Get Ids With Similar Address In A New Column

I have a dataframe from which i process some columns to get the matching percentage of address of each customer id with address of every other customer id. If some addresses match

Solution 1:

As per your problem, this solution will work, Code is self-explanatory :)

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

    # Getting the column values of id and address in seprate listid = 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 onefor 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)   

main function :

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