Have data appear in first row only in one column of dataframe

I have a column of ticker symbols and from that column I made a comma delimited string of symbols that was placed in a new column called v1 in the same dataframe, DF. I also took the comma delimited string to a new dataframe, DF1. In both cases, I only wanted the string to appear in column 1, not in every column. Is there any way in either dataframe, to have the comma delimited string of symbols only appear in the first row and not repeat in all the rows? If possible could someone explain how. Thanks

Delimited Comma String Code

v1 = df['Ticker'].tolist()
        v1 = ",".join(map(str,v1))
        df['v1'] = v1
        df1 = df[['v1']]
        print(df)
        print (df1)

Current DF Output

 No. Ticker  ... AH Change                                                 v1
    0    1   AAPL  ...         -  AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...
    1    2   MSFT  ...         -  AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...
    2    3   TSLA  ...         -  AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...
    3    4     FB  ...         -  AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...

Current DF1 Output

    0   AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...
    1   AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...
    2   AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...
    3   AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...

Desired DF Output

   No. Ticker  ... AH Change                                                 v1
    0    1   AAPL  ...         -  AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...
    1    2   MSFT  ...         -  
    2    3   TSLA  ...         -  
    3    4     FB  ...         -  

Desired DF1 Output

    0   AAPL,MSFT,TSLA,FB,BRK-B,NVDA,TSM,JPM,V,JNJ,HD,...


    
    

Full Code

    import pandas as pd
    import requests
    import bs4
    import time
    import random
    
    
    headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/50.0.2661.102 Safari/537.36'}
    
    def testDf(version):
        url = 'https://finviz.com/screener.ashx?v={version}&r={page}&f=sh_outstanding_o1000&c=0,1,2,3,4,5,6,7,71,72&f=ind_stocksonly&o=-marketcap'
    
        page = 1
    
        screen = requests.get(url.format(version=version, page=page), headers=headers)
        soup = bs4.BeautifulSoup(screen.text, features='lxml')
        pages = int(soup.find_all('a', {'class': 'screener-pages'})[-1].text)
    
        data = []
        for page in range(1, 1 * pages, 20):
            print(version, page)
            screen = requests.get(url.format(version=version, page=page), headers=headers).text
            tables = pd.read_html(screen)
            tables = tables[-2]
            tables.columns = tables.iloc[0]
            tables = tables[1:]
            data.append(tables)
            time.sleep(random.random())
        return pd.concat(data).reset_index(drop=True).rename_axis(columns=None)
    
    df = testDf('152').copy()
    
    
    v1 = df['Ticker'].tolist()
    v1 = ",".join(map(str,v1))
    df['v1'] = v1
    df1 = df[['v1']]
    print(df)
    print (df1)

grouping = df.groupby('v1')

indices = []
for x in grouping.groups.values():
    indices.extend(x[1:])

df.loc[indices, 'v1'] = ''
df1 = pd.DataFrame(grouping.groups.keys())

Note: This changes df and is irreversible.