Hi Dev Team, can you please help and assist on the client's query

CVSS

script_compressed.pdf

You may refer to the compressed script in the PDF . We tried replicating but getting the same error as well.

Is there a problem with the codebook? It is taking a long time to load the data, and all the variable columns are completely filled with NAs.

import pandas as pd
import numpy as np
import refinitiv.data as rd # refinitiv
import time
from refinitiv.data.discovery import Screener # buscar screener de firmas
from pandas import read_csv # leitura de csv
from datetime import datetime
from IPython.display import display

abre sessao refinitiv
rd.open_session()


vars_t = [
'TR.TickerSymbol',
'TR.CompanyName',
'TR.ExchangeCountry',
'TR.Instrument',
'TR.TotalAssets.Date',
'TR.OperatingIncome',
'TR.TotalAssets',
'TR.F.NetIncBefMinIntr',
'TR.TotalEquity',
"TR.IncorporationDate",
"TR.CompanyInceptionDate",


'TR.CompanyMarketCap',
'TR.CurrentPortionLongTermDebt',
'TR.LongTermDebt',


'TR.SharesOutstanding',
'TR.PriceClose',


'TR.AccumulatedVolume',
'TR.Turnover',


'TR.IPODate',


'TR.IntangibleAssets',
'TR.NetIntangibleAssets',
'TR.Goodwill',
'TR.Trademarks',
'TR.ResearchAndDevelopment',
'TR.Revenue',


'TR.TRBCEconomicSector',


'TR.NetSalesRevenue',


'TR.F.IntangExclGoodwNetTot',
'TR.F.BrandsPatentsGross',
'TR.F.BrandsPatentsAccumAmort',
'TR.F.BrandsPatentsNet'
]

parametros contabeis
parametros anuais
parms={
'Period': 'FY0',
'Frq':'FY',
'EDate': '2003-01-01',
'SDate': '0FY',
#'Curn': 'Native' # para moeda local
'Curn': 'USD'
}

parametros trimestrais
'''parms_q={
'Period': 'FQ0',
'Frq':'FQ',
'EDate': '2000-01-01',
'SDate': '0FQ',
'Curn': 'USD'
}'''



define screener
rics = Screener('U(IN(Equity(active or inactive, public, primary))/UNV:Public/), '
'IN(TR.HQCountryCode,"BR","CO","MX","PE","CL"),'
'IN(TR.InstrumentType,"Ordinary Shares","Preference Shares","Unit"), ')




print(list(rics))


df = rd.get_data(
universe = rics,
fields = vars_t,
parameters = parms
)
display(df)

salva excel com dados coletados no diretório principal
df.to_excel('df_principal.xlsx', index=False)

Jirapongse

@CVSS

Thank you for reaching out to us.

I can run it properly in CodeBook.

import pandas as pd

import numpy as np

import lseg.data as rd # refinitiv

import time

from lseg.data.discovery import Screener # buscar screener de firmas

from pandas import read_csv # leitura de csv

from datetime import datetime

from IPython.display import display



rd.open_session()


vars_t = [

    'TR.TickerSymbol',

    'TR.CompanyName',

    'TR.ExchangeCountry',

    'TR.Instrument',

    'TR.TotalAssets.Date',

    'TR.OperatingIncome',

    'TR.TotalAssets',

    'TR.F.NetIncBefMinIntr',

    'TR.TotalEquity',

    "TR.IncorporationDate",

    "TR.CompanyInceptionDate",

    'TR.CompanyMarketCap',

    'TR.CurrentPortionLongTermDebt',

    'TR.LongTermDebt',

    'TR.SharesOutstanding',

    'TR.PriceClose',

    'TR.AccumulatedVolume',

    'TR.Turnover',

    'TR.IPODate',

    'TR.IntangibleAssets',

    'TR.NetIntangibleAssets',

    'TR.Goodwill',

    'TR.Trademarks',

    'TR.ResearchAndDevelopment',

    'TR.Revenue',

    'TR.TRBCEconomicSector',

    'TR.NetSalesRevenue',

    'TR.F.IntangExclGoodwNetTot',

    'TR.F.BrandsPatentsGross',

    'TR.F.BrandsPatentsAccumAmort',

    'TR.F.BrandsPatentsNet'

]


parms={

    'Period': 'FY0',

    'Frq':'FY',

    'EDate': '2003-01-01',

    'SDate': '0FY',

    #'Curn': 'Native' # para moeda local

    'Curn': 'USD'

    }


rics = Screener('U(IN(Equity(active or inactive, public, primary))), '

    'IN(TR.HQCountryCode,"BR","CO","MX","PE","CL"),'

    'IN(TR.InstrumentType,"Ordinary Shares","Preference Shares","Unit"), ')


print(len(list(rics)))


df = rd.get_data(

    universe = rics,

    fields = vars_t,

    parameters = parms

    )

display(df)


df.to_excel('df_principal.xlsx', index=False)

It takes a lot of time because the code requests data for a lot of items. The client may use chunk requests instead as mention in this LSEG Data Library Vol.3 : Calls That Survives Scale article.

I saw a lot of blank data (NA) in the excel file.

Please contact the content support team directly to verify it.