Calculation of stock values with yfinance and python - python-3.x

Question

I would like to make some calculations on stock prices in Python 3 and I have installed the module yfinance.
I try to get an individual value like this:
import yfinance as yf
#define the ticker symbol
tickerSymbol = 'MSFT'
#get data on this ticker
tickerData = yf.Ticker(tickerSymbol)
#get the historical prices for this ticker
tickerDf = tickerData.history(period='1d', start='2015-1-1', end='2020-12-30')
row_date = tickerDf[tickerDf['Date']=='2020-12-30']
value = row_date.Open.item()
#see your data
print (value)
But when I run this, it says:
KeyError: 'Date'
Which is strange because when I do this, it works well and I have the column Date:
import yfinance as yf
#define the ticker symbol
tickerSymbol = 'MSFT'
#get data on this ticker
tickerData = yf.Ticker(tickerSymbol)
#get the historical prices for this ticker
tickerDf = tickerData.history(period='1d', start='2015-1-1', end='2020-12-30')
#row_date = tickerDf[tickerDf['Date']=='2020-12-30']
#value = row_date.Open.item()
#see your data
print (tickerDf)
I get the following result:
G:\python> python test.py
Open High Low Close Volume Dividends Stock Splits
Date
2014-12-31 41.512481 42.143207 41.263744 41.263744 21552500 0.0 0
2015-01-02 41.450302 42.125444 41.343701 41.539135 27913900 0.0 0
2015-01-05 41.192689 41.512495 41.086088 41.157158 39673900 0.0 0
2015-01-06 41.201567 41.530255 40.455355 40.553074 36447900 0.0 0
2015-01-07 40.846223 41.272629 40.410934 41.068310 29114100 0.0 0
... ... ... ... ... ... ... ...
2020-12-22 222.690002 225.630005 221.850006 223.940002 22612200 0.0 0
2020-12-23 223.110001 223.559998 220.800003 221.020004 18699600 0.0 0
2020-12-24 221.419998 223.610001 221.199997 222.750000 10550600 0.0 0
2020-12-28 224.449997 226.029999 223.020004 224.960007 17933500 0.0 0
2020-12-29 226.309998 227.179993 223.580002 224.149994 17403200 0.0 0
[1510 rows x 7 columns]

Answer 1

Under the hood, yfinance uses a Pandas data frame to create a Ticker. In this dataframe, Date isn't an ordinary column, but is instead a name given to the index (see line 240 in base.py of yfinance). The index column behaves differently than other columns and actually can't be referenced by name. You can access it using TickerDf.index=='2020-12-30' or by turning it into a regular column using reset_index as explained in another question. Searching through an index is faster than searching a regular column, so if you are looking through a lot of data, it will be to your advantage to leave it as an index.