Infrastructure 360

(I apologise in advance to those to whom this question may sound stupid.)

I have just started using the LSEG data. I would really like to connect the "Infrastructure 360" app in Python, but I cannot seem to find a way to get the data through the API. It would be extremely useful to obtain the geolocations of the projects, mergers, and deals, as well as the financial information of the companies operating them. However, I am not able to find the "projects" in the API.

Thank you in advance,

Matilde

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jason.ramchandani01

@MatildeCiani Thanks for your question - so this is achievable using a screener query (using the SCREENER app) and the LD Library get_data function.

import lseg.data as ld

import pandas as pd

ld.open_session()

pjf_deals = []

year_ = ['2024','2025']
pjf_fields = ['TR.PJFAnnouncementDate','TR.PJFFinancedDate','TR.PJFProjectLocation',

'TR.PJFProjectCompany','TR.PJFProjectLongitude','TR.PJFProjectLatitude',

'TR.PJFProjecttCompanyImmParentPermID','TR.PJFProjecttCompanyUltParentPermID',

'TR.MnARelPJFSdcDealNumber','TR.MnARelatedProjectPermId','TR.PJFPkgTotalProjectCost',

'TR.PJFProjectCurrency']
for year in year_:

  df = ld.get_data("SCREEN(U(IN(DEALS)/UNV:DEALSPROJECTFINANCE/), IN(TR.PJFProjectUniverseType,""SDCPJF""), BETWEEN(TR.PJFFinancedDate," + str(year) + "0101," + str(year) + "1231)/dt:Date/)",

pjf_fields)

  if len(pjf_deals):

    pjf_deals = pd.concat([pjf_deals,df],ignore_index=True)

  else:

    pjf_deals = df

pjf_deals

Now you have some of the data you need you can further explore the companies etc using the Data Item Browser app (type DIB into the Launcher bar)

You can also add lots of data from the Project Finance deal dataset:

I hope this can help.

MatildeCiani

Hey,

Thank you for your reply. The code you provided does not run.

I managed to get the following code to work:

for year in year_:

    query = f"SCREEN(U(IN(DEALS)), IN(TR.PJFProjectUniverseType,\"SDCPJF\"), BETWEEN(TR.PJFFinancedDate,{year}0101,{year}1231))"


    df = ld.get_data(query, pjf_fields)


    if len(pjf_deals):

        pjf_deals = pd.concat([pjf_deals, df], ignore_index=True)

    else:

        pjf_deals = df


pjf_deals.head(10)


print("Total infrastructure project finance deals collected:")

print(len(pjf_deals))

However, I am under the impression that I am getting a subset of the projects. There are more than 180 000 projects on Workspace, and I am getting only 23 000 observations.

Any idea on how I could fix this? Would it be possible to filter directly based on 'TR.PJFProjectPrimaryIndustrySubSector'?

Sorry for this set of basic questions

Thanks

Jirapongse

@MatildeCiani

If it is about the screener, you may need to contact the helpdesk team to verify the screener formula.

For more information, please refer to this https://developers.lseg.com/en/article-catalog/article/find-your-right-companies-with-screener article.

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