Generating numbers in front of duplicate values

Question

Scenario: I am getting the data of companies name, address, city and contact from a flat file imported into SQL Server.

I am trying to import this data into a platform that only accepts unique company names. Let's look at an example of the flat data:

CompanyName  City          Address                           Contact
------------------------------------------------------------------------
Starbucks    Seattle       Null                              Pedram
Starbucks    Seattle       44 East Ave                       Daniel
Starbucks    Seattle       2701 Freedom way                  April
Starbucks    Seattle       3500 E Destination Drive          Steve
Starbucks    Luxembourg    N2915 Countrt Road AB             Hans
Starbucks    Orleans       2800 Rice St.                     Emily
Starbucks    St. Paul      6500 Henri-Bourassa BE            Casey
Starbucks    St. Paul      6500 Henri-Bourassa BE            Kathy

With a data set like this, I am trying to get a result as shown below:

 CompanyName                 City               Address                            
 -------------------------------------------------------------------------
 Starbucks (Seattle)         Seattle            Null                    
 Starbucks (Seattle-1)       Seattle            44 East Ave                       
 Starbucks (Seattle-2)       Seattle            2701 Freedom way                  
 Starbucks (Seattle-3)       Seattle            3500 E Destination Drive          
 Starbucks (Luxembourg)      Luxembourg         N2915 Countrt Road AB             
 Starbucks (Orleans)         Orleans            2800 Rice St.                     
 Starbucks (St. Paul)        St. Paul           6500 Henri-Bourassa BE 

I have tried using Row_number and Partition By but the issue that I have is: how do I generate that number in front?

Below is the code for data Set and what I have tried:

Create table #Company 
(
     companyname nvarchar(255),
     City nvarchar(100),
     [Address] nvarchar(255),
     Contact nvarchar(255)
)

insert into  #Company (companyname, City, Contact) 
values ('Starbucks', 'Seattle', 'Pedram');

insert into  #Company (companyname, City, [Address], Contact) 
values ('Starbucks', 'Seattle', '44 East Ave', 'Daniel'),  
       ('Starbucks', 'Seattle', '2701 Freedom way', 'April'),
       ('Starbucks', 'Seattle','3500 E Destination Drive', 'Steve'),
       ('Starbucks', 'Luxembourg', 'N2915 Countrt Road AB', 'Hans'),
       ('Starbucks', 'Orleans', '2800 Rice St.', 'Emily'),
       ('Starbucks', 'St. Paul', '6500 Henri-Bourassa BE', 'Casey'),
       ('Starbucks', 'St. Paul', '6500 Henri-Bourassa BE', 'Kathy');

SELECT * FROM #Company

SELECT 
    ROW_NUMBER() OVER (PARTITINO BY companyname, city, [address] ORDER BY  companyname), 
    CASE 
       WHEN ROW_NUMBER() OVER (PARTITION BY companyname, city, [address] ORDER BY companyname, city, [address]) = 1 
          THEN companyname + ' ' + '(' + ISNULL(city,'')+ ')'
          ELSE companyname END,   --+ CAST(ROW_NUMBER() OVER (PARTITION BY T1.COMPANY, T1.CITY ORDER BY T1.[Address 1]) AS VARCHAR(3))
    *
FROM 
    #Company

Answer 1

Query

SELECT 
        companyname 
       + ' (' + City 
       + REPLACE( ' - ' 
       + CAST( 
        ROW_NUMBER() OVER (PARTITION BY companyname , City 
                            ORDER BY CASE WHEN [Address] IS NULL 
                                            THEN '0' ELSE [Address] END
                            ) - 1 AS VARCHAR(10))
        + ')' , ' - 0', '') AS CompanyNameNew
        , City
        , [Address]

FROM #Company
ORDER BY CompanyName , [Address]

Result Set

╔══════════════════════════╦════════════╦══════════════════════════╗
║      CompanyNameNew      ║    City    ║         Address          ║
╠══════════════════════════╬════════════╬══════════════════════════╣
║ Starbucks (Seattle)      ║ Seattle    ║ NULL                     ║
║ Starbucks (Seattle - 1)  ║ Seattle    ║ 2701 Freedom way         ║
║ Starbucks (Seattle - 2)  ║ Seattle    ║ 3500 E Destination Drive ║
║ Starbucks (Seattle - 3)  ║ Seattle    ║ 44 East Ave              ║
║ Starbucks (Orleans)      ║ Orleans    ║ 2800 Rice St.            ║
║ Starbucks (St. Paul)     ║ St. Paul   ║ 6500 Henri-Bourassa BE   ║
║ Starbucks (St. Paul - 1) ║ St. Paul   ║ 6500 Henri-Bourassa BE   ║
║ Starbucks (Luxembourg)   ║ Luxembourg ║ N2915 Countrt Road AB    ║
╚══════════════════════════╩════════════╩══════════════════════════╝