The dataframe I am working with contains historical stock prices and looks like this : timestamp open high low close volume 0 1609459200 20830.70 21243.95 20830.7 21127.60 1663 1 1609718400 21288.00 21300.00 21065.0 21154.65 3043 2 1609804800 21154.65 21899.00 21011.0 21594.20 3048 ... The data is for January 1, 4 and 5 2021 and there are no rows for 2nd and 3rd of January as these are Saturdays and Sundays. I wish to reindex this dataframe so that I can have these dates as well in my dataframe with forward filled data. I have found dti = pandas.date_range("2021-01-01", periods=3, freq="D") which generates dates but not as unix second timestamps. DatetimeIndex(['2021-01-01', '2021-01-02', '2021-01-03'], dtype='datetime64[ns]', freq='D') What is the easiest way to generate unix timestamps such as 1609459200 using pandas. Continue reading...
