Lookup#

morningstar_data.direct.get_data_point_settings(
data_point_ids: List[str],
) → DataFrame#

Returns settings for a given set of data points. This settings DataFrame can be manipulated to reflect specific settings to be used for data retrieval.

Parameters:

data_point_ids (list) – A list of unique identifiers for data points. Example: [“OS01W”, “HP010”]

Returns:

DataFrame: A DataFrame object with data point settings. DataFrame columns include:

  • datapointId

  • datapointName

  • displayName

  • currency

  • preEuroConversion

  • sourceId

  • frequency

  • startDate

  • endDate

  • floatStart

  • floatEnd

  • startDelay

  • endDelay

  • diffStart

  • diffEnd

  • compounding

  • calculationId

  • annualized

  • annualDays

  • benchmark

  • riskfree

  • windowType

  • windowSize

  • stepSize

  • requireContinueData

  • fit

  • scalType

  • scalValue

  • scalPercentValue

  • timehorizon

Examples:

Get data point settings for data point “OS01W”.

import morningstar_data as md

df = md.direct.get_data_point_settings(data_point_ids=["OS01W"])
df
Output:

datapointId

datapointName

…

calcMnav

showType

transType

OS01W

Name

…

None

None

None
Errors:

AccessDeniedError: Raised when the user is not authenticated.

ForbiddenError: Raised when the user does not have permission to access the requested resource.

InternalServerError: Raised when the server encounters an unhandled error.

NetworkExceptionError: Raised when the request fails to reach the server due to a network error.

ResourceNotFoundError: Raised when the requested resource does not exist in Direct.

morningstar_data.lookup.currency_codes(
keyword: str | None = None,
) → DataFrame#

Returns currency codes and currency name that match the given keyword. If no keyword is provided, the function returns all currency codes and currency names.

Parameters:

keyword (Optional[str], optional) – A string used to lookup currency codes. Example: “USD”. Returns matching currency code for the keyword ‘USD’.

Returns:

DataFrame: Returns a DataFrame. The DataFrame columns include:

  • currency_code

  • currency_name

Examples:

Search currency codes based on keyword “Afgh”

import morningstar_data as md
df = md.lookup.currency_codes(
    keyword="Afgh"
)
df
Output:

currency_code

currency_name

AFN

Afghani
Errors:

AccessDeniedError: Raised when the user is not authenticated.

ForbiddenError: Raised when the user does not have permission to access the requested resource.

InternalServerError: Raised when the server encounters an unhandled error.

NetworkExceptionError: Raised when the request fails to reach the server due to a network error.

ResourceNotFoundError: Raised when a currency code matching the given keyword does not exist.

morningstar_data.direct.lookup.investments(
keyword: str = '',
investment: InvestmentIdentifier | None = None,
count: int = 50,
only_surviving: bool = True,
) → DataFrame#

Returns investments that match the given keyword or InvestmentIdentifier object.

Parameters:

  • keyword (str, optional) – Keyword to search for investments.

  • investment (InvestmentIdentifier, optional) – Identifies an investment by its ISIN, CUSIP, ticker, base currency, and/or exchange.

  • count (int, optional) – Maximum number of matching investments to return.

  • only_surviving (bool, optional) – Include only surviving investments.

Note

You must specify one of, but not both of keyword or investment.

Returns:

DataFrame: A DataFrame containing the matching investments with the following columns:

  • Name

  • SecId: Morningstar’s unique identifier for this investment

  • Ticker

  • ISIN

  • CUSIP

  • Base Currency

  • Exchange: The exchange where the investment is listed

  • Country: The country where the investment is based

  • Security Type: Morningstar security type code for this investment

  • Fund Id

  • Performance Id

Examples:

1. Find all global listings for a security by its ticker symbol

import morningstar_data as md
from morningstar_data.direct import InvestmentIdentifier

