Adding yfinance historical price data onto dataframe without hard-coding dates (using dates already in the dataframe)

Question

The following code pulls balance sheet data using yfinance. I would like to get the close price as of the corresponding dates in the dataframe on the last row without hard coding dates.

import yfinance as yf

ticker_object = yf.Ticker('AAPL')
balancesheet = ticker_object.balancesheet

# Select specific rows and columns
selected_data = balancesheet.loc[['Share Issued', 'Tangible Book Value']]

selected_data

Current output:

Desired output:

Here is sample code to get price data:

import yfinance as yf

data = yf.download("AAPL", start="2017-01-01", end="2017-04-30")
data.head(3)

Output:

Answer 1

Because trades are close during weekends shift minimal dates for start by 3 days, then select Close columns and add new row by DataFrame.loc with Series.reindex with method='ffill', because Friday's close Price holds until open on Monday.

import yfinance as yf

ticker_object = yf.Ticker('AAPL')
balancesheet = ticker_object.balancesheet

start = balancesheet.columns.min() - pd.Timedelta(3, 'days')
end = balancesheet.columns.max()

data = yf.download("AAPL", period="5y")['Close']

#test data - missing 2023-09-30 because Saturday, so used Friday values
print (data.loc['2023-09-27':'2023-10-03'])
Date
2023-09-27    170.429993
2023-09-28    170.690002
2023-09-29    171.210007
2023-10-02    173.750000
2023-10-03    172.399994
Name: Close, dtype: float64

# Select specific rows and columns
selected_data = balancesheet.loc[['Share Issued', 'Tangible Book Value']]
selected_data.loc['Price'] = data.reindex(index=selected_data.columns, method='ffill')
print (selected_data)
                        2023-09-30     2022-09-30     2021-09-30  \
Share Issued         15550061000.0  15943425000.0  16426786000.0   
Tangible Book Value  62146000000.0  50672000000.0  63090000000.0   
Price                   171.210007     138.199997          141.5   

                        2020-09-30  
Share Issued         16976763000.0  
Tangible Book Value  65339000000.0  
Price                   115.809998