Hello,

I'm testing EarningsCalendar Dataset from Eventvestor.
It appears to me that the design of the dataset might be misleading or the data availability is quite limited.

I'm using ADBE as an example and looking at the next_announcement data field.
Example below (backtesting from 6/10/2013-6/18/2013):

from quantopian.pipeline import Pipeline  
from quantopian.algorithm import attach_pipeline, pipeline_output  
from quantopian.pipeline.data.eventvestor import EarningsCalendar  
from quantopian.pipeline.factors.eventvestor import (  
    BusinessDaysUntilNextEarnings,  
    BusinessDaysSincePreviousEarnings  
)

def initialize(context):  
    schedule_function(get_stocks, date_rules.every_day(),  
                      time_rules.market_open(hours=1.0))  
    # Create and attach an empty Pipeline.  
    pipe = Pipeline()  
    pipe = attach_pipeline(pipe, name='pipeline')  
    # Construct Factors.  
    previous_earning = BusinessDaysSincePreviousEarnings()  
    next_announcement = EarningsCalendar.next_announcement.latest  
    recent_earning_report = (previous_earning < 1)  
    #pipe.add(previous_earning, 'previous_earning')  
    pipe.add(next_announcement, 'next_announcement')  
    pipe.set_screen(recent_earning_report)

def get_stocks(context, data):  
    results = pipeline_output('pipeline')  
    print results['next_announcement'][symbols('ADBE')]  

ADBE's earning date was on 6/18/2013, so I would expect that the next_announcement date should be known well before 6/18/2013, but the print results show that the value are all NaN from 6/10/2013 to 6/17/2013. The value (6/18/2013) is only shown on 6/18/2013.

Also, I checked AAPL for Q1 and Q2 2013, there are no earnings dates data at all (all NaN) for the periods. Having no data for stock like AAPL makes me feel that the dataset is not usable.

Thanks.
Wei