Query regarding pulling percent change data using API

I need to pull up 1M Price change data and percent change data for financial metrics like EPS and Dividend yield for a selected universe. How do we pull them up using the ld.get data end point.

Universe: RELI.NS, ADEL.NS, BRTI.NS, How do we get this?

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Accepted answers

Jirapongse

@Hemant

Typically, the ld.get_data method requires the universe, fields, and parameters which is similar to the TR function. Therefore, you can apply the parameters used in the TR function to the ld.get_data method.

For example:

df = ld.get_data(
    universe = ['RELI.NS','ADEL.NS','BRTI.NS'],
    fields = ['PERCENT_CHG(TR.PriceClose(sdate=2025-01-01),tr.priceclose(sdate=2025-01-01-1AW))'],
    parameters = {'SDate':'2025-01-01'})

print(df)


df1 = ld.get_data(
    universe = ['RELI.NS','ADEL.NS','BRTI.NS'],
    fields = ['TR.HistPE(Period=FY0); TR.PtoEPSMeanEst(Period=FY1); TR.PtoEPSMeanEst(Period=FY2)'],
    parameters = {'SDate':'2025-01-01'})
print(df1)

You can also refer to the examples of LSEG Data Library for Python on GitHub.

Jirapongse

@Hemant

Is it this one?

start_date=datetime(date.today().year, 1, 1).strftime("%Y-%m-%d")
cons_metrics_calulated = ["TR.CommonName", f'PERCENT_CHG(TR.PriceClose(SDATE={start_date} ),TR.PriceClose(SDATE={start_date} -1AW))']

cons_df_calculated = ld.get_data(
    universe= ['RELI.NS','ADEL.NS','BRTI.NS'],
    fields= cons_metrics_calulated,
    parameters = {'SDate': start_date}
    )

cons_df_calculated

All comments

Jirapongse

@Hemant

Thank you for reaching out to us.

This forum is dedicated to software developers using LSEG APIs. The moderators on this forum do not have deep expertise in every bit of content available through LSEG products, which is required to answer content questions such as this one.

The best resource for content questions is the Helpdesk support team, which can be reached by submitting queries through LSEG Support. The support team will either have the required content expertise ready available or can reach out to relevant content experts to get the answer for you.

You need to ask for the Excel formula, such as =RDP.Data, that can be used to retrieve the required data. Then, we can help you converting that formula to Python code.

Otherwise, you can use the Data Item Browser tool to search for fields and parameters.

Please include the URL of this discussion in your raised question to prevent it from being redirected back to this Q&A forum.

Hemant

Thanks for the message. I already have these data points in excel. But I am not able to change that to pulling via API.

For example: =IF($B$1,TR($AQ$6:$AQ$456,"PERCENT_CHG(TR.PriceClose(sdate=#1),tr.priceclose(sdate=#1-1AW))","SDate=#1 NULL=BLANK",H$6:H$456,$B$2))

=IF($B$1,TR($AQ$6:$AQ$456,"TR.HistPE(Period=#1); TR.PtoEPSMeanEst(Period=#2); TR.PtoEPSMeanEst(Period=#3)","Sdate=#4 NULL=BLANK",$P$6:$R$456,"FY0","FY1","FY2",$B$2))

How to get this using APIs?

Jirapongse

@Hemant

For example:

df = ld.get_data(
    universe = ['RELI.NS','ADEL.NS','BRTI.NS'],
    fields = ['PERCENT_CHG(TR.PriceClose(sdate=2025-01-01),tr.priceclose(sdate=2025-01-01-1AW))'],
    parameters = {'SDate':'2025-01-01'})

print(df)


df1 = ld.get_data(
    universe = ['RELI.NS','ADEL.NS','BRTI.NS'],
    fields = ['TR.HistPE(Period=FY0); TR.PtoEPSMeanEst(Period=FY1); TR.PtoEPSMeanEst(Period=FY2)'],
    parameters = {'SDate':'2025-01-01'})
print(df1)

You can also refer to the examples of LSEG Data Library for Python on GitHub.

Hemant

Thanks
How do I dynamically access the dates here inside the api call , for example start date below

start_date=datetime(date.today().year, 1, 1).strftime("%Y-%m-%d")
cons_metrics_calulated = ["TR.CommonName", 'PERCENT_CHG(TR.PriceClose(SDATE=@MyStartDate ),TR.PriceClose(SDATE=@MyStartDate -1AW))']

cons_df_calculated = ld.get_data(
universe= ['RELI.NS','ADEL.NS','BRTI.NS'],
fields= cons_metrics_calulated,
parameters = {'MyStartDate': start_date}
)

Jirapongse

@Hemant

Is it this one?

start_date=datetime(date.today().year, 1, 1).strftime("%Y-%m-%d")
cons_metrics_calulated = ["TR.CommonName", f'PERCENT_CHG(TR.PriceClose(SDATE={start_date} ),TR.PriceClose(SDATE={start_date} -1AW))']

cons_df_calculated = ld.get_data(
    universe= ['RELI.NS','ADEL.NS','BRTI.NS'],
    fields= cons_metrics_calulated,
    parameters = {'SDate': start_date}
    )

cons_df_calculated

Hemant

Thanks a lot @Jirapongse

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