Can I get the value of a index if there seems to be multiple indexes? [duplicate]

I have this df:

ticker  GSPC.INDX   IBM.US  US10Y.INDX  adjustedRF  index_returns   equity_returns  excess_market_returns   alpha   beta
date                                    
2013-11-04  1764.180033 179.116667  2.634467    0.001043    0.001218    -0.002539   0.000175    -0.001419   0.647420
2013-11-05  1767.130033 179.103333  2.643033    0.001047    0.001670    -0.000074   0.000624    -0.001423   0.647479
2013-11-06  1760.203333 179.013333  2.642467    0.001047    -0.003941   -0.000500   -0.004988   -0.001427   0.647593
2013-11-07  1762.750000 179.726667  2.668500    0.001057    0.001441    0.003987    0.000385    -0.001428   0.647597
2013-11-08  1763.216667 180.956667  2.701867    0.001070    0.000263    0.006795    -0.000807   -0.001428   0.647452
... ... ... ... ... ... ... ... ... ...
2021-07-06  4351.336567 139.540000  1.368967    0.000542    0.002934    -0.016329   0.002392    -0.000276   0.391254
2021-07-07  4340.829900 139.780000  1.322733    0.000524    -0.002423   0.001710    -0.002947   -0.000276   0.391306
2021-07-08  4349.499833 140.693333  1.325433    0.000525    0.001990    0.006517    0.001465    -0.000275   0.391341
2021-07-09  4345.184800 141.130000  1.339500    0.000530    0.001308    0.006043    0.000782    -0.000276   0.391278
2021-07-10  4377.089850 141.220000  1.362000    0.000539    0.011215    0.005527    0.010676    -0.000271   0.391562
1992 rows × 9 columns

I had to pivot this table so I think ticker & date are indexes(?)

df.columns results in:

Index(['GSPC.INDX', 'IBM.US', 'US10Y.INDX', 'adjustedRF', 'index_returns',
       'equity_returns', 'excess_market_returns', 'alpha', 'beta'],
      dtype='object', name='ticker')

I wanted to create a new column for the year(I belive this does the trick – df['year'] = pd.to_datetime(df['date'],format='%Y') ) but it’s not finding the date column because I think it’s some kind of index?

How can I access it?

Answer

Your dataframe likely stores the dates in a DatetimeIndex. To access the year of each row in your dataframe, simply use df.index.year

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Answer