# Define an investment identifier
investment = InvestmentIdentifier(ticker="AAPL")

# Retrieve matching investments
df = md.direct.lookup.investments(investment=investment)
df

Name

SecId

Ticker

ISIN

CUSIP

Base Currency

Exchange

Country

Security Type

Fund Id

Performance Id

Apple Inc

0P000000GY

AAPL

US0378331005

037833100

USD

EXXNAS

USA

ST

None

0P000000GY

Apple Inc

0P0001367D

AAPL

US0378331005

037833100

USD

EXXSGO

USA

ST

None

0P0001367D

…

…

…

…

…

…

…

…

…

…

…

Apple Inc

0P0001KOM0

AAPL

US0378331005

037833100

USD

EXXLIM

USA

ST

None

0P0001KOM0

Apple Inc

0P0000EEPX

AAPL

US0378331005

037833100

EUR

EXXWBO

USA

ST

None

0P0000EEPX

2. Get listings using ticker symbol and base currency

import morningstar_data as md
from morningstar_data.direct import InvestmentIdentifier

# Define an investment identifier
investment = InvestmentIdentifier(ticker="AAPL", base_currency="Canadian Dollar")

# Retrieve matching investments
df = md.direct.lookup.investments(investment=investment)
df

Name

…

Base Currency

Exchange

Country

…

Performance Id

Apple Inc Canadian Depository Receipt (CAD Hedged)

…

CAD

EXXTSE

USA

…

0P0001N6JJ

Apple Inc

…

CAD

EXXNAS

USA

…

0P000000GY

3. Get listings using ISIN

import morningstar_data as md
from morningstar_data.direct import InvestmentIdentifier

# Define an investment identifier
investment = InvestmentIdentifier(isin="US5949181045")

# Retrieve matching investments
df = md.direct.lookup.investments(investment=investment)
df

Name

SecId

Ticker

ISIN

…

PerformanceId

Microsoft Corp

0P000003MH

MSFT

US5949181045

…

0P000003MH

Microsoft Corp

0P0000BNJR

MSF

US5949181045

…

0P0000BNJR

Microsoft Corp

0P0000EGEI

MSF

US5949181045

…

0P0000EGEI

Microsoft Corp

0P0001AJSV

MSFT

US5949181045

…

0P0001AJSV
morningstar_data.direct.firms(
keyword: str,
universe: str | None = None,
) → DataFrame#

Returns firms that match the given keyword.

Parameters:

  • keyword (str) – Keyword to search for firms.

  • universe (str, optional) – Investment universe code. Example: “FO”. Use get_investment_universes to discover possible values.

Returns:

DataFrame: A DataFrame object with firms. DataFrame columns include:

  • Id

  • Firm Name

  • Universe

Examples:

Get all firms that match the keyword “rock”.

import morningstar_data as md

df = md.direct.lookup.firms("rock")
df
Output:

Id

Firm Name

Universe

F00000Z17E

Amrock Capital B.V.

FO

F00000XC6D

BlackRock

FO

F00000SEJ6

BlackRock (Channel Islands) Limited

FO

…
Errors:

AccessDeniedError: Raised when the user is not authenticated.

ForbiddenError: Raised when the user does not have permission to access the requested resource.

InternalServerError: Raised when the server encounters an unhandled error.

NetworkExceptionError: Raised when the request fails to reach the server due to a network error.

ResourceNotFoundError: Raised when the requested resource does not exist in Direct.

morningstar_data.direct.get_brandings(
keyword: str,
find_by: str,
universe: str | None = None,
) → DataFrame#

Returns brandings for the given universe and keyword.

Parameters:

  • keyword (str) – Keyword to search for brandings.

  • find_by (str) – Search condition to search for brandings. Valid values are name_begin and name_contain.

  • universe (str, optional) –

    Investment universe code. Example: “FO”. Use get_investment_universes to discover possible values.

