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Could someone please point me in the right direction with respect to OHLC data timeframe conversion with Pandas ? What I'm trying to do is build a Dataframe with data for higher timeframes, given data with lower timeframe. For example, given I have the following one-minute (M1) data: Open High Low Close Volume Date 1999-01-04 10:22:00 1.1801 1.1819 1.1801 1.1817 4 1999-01-04 10:23:00 1.1817 1.1818 1.1804 1.1814 18 1999-01-04 10:24:00 1.1817 1.1817 1.1802 1.1806 12 1999-01-04 10:25:00 1.1807 1.1815 1.1795 1.1808 26 1999-01-04 10:26:00 1.1803 1.1806 1.1790 1.1806 4 1999-01-04 10:27:00 1.1801 1.1801 1.1779 1.1786 23 1999-01-04 10:28:00 1.1795 1.1801 1.1776 1.1788 28 1999-01-04 10:29:00 1.1793 1.1795 1.1782 1.1789 10 1999-01-04 10:31:00 1.1780 1.1792 1.1776 1.1792 12 1999-01-04 10:32:00 1.1788 1.1792 1.1788 1.1791 4 which has Open, High, Low, Close (OHLC) and volume values for every minute I would like to build a set of 5-minute readings (M5) which would look like so: Open High Low Close Volume Date 1999-01-04 10:25:00 1.1807 1.1815 1.1776 1.1789 91 1999-01-04 10:30:00 1.1780 1.1792 1.1776 1.1791 16 So the workflow is that: Open is the Open of the first row in the timewindow High is the highest High in the timewindow Low is the lowest Low Close is the last Close Volume is simply a sum of Volumes There are few issues though: the data has gaps ( note there is no 10:30:00 row) the 5-minute intervals have to start at round time, e.g. M5 starts at 10:25:00 not 10:22:00

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