Sort Pipeline output by Symbol

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Sort Pipeline output by Symbol

posted

I cannot find in the documentation how to do this simple thing.
I have a simple Pipeline and want to sort the results by symbol or sid.

Here's what I am trying to do: sort the "result" by symbol --- should be simple enough?

class StdDev(CustomFactor):  
    def compute(self, today, asset_ids, out, values):  
        # Calculates the column-wise standard deviation, ignoring NaNs  
        out[:] = numpy.nanstd(values, axis=0)

def make_pipeline():  
    mean_close_10 = SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=10)  
    volume_filter = (USEquityPricing.volume.latest > 1000000)  
    std_dev = StdDev(inputs=[USEquityPricing.close], window_length=5)  
    std_filter = (std_dev > 2)  
    price_filter = (USEquityPricing.close.latest > 5) and (USEquityPricing.close.latest < 50)  
    return Pipeline(  
        columns={  
            '10 MA of closing price' : mean_close_10,  
            'Volume': USEquityPricing.volume.latest,  
            'std_dev': std_dev  
        } , screen=(std_filter & price_filter & volume_filter)  
    )

result = run_pipeline(make_pipeline(), '2016-12-15', '2016-12-15')

result.sort_values(symbol)   <----------this doesn't work.   How do you sort output by Symbol/Sid ????

Help !

5 responses

The dataframe returned from a pipeline has a multi-index by date and security (inside the research environment). The sort_values method only works on columns. Use the sort_index method instead. You could also reset the index using the reset_index method which would turn the security index into a regular column. You could then use the sort_values method.

# result has a multi-index with date as level_0 and the equity object as level_1  
# use sort_index to sort the dataframe on the index.  
# this will sort by SID  
result.sort_index(axis=0, level=1, ascending=True, inplace=True)  
result

Thank you. Sorting by SID, works. I have a better idea now what to do. I'll examine the index more closely. Thanks again.

Hm, @Dan - thank you!

How about trying to sort by another column, let's say -'Volume' - in this case?

As mentioned above, the dataframe returned from a pipeline indexed by date and security (inside the research environment). The sort_values method can be used to sort by columns. See the pandas docs https://pandas.pydata.org/pandas-docs/version/0.18/generated/pandas.DataFrame.sort_values.html . So something like this

# use sort_values to sort the dataframe on one or more columns.  
# this will sort by market_cap (assuming one of the column names is 'market_cap'  
result.sort_values('market_cap')  
result

Additionally, an interactive way to sort and filter dataframes in the research environment is to use qgrid. See this post https://www.quantopian.com/posts/qgrid-now-available-in-research-an-interactive-grid-for-sorting-and-filtering-dataframes .

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Yup, pardon me, now I did it! Thanks a lot!

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In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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.

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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 Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian 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.