I've recently started using quantopian but its not really that intuitive for a newcomer. Im looking to check wether a stock in the stock universe was down the day before and also check if a particular stock is gapping down today. The pipelines make all this so counter intuitive (in my opinion) I've been used to Tradingviews pine script which is way more user friendly and I just simply can't wrap my head around the pipelines and how to properly do what I described.

For example when I try the following I get

import quantopian.algorithm as algo  
from quantopian.pipeline import Pipeline, CustomFactor  
from quantopian.pipeline.data.builtin import USEquityPricing  
from quantopian.pipeline.filters import QTradableStocksUS  
from quantopian.pipeline.filters.morningstar import Q500US  
from quantopian.pipeline.factors import PercentChange        

def initialize(context):  
    """  
    Called once at the start of the algorithm.  
    """  
    # Rebalance every day, 1 hour after market open.  
    schedule_function(ma_crossover_handling, date_rules.every_day(), time_rules.market_open(minutes=1))  
    set_benchmark(sid(19920))  
    context.QQQ = sid(19920)  
    # Create our dynamic stock selector.  
    algo.attach_pipeline(make_pipeline(), 'pipeline')


def make_pipeline():  
    """  
    A function to create our dynamic stock selector (pipeline). Documentation  
    on pipeline can be found here:  
    https://www.quantopian.com/help#pipeline-title  
    """

    # Base universe set to the QTradableStocksUS  
    base_universe = Q500US()  
    pipe = Pipeline(  
        columns={  
            'close': USEquityPricing.close.latest,  
            "open": USEquityPricing.open.latest,  
            "high": USEquityPricing.high.latest,  
            "low": USEquityPricing.low.latest,  
        },  
        screen=base_universe  
    )  
    return pipe

def before_trading_start(context, data):  
    """  
    Called every day before market open.  
    """  
    context.output = algo.pipeline_output('pipeline')

    # These are the securities that we are interested in trading each day.  
    context.security_list = context.output.index

def ma_crossover_handling(context, data):  
    for stock in context.security_list:  
        open_orders = get_open_orders()  
        price_history = history(bar_count=5, frequency='1d', field='price')  
        close_2_day_ago = price_history[stock][-3] # close two days ago  
        close_yesterday = price_history[stock][-2] # close of yesterday  
        open_today = price_history[stock][-1]  
        gap_percent = (open_today-close_yesterday)/close_yesterday*100  
        prevday = close_2_day_ago>close_yesterday  
        close_yesterdayQQQ = price_history[context.QQQ][-2] # close of yesterday  
        open_todayQQQ = price_history[context.QQQ][-1]  
        percentgapQQQ =(open_todayQQQ-close_yesterdayQQQ)/close_yesterdayQQQ*100  

KeyError: Equity(2 [HWM])
There was a runtime error on line 57.