Use the top method. No need to sort first. The top method first sorts and then takes the 'top n' of that sorted list. Remember that SlopeAdj is a factor object. It's not the actual data like a dataframe or series. It only has specific factor object methods. The method 'sort' is not one of them. Something like this should be what you want

def make_pipeline():

    slope_adj = SlopeAdj(inputs=[USEquityPricing.close],  window_length=100) 

    # Use the 'top' method to get a filter for the highest n equities  
    # No need to sort first. The top method does that for you.  
    # Use a mask to limit the results.  
    positive_slope = slope_adj > 0  
    is_tradable = positive_slope & my_equities  
    slope_adj_top_3 = slope_adj.top(3, mask=is_tradable)

    return Pipeline(  
        columns={  
            'slope_adj': slope_adj},  
        screen = is_tradable & slope_adj_top_3  
        )

It's a good practice, if one will be applying a filter to the results, to use that filter as a mask to the top method. Otherwise, there is the chance that one will fetch the top n securities but then filter them out and perhaps leave none. Maybe this is the desired result but typically not.

Also, it's great you are debugging your custom factor and pipeline logic in a notebook before using it in an algo. It's generally easier to debug, but moreover, one can easily display the results, perhaps plot them, and verify they are what is expected. Keep it up!

Look at the methods that one can use with factors in the docs https://www.quantopian.com/docs/api-reference/pipeline-api-reference#methods-that-create-filters

See attached notebook for this pipeline in action.

Dmitry,

Try this:

is_tradable = slope_adj.top(3,  mask = my_equities)  

result.sort_index()  

Equity(114 [ADBE]) 0.000913
Equity(5061 [MSFT]) 0.001387
Equity(28016 [CMG]) 0.002009

Thanks a lot to both of you. Indeed very helpful