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I am working on a GUI that edits and compares CSV files for my monthly user uploads in my wellness data job. I have already built out this operation for one of our client businesses, but now I am trying to reconfigure it to work for our other client business. It currently works without errors, but for some reason my new_users dataframe prints as blank after merging it. For my other package that I built, this exact code works correctly. My first thought was perhaps it is because UniqueIDs need to be 10 characters, but even after putting in the character requirements I am still getting an empty dataframe for new_users. This has me stumped.

def client_merge(ef_in, ul_in):
    pd.set_option('mode.chained_assignment', None)

    ef_in['UniqueID'] = ef_in['UniqueID'].astype(object)
    ef_in['HireDate'] = ef_in['HireDate'].astype(object)
    ef_in['DateOfBirth'] = ef_in['DateOfBirth'].astype(object)
    ul_in['UniqueID'] = ul_in['UniqueID'].astype(object)
    ul_in['Action'] = ul_in['Action'].astype(object)
    ul_in['ZipCode'] = ul_in['ZipCode'].astype(object)

    df = pd.concat(([ef_in, ul_in]), axis=0, ignore_index=True, sort=False)
    df.drop_duplicates(subset=["UniqueID"], keep=False, inplace=True)

    df['UniqueID'] = df['UniqueID'].str.rjust(10, "0")
    ef_in['UniqueID'] = ef_in['UniqueID'].str.rjust(10, "0")
    ul_in['UniqueID'] = ul_in['UniqueID'].str.rjust(10, "0")

    print(ef_in)
    new_users = df.merge(ef_in)
    #print(new_users)
    disable_users = df.merge(ul_in)
    #print(ul_in)

    disable_users['Action'].fillna('Disable', inplace=True)
    ready_to_print_file = pd.concat([new_users, disable_users], ignore_index=False)

    rtpf1 = ready_to_print_file[ready_to_print_file["FirstName"].str.contains("companytest") == False]
    rtpf2 = rtpf1[rtpf1["FirstName"].str.contains("Clarks", "test") == False]

    rtpf2.to_csv(path, header=True, index=False)

I have been playing with it for two hours cross-referencing hand-done comparison in Excel, and my file, and it should definitely not be coming back blank. I have attached the working code for my other client below:

def client_merge(ef_in, ul_in):
    pd.set_option('mode.chained_assignment', None)

    ef_in['EmployeeId'] = ef_in['EmployeeId'].astype(object)
    ul_in['EmployeeId'] = ul_in['EmployeeId'].astype(object)
    ul_in['Action'] = ul_in['Action'].astype(object)
    ul_in['PrimaryMemberEmployeeId'] = ul_in['PrimaryMemberEmployeeId'].astype(object)
    ul_in['ZipCode'] = ul_in['ZipCode'].astype(object)

    df = pd.concat(([ef_in, ul_in]), axis=0, ignore_index=True, sort=False)
    df.drop_duplicates(subset=["EmployeeId"], keep=False, inplace=True)

    new_users = df.merge(ef_in)
    disable_users = df.merge(ul_in)

    disable_users['Action'].fillna('Disable', inplace=True)
    ready_to_print_file = pd.concat([new_users, disable_users], ignore_index=False)

    rtpf1 = ready_to_print_file[ready_to_print_file["FirstName"].str.contains("admin") == False]
    rtpf2 = rtpf1[rtpf1["FirstName"].str.contains("client") == False]

    rtpf2.to_csv(path, header=True, index=False)
Pongotan
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  • 4

1 Answers1

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df1.merge(ef_in, how='left', on='a')

Refer to the link for more information:

Reference for pandas dataframe merging

Sagar S
  • 1
  • What should i be replacing 'a' with? – Pongotan Dec 27 '22 at 17:43
  • I am unsure of this answer, my man. I will continue to search for solutions, I may actually already have it working, and my input files may be off because on a manual test it’s some pretty slim margins – Pongotan Dec 27 '22 at 19:14
  • As it’s currently written, your answer is unclear. Please [edit] to add additional details that will help others understand how this addresses the question asked. You can find more information on how to write good answers [in the help center](/help/how-to-answer). – Community Dec 27 '22 at 19:47