TypeError(f"Bulk reference data not supported, expected singleton values but received {data}")

[gghickman]

Hi! I am struggling with this: df1 + df2 are fine. df3 gives me the bulk reference data not supported, followed by unstructured output. Any suggestion?

import datetime import json import pandas as pd from blp import blp bquery = blp.BlpQuery().start()

df1 = pd.DataFrame(bquery.bdh(['MSFT US Equity'],['PX_LAST','PE_RATIO'],start_date='20210601',end_date='20210622')) print(df1.head(3))

df2 = pd.DataFrame(bquery.bdp(['MSFT US Equity', 'GOOG US Equity'],['PX_OPEN', 'PX_LAST'])) print(df2)

df3 = pd.DataFrame(bquery.bdp(['DBR 5.5 31 Govt'],['DES_CASH_FLOW'])) print(df3)

[matthewgilbert]

It's impossible for me to see what is going on if you don't include your output from print.

[gghickman]

Sorry, I am a bit new to this - here is the output:

D:\Users\Gordon\My Documents\Python>bbg_input2.py date security PX_LAST PE_RATIO 0 2021-06-01 MSFT US Equity 247.40 34.2080 1 2021-06-02 MSFT US Equity 247.30 34.1941 2 2021-06-03 MSFT US Equity 245.71 33.9743 security PX_OPEN PX_LAST 0 MSFT US Equity 266.16 266.69 1 GOOG US Equity 2541.07 2545.64 Traceback (most recent call last): File "D:\Users\Gordon\My Documents\Python\bbg_input2.py", line 13, in df3 = pd.DataFrame(bquery.bdp(['DBR 5.5 31 Govt'],['DES_CASH_FLOW'])) File "C:\Users\gordo\AppData\Local\Programs\Python\Python39\lib\site-packages\blp\blp.py", line 821, in bdp df = self.query(query, self.parser, self.collect_to_bdp) File "C:\Users\gordo\AppData\Local\Programs\Python\Python39\lib\site-packages\blp\blp.py", line 646, in query res = collector(res) File "C:\Users\gordo\AppData\Local\Programs\Python\Python39\lib\site-packages\blp\blp.py", line 835, in collect_to_bdp raise TypeError(f"Bulk reference data not supported, expected singleton values but received {data}") TypeError: Bulk reference data not supported, expected singleton values but received {'DES_CASH_FLOW': [{'Payment Date': Timestamp('2022-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2023-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2024-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2025-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2026-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2027-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2028-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2029-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2030-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2031-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 1000000.0}]}

[matthewgilbert]

I would take a look at this https://stackoverflow.com/help/minimal-reproducible-example and also look at github code formatting https://docs.github.com/en/github/writing-on-github/working-with-advanced-formatting/creating-and-highlighting-code-blocks

[gghickman]

Python Code

import datetime
import json
import pandas as pd
from blp import blp
bquery = blp.BlpQuery().start()
df3 = pd.DataFrame(bquery.bdp(['DBR 5.5 31 Govt'],['DES_CASH_FLOW']))

Output

Traceback (most recent call last):
  File "D:\Users\Gordon\My Documents\Python\bbg_input2.py", line 6, in <module>
    df3 = pd.DataFrame(bquery.bdp(['DBR 5.5 31 Govt'],['DES_CASH_FLOW']))
  File "C:\Users\gordo\AppData\Local\Programs\Python\Python39\lib\site-packages\blp\blp.py", line 821, in bdp
    df = self.query(query, self.parser, self.collect_to_bdp)
  File "C:\Users\gordo\AppData\Local\Programs\Python\Python39\lib\site-packages\blp\blp.py", line 646, in query
    res = collector(res)
  File "C:\Users\gordo\AppData\Local\Programs\Python\Python39\lib\site-packages\blp\blp.py", line 835, in collect_to_bdp
    raise TypeError(f"Bulk reference data not supported, expected singleton values but received {data}")
TypeError: Bulk reference data not supported, expected singleton values but received {'DES_CASH_FLOW': [{'Payment Date': Timestamp('2022-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2023-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2024-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2025-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2026-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2027-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2028-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2029-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2030-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 0.0}, {'Payment Date': Timestamp('2031-01-04 00:00:00'), 'Coupon Amount': 55000.0, 'Principal Amount': 1000000.0}]}

[gghickman]

I hope that is better. Steep learning curve. Help (and patience) appreciated

[matthewgilbert]

As the error indicates, I believe DES_CASH_FLOW is a bulk reference field. Take a look at using bquery.bds. You can see an example in the documentation here https://matthewgilbert.github.io/blp/quickstart.html#Excel-like-functionality

[gghickman]

Thank you. That works. Help appreciated.