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I ran into a duplicate index issue (as seen on your Github here) when using python in your research notebook. Is there a workaround so I can do tick-level research in python not c#? I don't see any mentioned in GH but I understand that is for the open-source edition.
Aside from not being the best at c#, I believe I can't plot in that language.
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Derek Melchin
Hi Desmond,
To get tick data, request a list of Tick objects instead of a DataFrame.
We will update the Research Environment docs to include this type of example. In the mean time, for more information, see History Requests.
Best,
Derek Melchin
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Dizzy
Thanks Derek Melchin that's brilliant that I can do it in py - just wondering how do I cast/operate on this object from there?Â
I take it the regular DF functions don't work on it; when I print(ticks) I get what I guess is the type:
Didn't see anything on this in History Requests but might have missed it.
Derek Melchin
Hi Desmond,
To operate on each individual tick, iterate through the `ticks` object.
To view the properties of the Tick class, see Ticks.
Regular DataFrame functions won't work on `ticks` because it's not a DataFrame object. However, if you want to format the data into a DataFrame, you could adjust the timestamps of the ticks so they are unique or add another level to the DataFrame index.
Best,
Derek Melchin
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
Dizzy
The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by QuantConnect. In addition, the material offers no opinion with respect to the suitability of any security or specific investment. QuantConnect makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances. All investments involve risk, including loss of principal. You should consult with an investment professional before making any investment decisions.
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