Python: disparity in fundamental data
If I use get_data, I'm able to get the current value. If I use get_timeseries, the most recent value is excluded. For example:
data = ek.get_timeseries('DST-STK-T-EIA', fields=['CLOSE','Timestamp'])
vs.
data = ek.get_data('DST-STK-T-EIA', 'CF_LAST')
I've obviously stripped-out dates, intervals, etc. from time_series, but including those yields the same result.
Best Answer
-
df =ek.get_timeseries(['DST-STK-T-EIA'],['CLOSE'],start_date='2010-03-01',interval='weekly')
dfThe above is fine - you are using real-time fields for the RIC which is an economic RIC:
data, err = ek.get_data('DST-STK-T-EIA', ['CF_LAST','CF_DATE'])
dataWhich will give you the last value but the date is the current date not the date of the last release which was on 25-04-2021.
I hope this can help.
1
Answers
-
@jason.ramchandani. Thank you. There must be some sort of lag for this, because I am now able to use my original get_timeseries code and it displays the most recent data (ignore the end_date; I've reused code throughout my project) :
inventories = ek.get_timeseries('DST-STK-T-EIA',
fields=['Close','Timestamp'],
start_date=(date.today()-timedelta(days=(13*365))).strftime("%Y-%m-%d"),
end_date=(date.today()+timedelta(days=(5*365))).strftime("%Y-%m-%d"),interval="weekly"
)
inventories['Timestamp'] = inventories.index
Anyway, thanks again for your response.
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