I have a csv file with 1 minute stock data spanning multiple days. Each day runs from 9:30 to 16:00.
Some of the minutes in the time series are missing: (here 2013-09-16 09:32:00 and 2013-09-17 09:31:00 are missing)
2013-09-16 09:30:00,461.01,461.49,461,461,183507
2013-09-16 09:31:00,460.82,461.6099,460.39,461.07,212774
2013-09-16 09:33:00,460.0799,460.88,458.97,459.2401,207880
2013-09-16 09:34:00,458.97,460.08,458.8,460.04,148121
...
2013-09-16 15:59:00,449.72,450.0774,449.59,449.95,146399
2013-09-16 16:00:00,450.12,450.12,449.65,449.65,444594
2013-09-17 09:30:00,448,448,447.5,447.96,173624
2013-09-17 09:32:00,450.6177,450.9,449.05,449.2701,268715
2013-09-17 09:33:00,451.39,451.96,450.58,450.7061,197019
...
...
With pandas, how do I forward fill the series so every minute is present? I should look like this:
2013-09-16 09:30:00,461.01,461.49,461,461,183507
2013-09-16 09:31:00,460.82,461.6099,460.39,461.07,212774
2013-09-16 09:32:00,460.82,461.6099,460.39,461.07,212774 <-- forward filled
2013-09-16 09:33:00,460.0799,460.88,458.97,459.2401,207880
2013-09-16 09:34:00,458.97,460.08,458.8,460.04,148121
...
2013-09-16 15:59:00,449.72,450.0774,449.59,449.95,146399
2013-09-16 16:00:00,450.12,450.12,449.65,449.65,444594
2013-09-17 09:30:00,448,448,447.5,447.96,173624
2013-09-17 09:31:00,448,448,447.5,447.96,173624 <-- forward filled
2013-09-17 09:32:00,450.6177,450.9,449.05,449.2701,268715
2013-09-17 09:33:00,451.39,451.96,450.58,450.7061,197019
...
It also needs to account for if multiple consecutive minutes are missing...