print(score)                    # actual results(list of tuples)
        d2=[sc[1] for sc in score]
        #print(d2)                       # variable having list of scores per address tuple



if __name__ == '__main__':
    data = pd.read_csv(r"address_details.csv", skiprows=0)
    id = data['COD_CUST_ID'].values.tolist()
    address = data['ADDRESS'].values.tolist()
    pat_match(id,address)

假设我输入的数据为

Customer_ID Address
21213944    VPO. SAHWA   CHURU RAJASTHAN 331302
21991538    WARD NO.-3 NATT ROAD TALWANDI SABO BATHINDA  BATHINDA PUNJAB 151302
21991539    H.NO.-137 RAMA ROAD TALWANDI SABO BATHINDA  BATHINDA PUNJAB 151302
21603327    VAGPUR KARCHCHA KALAN   UDAIPUR RAJASTHAN 313803
21215934    VILLAGE GORIYAN TEHSIL UDAIPURWATI DIST JHUNJHUNU  JHUJHUNU RAJASTHAN 333307

变量SCORE的中间输出是

[('WARD NO 25 GHADSISAR ROAD BASANT KUNJ KE SAMNE HANUMAN MANDIR KE PASS CHOUDHARY COLONY GANGASHAR BIKANER RAJASTHAN 334001', 100), ('VPO. SAHWA   CHURU RAJASTHAN 331302', 86), ('WARD NO.-3 NATT ROAD TALWANDI SABO BATHINDA  BATHINDA PUNJAB 151302', 86), ('H.NO.-137 RAMA ROAD TALWANDI SABO BATHINDA  BATHINDA PUNJAB 151302', 86), ('Karchha Kalan   UDAIPUR RAJASTHAN 313803', 86)]
[('Karchha Kalan   UDAIPUR RAJASTHAN 313803', 100), ('VAGPUR KARCHCHA KALAN   UDAIPUR RAJASTHAN 313803', 91), ('WARD NO 25 GHADSISAR ROAD BASANT KUNJ KE SAMNE HANUMAN MANDIR KE PASS CHOUDHARY COLONY GANGASHAR BIKANER RAJASTHAN 334001', 86), ('VILLAGE GORIYAN TEHSIL UDAIPURWATI DIST JHUNJHUNU  JHUJHUNU RAJASTHAN 333307', 86)]
[('VAGPUR KARCHCHA KALAN   UDAIPUR RAJASTHAN 313803', 100), ('Karchha Kalan   UDAIPUR RAJASTHAN 313803', 91), ('WARD NO 25 GHADSISAR ROAD BASANT KUNJ KE SAMNE HANUMAN MANDIR KE PASS CHOUDHARY COLONY GANGASHAR BIKANER RAJASTHAN 334001', 86), ('VILLAGE GORIYAN TEHSIL UDAIPURWATI DIST JHUNJHUNU  JHUJHUNU RAJASTHAN 333307', 86)]
[('VILLAGE GORIYAN TEHSIL UDAIPURWATI DIST JHUNJHUNU  JHUJHUNU RAJASTHAN 333307', 100), ('VPO. SAHWA   CHURU RAJASTHAN 331302', 86), ('WARD NO 25 GHADSISAR ROAD BASANT KUNJ KE SAMNE HANUMAN MANDIR KE PASS CHOUDHARY COLONY GANGASHAR BIKANER RAJASTHAN 334001', 86), ('Karchha Kalan   UDAIPUR RAJASTHAN 313803', 86), ('VAGPUR KARCHCHA KALAN   UDAIPUR RAJASTHAN 313803', 86)]

我想要成为的最终输出是

Search String   Match Customer Ids
WARD NO.-3 NATT ROAD TALWANDI SABO BATHINDA  BATHINDA PUNJAB 151302 21991538,21991539
VAGPUR KARCHCHA KALAN   UDAIPUR RAJASTHAN 313803    21603327,21215934

Answer 1

根据您的问题，此解决方案将起作用，代码不言自明:)

# Getting the DataFrame as the parameter
def pat_match(df):

    # Getting the column values of id and address in seprate list
    id = df['COD_CUST_ID'].values.tolist()
    address = df['ADDRESS'].values.tolist()

    # Creating a new column with name 'Ids'
    df['Ids'] = ""
    length01=len(id)   

    for y in range(0,length01):

        # The mathched address Id will will be appended in a list for every address
        matched_ids = []

        # Calculating list of address with match percentage more than 80%
        score=process.extractBests(address[y],address,score_cutoff=80)

        # Iterating over every address returned by score one by one
        for matched_address in score:

            # Getting Customer_ID of every Address
            get = df['Customer_ID'][df['Address']==matched_address].tolist()[0]

            # Appending the Id into a list
            matched_ids.append(get)

        # Finally Appending the list of matched ID to the column 
        df['Ids'][df['Customer_ID']==id[y]] = str(matched_ids)

主要功能：

  if __name__ == '__main__':
    data = pd.read_csv(r"address_details.csv", skiprows=0)
    pat_match(data)

在新列中获取具有类似地址的ID

1 个答案: