For loop in RIC screener search string
Hello, I would like to screen for companies through a for loop. I would like to iterate on industry code, but I cannot get the iterators to work with the proper package syntax. Looking through the below code, can you tell me where I am going wrong? (Note, the need for the loop arises because my full search, and below is just a shortened sample, is hitting download limits, so I am trying to break it up.)
import eikon as rd
import pandas as pd
from datetime import date
rd.set_app_key('8__________1')
indcode = [52,53,54,57]
syntax = f"SCREEN(U(IN(Equity(active,public,primary)))," \
"IN(TR.HQCountryCode,GB)," \
"IN(TR.TRBCEconSectorCode,{i}),CURN=USD)"
CATfields = ["TR.CommonName", "TR.HeadquartersCountry"]
df1 = []
for i in indcode:
data1, err = rd.get_data(syntax, CATfields)
df1.append(data1)
df1 = pd.concat(data1)
print(df1)
Best Answer
-
Hi @LRE42 ,
The issue is coming from 'syntax' formatted string with i:
- in Python, formatted string doesn't support splitted multiline with '\'
- it need to be evaluated for each i value in the loop.
Your issue can be fixed with following update:
import eikon as rd
import pandas as pd
from datetime import date
rd.set_app_key('8__________1')
indcode = [52,53,54,57]
CATfields = ["TR.CommonName", "TR.HeadquartersCountry"]
syntax = "SCREEN(U(IN(Equity(active,public,primary)))," \
"IN(TR.HQCountryCode,GB),"
df1 = []
for i in indcode:
data1, err = rd.get_data(
syntax + f"IN(TR.TRBCEconSectorCode,{i}),CURN=USD)",
CATfields)
df1.append(data1)
df1 = pd.concat(data1)
print(df1)0
Answers
-
Just an update !
For splitted multiline string, formatted string can be used with this way (only third line is formatted with i parameter):
syntax = "SCREEN(U(IN(Equity(active,public,primary)))," \
"IN(TR.HQCountryCode,GB)," \
f"IN(TR.TRBCEconSectorCode,{i}),CURN=USD)"But it still need to be evaluated in the loop for each indcode value.
1 -
Hi -- thank you for this. It almost resolved my problem, except I had to make one more edit in the names of my tables in the foor loop. Here is the code I used to get this working:
import eikon as rd
import pandas as pd
rd.set_app_key('8_________1')
indcode = [52, 53, 54, 57]
CATfields = ["TR.CommonName", "TR.HeadquartersCountry"]
syntax = "SCREEN(U(IN(Equity(active,public,primary)))," \
"IN(TR.HQCountryCode,GB),"
data2 = []
for i in indcode:
data1, err = rd.get_data(
syntax + f"IN(TR.TRBCEconSectorCode,{i}),CURN=USD)",
CATfields)
data2.append(data1)
df1 = pd.concat(data2)
print(df1)0
Categories
- All Categories
- 6 AHS
- 37 Alpha
- 161 App Studio
- 4 Block Chain
- 4 Bot Platform
- 16 Connected Risk APIs
- 47 Data Fusion
- 30 Data Model Discovery
- 608 Datastream
- 1.3K DSS
- 577 Eikon COM
- 4.9K Eikon Data APIs
- 7 Electronic Trading
- Generic FIX
- 7 Local Bank Node API
- Trading API
- 2.7K Elektron
- 1.3K EMA
- 236 ETA
- 519 WebSocket API
- 33 FX Venues
- 10 FX Market Data
- 1 FX Post Trade
- 1 FX Trading - Matching
- 12 FX Trading – RFQ Maker
- 5 Intelligent Tagging
- 2 Legal One
- 20 Messenger Bot
- 2 Messenger Side by Side
- 9 ONESOURCE
- 7 Indirect Tax
- 59 Open Calais
- 264 Open PermID
- 39 Entity Search
- 2 Org ID
- PAM
- PAM - Logging
- 8.4K Private Comments
- 6 Product Insight
- Project Tracking
- ProView
- ProView Internal
- 20 RDMS
- 1.4K Refinitiv Data Platform
- 367 Refinitiv Data Platform Libraries
- 3 Refinitiv Due Diligence
- LSEG Due Diligence Portal API
- 3 Refinitiv Due Dilligence Centre
- Rose's Space
- 1.1K Screening
- 18 Qual-ID API
- 13 Screening Deployed
- 23 Screening Online
- 10 World-Check Customer Risk Screener
- 990 World-Check One
- 44 World-Check One Zero Footprint
- 45 Side by Side Integration API
- Test Space
- 3 Thomson One Smart
- 1.2K TR Internal
- Global Hackathon 2015
- 2 Specialists Who Code
- 10 TR Knowledge Graph
- 150 Transactions
- 142 REDI API
- 1.7K TREP APIs
- 4 CAT
- 21 DACS Station
- 117 Open DACS
- 1.1K RFA
- 103 UPA
- 172 TREP Infrastructure
- 224 TRKD
- 886 TRTH
- 5 Velocity Analytics
- 5 Wealth Management Web Services
- 59 Workspace SDK
- 9 Element Framework
- 5 Grid
- 13 World-Check Data File
- Yield Book Analytics
- 46 中文论坛