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How to access the time stamp from run_pipeline return

Hello, all
I have a question that need you help. I googled around and searched on this forum, but I still have no idea.
I run a pipe line to screen all stocks that meet my criteria for a period (a year, for example). It works fine. After I print out, I can see the time stamp with all records.
I need count how many stocks that meet my criteria each day. How can I do that? It seems that there is no column called 'timestamp' or 'datetime', etc. How can I access the time stamp?

jason

3 responses

The output of a pipeline is a pandas dataframe with a multi-index. Index level 0 are the dates while level 1 are the securities. The 'timestamp' isn't a column but rather in the index. So to count the stocks in the pipeline by day, first group by level 0 then use the count method. Something like this.

# Assumes we have previously defined the pipe as 'pipe'  
result = run_pipeline(pipe, '2017-01-01', '2017-12-31')  
result.index.rename(['date', 'stock'], inplace=True)  
result.groupby(level='date').my_criteria.count()  

Is this something like you were looking for? See the attached notebook which also shows how the results can easily be plotted.

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Dan
That's exactly what I need. Thanks

jason

Thanks Dan!