Resolved: pandas- convert/transpose columns to rows without using loop

stock_list = ['AAPL', 'TSLA', ' MSFT', 'COIN', 'META' ...... ]

df

    date     price_AAPLE    volume_AAPLE      price_TSLA   volume_TSLA      price_MSFT    volume_MSFT    ...
    01-01      187            324234            517         5346             128             45143
    01-02      124            234234            512         5436345          130             42345

cols = ['date', 'price', 'volume']

agg_df = pd.DataFrame()
for i in stock_list:
   dataframe = df[['date', f'price_{i}', f'volume_{i}']]
   dataframe.columns = cols 
   dataframe['stock'] = i
   agg_df = agg_df.append(dataframe)

   date     price    volume       stock         
   01-01      187    324234        AAPL       
   01-02      124    234234        AAPL       
   01-01      517     5346         TSLA 
   01-02      512    5436345       TSLA
   ....      ....    ....          ....

out = pd.wide_to_long(df, 
                      ['volume','price'], 
                      i = ['date'], 
                      j = 'stock', 
                      suffix = '\w+', 
                      sep='_').reset_index()
Out[27]: 
    date  stock   volume  price
0  01-01  AAPLE   324234    187
1  01-02  AAPLE   234234    124
2  01-01   TSLA     5346    517
3  01-02   TSLA  5436345    512
4  01-01   MSFT    45143    128
5  01-02   MSFT    42345    130