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def get_al_prices(result, periods=(1,5,21)):
    assets = result.index.get_level_values(1).unique()
    start_date = result.index.get_level_values(0)[0] 
    end_date = result.index.get_level_values(0)[-1]  + max(periods) * pd.tseries.offsets.BDay()
    pricing = get_pricing(assets, start_date, end_date, fields="open_price")
    return pricing 

def get_factor_data(result, 
                    factor_col, 
                    periods=(1,5,21),
                    quantiles=5,
                    bins=None, 
                    groupby=None, 
                    binning_by_group=False,
                    groupby_labels=None,
                    max_loss=0.35):

    pricing = get_al_prices(result, periods)
    
    factor_data = al.utils.get_clean_factor_and_forward_returns(factor=result[factor_col],
                                                                prices=pricing,
                                                                groupby=groupby,
                                                                binning_by_group=binning_by_group,
                                                                groupby_labels=groupby_labels,
                                                                quantiles=quantiles,
                                                                bins=bins,
                                                                periods=periods,
                                                                max_loss=max_loss)
    
    return pricing, factor_data

al.tears.create_full_tear_sheet(factor_data,
                                by_group=True,
                                long_short=True)

def get_al_prices(result, periods=(1,5,21)):
    assets = result.index.levels[1].unique()
    start_date = result.index.get_level_values(0)[0] 
    end_date = result.index.get_level_values(0)[-1]  + max(periods) * pd.tseries.offsets.BDay()
    pricing = get_pricing(assets, start_date, end_date, fields="open_price")
    return pricing 

factor_data = al.utils.get_clean_factor_and_forward_returns(factor=result['Factor_Column_Name'],
                                                            prices=pricing,
                                                            groupby=result['sector_code'],
                                                            by_group=False,
                                                            groupby_labels=MORNINGSTAR_SECTOR_CODES,
                                                            quantiles=5,
                                                            periods=(1,5,10))

# Create Event Tearsheet to Evaluate Alpha decay
al.tears.create_event_returns_tear_sheet(factor_data,
                                         pricing, 
                                         avgretplot=(0,65), 
                                         long_short=True,
                                         by_group=False)