how to append a distinct value for each iteration to a pandas dataframe through a loop?

I am trying to add the stock name value for each iteration to it's corresponding data bulk upload to a pandas dataframe:

This is what I've tried so far:

from pandas_datareader import data as pdrimport requestsfrom bs4 import BeautifulSoupimport json, requestsimport pandas as pdimport reimport numpy as npimport pandas_datareader.data as webimport yfinance as yfinfrom tqdm import tqdmimport numpy as npimport datetimefrom datetime import timedelta################# fetch series names for sic ######################sic_emisoras_df = pd.json_normalize(    json.loads(        requests.get('https://www.bmv.com.mx/es/Grupo_BMV/BmvJsonGeneric?idSitioPagina=6&mercado=CGEN_SCSOP&tipoValor=CGEN_CASEO&random=5845')            .text            .split(';(', 1)[-1]            .split(')')[0]        )['response']['resultado']).dropna(axis=1, how='all')##################################################################### define time range:start=datetime.date.today()-datetime.timedelta(days=14)end=datetime.date.today()# fetch data# get all SIC names as liststock_names = sic_emisoras_df["cveCorta"].values.tolist()# append information per stock namesic_market_df = pd.DataFrame([])sic_market_df["stock_name"] = np.nanfor i in tqdm(stock_names):     # fetch data per stock_name    try:       yfin.pdr_override()       # append stock name       sic_market_df["stock_name"]=i       # fetch information by stock name       data = web.DataReader(i,start,end)       # append rows to empty dataframe       sic_market_df = sic_market_df.append(data)    except KeyError:       passprint("Fetched sic_market_df!")

And the output only fetches the name for the first iteration but gets NaN for every other bulk upload :

         stock_name Open    High       Low        Close   Adj   Close    Volume2024-02-20  ZS  14.500000   14.950000   14.490000   14.700000   14.700000   30253100.02024-02-21  ZS  14.590000   14.860000   14.570000   14.790000   14.790000   23032400.02024-02-22  ZS  14.940000   15.280000   14.890000   15.240000   15.240000   35702500.02024-02-23  ZS  15.150000   15.290000   14.950000   15.130000   15.130000   22914900.02024-02-26  ZS  15.130000   15.480000   15.130000   15.280000   15.280000   23675800.0

I would like to get a dataframe that identifies each iteration bulk upload with it's unique stock name, i.e, something like this:

             stock_name Open    High       Low        Close   Adj   Close    Volume    2024-02-20  ZS  14.500000   14.950000   14.490000   14.700000   14.700000   30253100.0    2024-02-21  ZS  14.590000   14.860000   14.570000   14.790000   14.790000   23032400.0    2024-02-22  ZS  14.940000   15.280000   14.890000   15.240000   15.240000   35702500.0    2024-02-23  ZS  15.150000   15.290000   14.950000   15.130000   15.130000   22914900.0    2024-02-26  ZS  15.130000   15.480000   15.130000   15.280000   15.280000   23675800.0...    ...      ...     ...          ...      ...     ...   ...        2024-02-20  AAPL    14.500000   14.950000   14.490000   14.700000   14.700000   30253100.0    2024-02-21  AAPL    14.590000   14.860000   14.570000   14.790000   14.790000   23032400.0    2024-02-22  AAPL    14.940000   15.280000   14.890000   15.240000   15.240000   35702500.0    2024-02-23  AAPL    15.150000   15.290000   14.950000   15.130000   15.130000   22914900.0    2024-02-26  AAPL    15.130000   15.480000   15.130000   15.280000   15.280000   23675800.0

package versions:

!pip show pandas.  #1.5.3!pip show beautifulsoup4  #4.12.3!pip show pandas-datareader  #0.10.0

Could you please assist on how to accomplish this?