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B', 'BHI', 'BIIB', 'BK', 'BLK', 'BLL', 'BMY', 'BRCM', 'BRK.

The S&P 500 stock market index, maintained by S&P Dow Jones Indices, comprises 505 common stocks issued by 500 large-cap companies and traded on American stock exchanges, and covers about 80 percent of the American equity market by capitalization.

If you’ve been away from the dating world for a while, diving back in can be intimidating.

The index constituents and the constituent weights are updated regularly using rules published by S&P Dow Jones Indices.

Wouldn't it be nice if there is an option to set pandas to read ALL data? And my salute to Wes and other pandas contributors; pandas is great! I realized another way to do this is to use reader_csv, which accept URL, don't require a start date, and read entire csv from Yahoo.

Even for a 50 year old public company, the data is only ~50*200 = 10,000 rows. Datetime Index: 7330 entries, 1984-09-07 to 2013-10-01 Data columns (total 6 columns): Open 7330 non-null values High 7330 non-null values Low 7330 non-null values Close 7330 non-null values Volume 7330 non-null values Adj Close 7330 non-null values dtypes: float64(5), int64(1) Datetime Index: 7330 entries, 1984-09-07 to 2013-10-01 Data columns (total 6 columns): Open 7330 non-null values High 7330 non-null values Low 7330 non-null values Close 7330 non-null values Volume 7330 non-null values Adj Close 7330 non-null values dtypes: float64(5), int64(1) Thanks a lot, Nipun! It appears that the Yahoo stock data only goes back to January of 1962.

Once the panels and dataframes are created you can slice by date index.

Note, you may want to use 'Adj Close' instead of 'Close' since you are going back far in the past.

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