I have the following data

ticker  company sector  industryGroup   industry    subindustry currency    1999-07-31  1999-10-31  2000-01-31  ...
CompA   Health  Health  Health      Health      Health      USD     12.3        23.33       33.1        ...
CompB   Machine Machine Machine     Machine     Machine     USD     32.1        34.44       23.1        ...                                                             
CompC   Machine Machine Machine     Machine     Machine     USD     32.1        34.44       23.1        ...
CompD   Machine Machine Machine     Machine     Machine     USD     32.1        34.44       23.1        ...

The above is just a sample of the data that is in excel file. The prices go till 02-01-2024 and there are more company row 541 companies to be exact. I wrote a code that takes the columns starting from the first date and puts them in a dataframe with the date column title. Next I took the second column prices and put them in a column with ticker symbol name. The output should be the same as below.

Date        CompA    CompB    CompC    CompD
1999-07-31  12.3     32.1     32.1     32.1
1999-10-31  23.33    34.44    34.44    34.44
2000-01-31  33.1     34.44    34.44    34.44

The is my code:

import pandas as pd


bvmf = pd.read_excel('Market.xlsx')

df = pd.DataFrame()
df['Date'] = bvmf.iloc[0:1, 10:].columns

for i in range(len(bvmf)):
    ticker = bvmf['ticker'][i]
    df[ticker] = bvmf.iloc[i:i+1, 10:].values[0]

There are alot of values. My question, is there a better way to implement this code?