How can one define empty (NULL) fields in a Python request for Refinitiv Data Library?

IoannisG

The Python command

df=rd.get_data('AAPL.OQ', ['TR.ISINCode', , , 'TR.InstrumentType'])

returns a syntax error.

What I would like to do is for formatting purposes to have some empty (NULL) fields between the fields TR.ISINCode and TR.InstrumentType. How can empty fields be specified?

Gurpreet

Hi @IoannisG,

Its always a good idea to separate the data from display. You cannot add null fields into the request and it is not a good idea anyways. Formatting the displayed data should be done with dataframe. Pandas has couple of options for column width settings which you can utilize.

You can even iterate over the dataframe and write your own data render routines, in the manner that you prefer.

pf

Hi @IoannisG ,

As Gurpreet mentionned, you can use Pandas functions to rework a result.
This example will insert an empty column between TR.ISINCode and TR.InstrumentType:

df = rd.get_data('AAPL.OQ', ['TR.ISINCode', 'TR.InstrumentType'])
df.insert(1, "", "")	

But columns are unique so you can't do this insert twice.

Unknown

To specify empty (NULL) fields in a Python request for the Refinitiv Data Library without coding, you can't use empty commas as placeholders directly within the list of fields. Instead, you need to handle the empty fields either by leaving them out of the request altogether or by including placeholder values that you can later identify and handle accordingly.

Here are two approaches to achieve this:

1. Omitting Empty Fields:Simply leave out the empty fields from your list of requested fields. For example:

   pythonCopy codedf = rd.get_data('AAPL.OQ', ['TR.ISINCode', 'TR.InstrumentType'])
   

   This approach ensures that only the specified fields are requested, without any empty fields in between.

2. Using Placeholder Values:If you need to maintain a consistent structure in your data for formatting purposes, you can include placeholder values in your request. For instance, you can use a string like 'NULL' or 'NA' to represent empty fields:

   pythonCopy codedf = rd.get_data('AAPL.OQ', ['TR.ISINCode', 'NULL', 'NULL', 'TR.InstrumentType'])
   

   Later, you can identify and handle these placeholder values as needed in your data processing pipeline.

By adopting one of these approaches, you can effectively specify empty (NULL) fields in your Python request for the Refinitiv Data Library without encountering syntax errors.