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Security Violation with Display Options

See security violation when simply wanting to access display options? What am I doing wrong?

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4 responses

Quantopian has chosen to blacklist certain methods and modules out of security concerns. The pandas get_option method is one of them.

In this specific case, the display.max_rowsoption is fixed and cannot be changed. This is to restrict the amount of data which could potentially be 'screen scraped' from the site. The agreements we have in place, and allow us to provide free data to our users, require that data cannot be copied off of our platform.

Sorry for any inconvenience of this precaution .

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Makes sense, Dan. I appreciate the feedback. Great platform and very glad to have the chance to learn how to use it.

In case it is helpful it others, I was trying to find a way to view a certain portion of a larger dataset, which seemed to always end up 'hidden' in the middle of the dataset when printed (the hidden part is indicated by the dotted ellipses).
I figured out how to slice the dataset by date, so that only those rows were displayed:
results.loc['2018-09-15':'2018-10-30']
A beginner's learnings.

Hi Dan,

I am encountering something similar - basically what I want to do is overlay weekly and monthly data on top of my main timeframe (daily). In order to do this, I have resampled the daily data and have calculated the same oscillators that I use with the daily data, using the resampled W and M data. All okay so far!

Now is where I run into trouble. I then need to resample the W and M data back down to daily observations, as my algorithm is centred on referencing a set of objects via a date (yesterday's date, retrospectively making decisions on yesterday's close). I noticed that the last observation in the resampled weekly and monthly intervals gets removed from my dataframe - which I think it is due to that timestamp being in the future (i.e. end of the current week, as my bins are labelled with the right hand side index). I have tried a series of workarounds but continue to violate your security policy as I need to adjust the final label in that dataframe and they are of datetime.timestamp type due to the resample outputs.. Pandas does not allow outputting of datetime.date in this instance for some reason.

Once the data is back down to daily observations, I remove any rows in the series that are beyond yesterday's close as they are irrelevant, however this method is necessary to allow a reference to the higher time frame data on a daily basis.

Confusing I know, but necessary for me to build this particular method into the algorithm. Have you encountered this issue in the past?

Thanks mate

Ideally what I'd like is for that final index value to not be removed from the series, I then wouldn't need such an unusual workaround :)