I am using the following code to get all the data on municipal bonds. However, the number of bonds in the period that I am interested in is around 800,000. How can I download the data for sub periods with at most 10000 observations? IssueDate should be between 01/01/2015 and 12/31/2020.
df = rdp.Search.search( view = rdp.SearchViews.MunicipalInstruments, filter = "IssueDate ???????, top = 10000, select = "IssuerName, MaturityDate,\ IssueDate, IssuerState, CUSIP, ISIN,RIC" )
To filter based on date, try this:
response = rdp.Search.search( view = rdp.SearchViews.MunicipalInstruments, filter = "IssueDate ge 2015-01-01 and IssueDate le 2020-12-31 and \ IsActive eq true and AssetStatus ne 'MAT' and \ RIC ne null", top = 10, select = "IssuerName, MaturityDate, IssueDate, IssuerState, \ CUSIP, ISIN,RIC" )
With the above filter, you can see I added a couple of other possible filters that may be relevant that eliminates bonds that are inactive, have matured, etc. If you haven't already, refer to the Search Article which discusses a number of tips, including how to deal with large results that hit the limits. The article points to a series of examples, one of which demonstrates different techniques to deal with limits. In your case, you can certainly limit the results by issue date. The article also points to the Search Reference documentation which is where you can determine the syntax for creating date filters.
This should provide for a good start.
@eikon.user2 So you will of course run into issues extracting universes with larger that 10,000 return limit. You would need to split that up into small time slices and try running that iteratively:
SDate = dt.datetime(2018, 1, 1) EDate = dt.datetime(2020, 1, 1) midDate = SDate + dateutil.relativedelta.relativedelta(months=1) data = pd.DataFrame() while SDate < EDate: print(SDate,EDate,midDate) df = rdp.search( view = rdp.SearchViews.MunicipalInstruments, filter = "IssueDate ge " + SDate.strftime("%Y-%m-%d") + " and IssueDate lt " + midDate.strftime("%Y-%m-%d") +"", top = 10000, select = "IssuerName, MaturityDate,IssueDate, IssuerState, CUSIP, ISIN,RIC" ) if len(df)=10000: print('Search Returned >10K for ' + SDate.strftime("%Y-%m-%d") + ' and ' + midDate.strftime("%Y-%m-%d")) if len(data): data = pd.concat([data, df], axis=0) else: data = df SDate = SDate + dateutil.relativedelta.relativedelta(months=1) midDate = midDate + dateutil.relativedelta.relativedelta(months=1)
So here you can see even splitting the date window up into small one month chunks we still hit our limit in some months - so in this case you would need to change the chunks to say weeks - this is easy to do by changing the relative delta offsets to weeks instead of a month. I hope this can help.