SF_AC_Name.py

# -*- coding: utf-8 -*-
import pandas as pd
import numpy as np
from fuzzywuzzy import process

infileName = 'SF Account Names.csv'

sfData = pd.read_csv(infileName, header=0)
# print (sfData.keys())
# print(sfData.head())
Name = sfData["Account Name"]


def find_app_name(name):
    #### set score_cutoff =88 for Magnus ###
    try:
        app_name = process.extract(name["Account Name"], choices=Name)

        result = [name[0] for name in app_name if 88 <= name[1] <100 ]
        return "".join(str(item) for item  in result)
        # return result
    except:
        pass
    return np.nan


# def find_app_name_score(name):
#     try:
#         app_name = process.extractOne(name["Account Name"], choices=Approved_supplier_name, score_cutoff=88)
#         if app_name:
#             return app_name[1]
#     except:
#         pass
#     return np.nan
#
#
# def find_app_name_position(name):
#     try:
#         app_name = process.extractOne(name["Account Name"], choices=Approved_supplier_name, score_cutoff=88)
#         if app_name:
#             return app_name[2]
#     except:
#         pass
#     return np.nan

sfData["Suggested Name"] =np.nan
sfData["Suggested Name"] = sfData.apply(find_app_name, axis=1)
# Name["Match Score"] = Name.apply(find_app_name_score, axis=1)
# Name["Match Position"] = Name.apply(find_app_name_position, axis=1)

# print (Name["Suggested name"].head())
writer = pd.ExcelWriter("SF Account Names Output.xlsx")

#sfData.to_excel(writer, 'SF Account Name')
# sfData[sfData["Suggested name"].notnull()].to_excel(writer, 'SF Account Name')
#sfData[pd.notnull(sfData["Suggested name"])].to_excel(writer,'SF Account Name')
sf_output = sfData[sfData['Suggested Name'].str.len() > 1]

sf_output.to_excel(writer,'SF Account Name')
writer.save()