You can add a filter by the primary symbol:

.filter(fundamentals.company_reference.primary_symbol == 'SPY')

Or you can filter by the sid:

.filter(fundamentals.valuation.sid == 8554)

EDIT: I misread your question, I realize now you're asking about adding this filter in pipeline. You can do this using a screen: https://www.quantopian.com/help/#quantopian_pipeline_Pipeline

Hi Alisa,

Thanks for your response. I was able to successfully set up a pipeline screen for market cap; this is commented out in the code below. However, when I tried to modify this to filter based on primary symbol I got the following error message: "Runtime exception: NotPipelineCompatible: 0079 company_reference.primary_symbol is not currently available in the Pipeline API". Do you have any recommendation on how to filter based on symbol/sid using a pipeline screen?

Thanks!

import numpy as np
import pandas as pd
from scipy import stats
from pytz import timezone
import datetime
import math
import time
import functools
import random
import itertools
from statsmodels.stats.moment_helpers import cov2corr, corr2cov, se_cov
from quantopian.algorithm import attach_pipeline, pipeline_output
from quantopian.pipeline import Pipeline
from quantopian.pipeline.data.builtin import USEquityPricing
from quantopian.pipeline.data import morningstar
from quantopian.pipeline.factors import SimpleMovingAverage, Latest, EWMSTD, EWMA
from quantopian.pipeline import CustomFactor

class MarketCap(CustomFactor):

#inputs = [morningstar.valuation.market_cap]  
#window_length = 1

#def compute(self, today, assets, out, market_cap):  
    #out[:] = market_cap  

class Primary_symbol(CustomFactor):

inputs = [morningstar.company_reference.primary_symbol]  
window_length = 1

def compute(self, today, assets, out, primary_symbol):  
    out[:] = primary_symbol  

def initialize(context):

context.stock=symbol('SPY')  

context.buy_flag=False  
context.sell_flag=False  

pipe = Pipeline()  
pipe = attach_pipeline(pipe, name='pipeline')  
context.sma_short= SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=50)  
pipe.add(context.sma_short, "sma_short")  
context.sma_long= SimpleMovingAverage(inputs=[USEquityPricing.close], window_length=100)  
pipe.add(context.sma_long, "sma_long")  

#pipe.add(MarketCap(), "Market_Cap")  
pipe.add(Primary_symbol(), "Primary_symbol")  

#market_cap = morningstar.valuation.market_cap.latest  
primary_symbol=morningstar.company_reference.primary_symbol.latest  

#market_cap_filter = (market_cap > 200000000000)  
name_filter = (primary_symbol == 'SPY')  
#pipe.set_screen(market_cap_filter)  
pipe.set_screen(name_filter)  

schedule_function(trading, date_rule=date_rules.every_day(),            time_rule=time_rules.market_open(hours=1))  

def before_trading_start(context,data):

results = pipeline_output('pipeline')  
print results.head(5)  

if context.sma_short > context.sma_long and context.portfolio.positions_value == 0:  
    context.buy_flag=True  
else:  
    context.buy_flag=False  
if context.sma_short < context.sma_long and context.portfolio.positions_value>0:  
    context.sell_flag=True  
else:  
    context.sell_flag=False

def trading(context, data):
if context.buy_flag == True:
order_value(context.stock, context.portfolio.cash)
if context.sell_flag == True:
order_target(context.stock, 0)

def handle_data(context, data):
record(positions=context.portfolio.positions_value,
cash=context.portfolio.cash,
buy_flag=context.buy_flag,
sell_flag=context.sell_flag)

Tommy,
Attached is an example backtest that filters the pipeline output for a single stock.

KR

Hey Karen,

Thanks! That worked perfectly. Would you be able to take a look at my latest post (same code, new problem):

https://www.quantopian.com/posts/having-trouble-creating-trading-signals-with-pipeline