Returns:

DataFrame: A DataFrame object with brandings. DataFrame columns include:

  • Id

  • Name

Examples:

Search brandings in the open-end fund universe, where branding name begins with the keyword “a”.

import morningstar_data as md

df = direct.lookup.get_brandings("a", "name_begin", "FO")
df
Output:

Id

Name

BN000007Q5

A Plus Finance

BN000007Q6

A&G

BN00000GBI

A1

…
Errors:

BadRequestException: Raised when the parameter find_by is not a valid value.

AccessDeniedError: Raised when the user is not authenticated.

ForbiddenError: Raised when the user does not have permission to access the requested resource.

InternalServerError: Raised when the server encounters an unhandled error.

NetworkExceptionError: Raised when the request fails to reach the server due to a network error.

ResourceNotFoundError: Raised when the requested resource does not exist in Direct.

morningstar_data.direct.lookup.portfolio_managers(
keyword: str = '',
universe: str = 'FO',
) → DataFrame#

Returns portfolio managers for the given universe and keyword.

Parameters:

  • keyword (str) – String to match one or more manager names. If the keyword is empty or not passed to the function, the function will return all managers.

  • universe (str) –

    Investment universe code. Example: “FO”. Use get_investment_universes to discover possible values.

Returns:

DataFrame: A DataFrame object with portfolio managers. DataFrame columns include:

  • Id

  • Manager Name

  • Firm

Examples:

Get portfolio managers that match the keyword “alla”.

import morningstar_data as md

df = md.direct.lookup.portfolio_managers(keyword="alla")
df
Output:

Id

Manager name

Firm

81643

Abdallah Guezour

Schroders

123653

Abdallah Nauphal

TD

213243

Adam Rizkalla

River Canyon

153647

Adrian Allardice

Old Mutual

182699

Adrian van Pallander

Coronation

…
Errors:

AccessDeniedError: Raised when the user is not authenticated.

ForbiddenError: Raised when the user does not have permission to access the requested resource.

InternalServerError: Raised when the server encounters an unhandled error.

NetworkExceptionError: Raised when the request fails to reach the server due to a network error.

ResourceNotFoundError: Raised when the requested resource does not exist in Direct.

morningstar_data.direct.lookup.companies(
keyword: str = '',
universe: str = 'ST',
) → DataFrame#

Returns companies for the given universe and keyword.

Parameters:

  • keyword (str) – String to match one or more company names. If the keyword is empty or not passed to the function, the function will return all companies.

  • universe (str) –

    Investment universe code. Example: “FO”. Use get_investment_universes to discover possible values.

Returns:

DataFrame: A DataFrame object with companies. DataFrame columns include:

  • Id

  • Company name

Examples:

Get companies that match the keyword “Energy”.

import morningstar_data as md

df = md.direct.lookup.companies("Energy")
df
Output:

Id

Company name

0C00008O2A

11 Good Energy Inc

0C000017RQ

2G Energy AG

0C0000516I

3MV Energy Corp

0C00000ZAZ

3Power Energy Group Inc

0C00000QLB

3TEC Energy Corp

…
Errors:

AccessDeniedError: Raised when the user is not authenticated.

ForbiddenError: Raised when the user does not have permission to access the requested resource.

InternalServerError: Raised when the server encounters an unhandled error.

NetworkExceptionError: Raised when the request fails to reach the server due to a network error.

ResourceNotFoundError: Raised when the requested resource does not exist in Direct.

morningstar_data.direct.lookup.get_investment_universes(
include_category_universes: bool = False,
) → DataFrame#

Returns investment universe names and IDs. For example, Bonds, eVestment Hedge Funds, Global Restricted Funds.

Parameters:

include_category_universes (bool, optional) – If True, the function will return all universes, including category universes. Default is False.

Returns:

DataFrame: A DataFrame object with universes. DataFrame columns include:

  • Id

  • Name

Examples:

import morningstar_data as md

df = md.direct.lookup.get_investment_universes()
df
Output:

Id

Name

FH

Hedge Funds

XI

Market_Indexes

…