python u.s. ticker to permid lookup

mjg

using the python eikon data API, what is the easiest way to go from U.S. Stock ticker ('AAPL') or at worst ('AAPL.O' as necessary) to PermID?

if my focus is just on U.S. listed stocks just on Nyse and Nasdaq, is there a simple way to pull down a lookup of ticker to permid?

if there isn't a 'simple' solution for major u.s. stocks, what is the least complicated/most efficient way to pull a lookup table of ticker to permid

jonathan.legrand

Hi @mjg ,

Have you had a look at the EX-2.05.01-Symbology.ipynb examples? Do they provide the answer you're after?

mjg

thanks that definitely helps move things forward, but i am not quite at the solution i need yet

2 questions on 2 paths that could get me there

1. is there just some file that exists for all US equities thath as all of this data preloaded that i can just access more natively?

2. i now see in that notebook there is evidence i can pass a 'Ticker Symbol' (i.e. AAPL and not AAPL.O) using

symbol_conversion.TICKER_SYMBOL => TickerSymbol

is there any documentation around how the ticker symbols are defined, to make sure i am not making any bad assumptions?

mjg

put another way, if i enter a symbol like MUR this way, does it default to the U.S. MUR (murphy oil) vs the Canadian MUR (Murchison materials)?

response = symbol_conversion.Definition(

symbols=["MUR"],

).get_data()

is the why/how about that documented somewhere? thanks

mjg

yes and i tried asking a followup question or two - can you look at my followup messages? thanks

mjg

what about PBRa, LGFa, BRKb, CWENa, etc

how do i pass those in as TickerSymbol

and how would i go about understanding why that is

mjg

and finally why, when i query for TickerSymbol = 'PXD', for example, does RIC not come back with PXD.N but rather just PXD. in other words, why does RIC sometimes have the .N or .O suffix and sometimes not when queried with a standard US TickerSymbol

jonathan.legrand

Hi @mjg ,

1. For an excel file with all the data you're after, you can use screener and pandas' to_csv function.
2. For documentation on the RD lib, please see the Dev. Port..

For further information (e.g.: answering your content questions about Ticker Nomenclature in coments below); please ask on my.refinitiv.

mjg

you are suggesting i use a screener to generate the table for all US equities? and just make sure to query for all the pertinent symbology output fields for each? just trying to clarify your suggestion - thanks -

the question becomes circular when we talk about U.S. Equities, and then it starts to beg the question - well what about US ADRs? do i need to have a 'special screener' for those?... and so on ...

jonathan.legrand

Hi @mjg,

Yes, I think using the screener Python function is best in this case. You may choose to have seperate screeners for each security type you're after; I would actually suggest doing so, to ake sure you capture all of the securities you're after.