No can do. The mechanics of a pipeline only allow daily data. For minute data in a notebook use the 'get_pricing' method. In an algorithm use the 'data.history' method. Maybe take a look at this post https://www.quantopian.com/posts/updating-pipeline-every-minute-using-handle-data .

Question, you apparently already have the output you want using pandas methods. Why do you feel you need to write a custom factor?

Hi Dan, thx for quick reply, i want to see different moving average cross over trends in research for all equities, and see how the strategy might perform for 5 minute moving averages. I took a look at the post and others, and i was able to resample pricing data to get 5 minute data, but now i want to expand on that to all equities for a short period of time and see how the strategy might perform for different sectors. Not sure if this is the correct way to go about it or if i should i just take a look at a few stock for 5minute moving averages and then implement and algo backtest.

I think i was trying to analyze all equities at once in research ... i guess i cannot do that , thx for the reply, will take a look at different individual stocks and then attempt to write algo based on different filters, i think i was trying to do everything all at once!

If I understand correctly, the code above is what you want but it only get's a single stock (ie MSFT). You want to try this across a larger sample of securities? What you want to do is run pipeline first to return a 'universe' of securities, then use that list of securities as the input to the 'get_pricing' method. See the attached notebook.

Much appreciated Dan, i think this is what I need to be doing!