Peer Group#
- morningstar_data.direct.get_peer_group_breakpoints(
- investments: List[str] | str,
- data_points: List[Dict[str, Any]] | DataFrame,
- order: Order = Order.ASC,
- percentiles: List[int] | None = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100],
- methodology: PeerGroupMethodology | None = None,
Returns peer group breakpoints for the specified list of investments and data points.
- Parameters:
investments (
Union
, required) –Defines the investments to fetch. Input can be:
Investment IDs (
list
, optional): Investment identifiers, in the format of SecId;Universe or just SecId. E.g., [“F00000YOOK;FO”,”FOUSA00CFV;FO”] or [“F00000YOOK”,”FOUSA00CFV”]. Use the investments function to discover identifiers.Investment List ID (
str
, optional): Saved investment list in Morningstar Direct. Use the get_investment_lists function to discover saved lists.Search Criteria ID (
str
, optional): Saved search criteria in Morningstar Direct. Use the get_search_criteria function to discover saved search criteria.Search Criteria Condition (
dict
, optional): Search criteria definition. See details in the Reference section of get_investment_data or use the get_search_criteria_conditions function to discover the definition of a saved search criteria.
data_points (
Union
, optional) –Defines the data points to fetch. If not provided and investments are specified with a list ID or search criteria ID, the corresponding bound dataset will be used.
Data Point IDs (
List[Dict]
, optional): A list of dictionaries, each defining a data point and its (optional) associated settings. The optional alias attribute can be added to each data point and will be used in the response, e.g., [{“datapointId”: “41”, “alias”: “Z1”}. Use get_data_set_details to discover data point identifiers from a saved data set.Data Point Settings (
DataFrame
, optional): A DataFrame of data point identifiers and their associated settings. Use the get_data_set_details function to discover data point settings from a saved data set.
order (
md.direct.data_type.Order
, optional) – Breakpoint order, can be set tomd.direct.data_type.Order.DESC
(descending) ormd.direct.dats_type.Order.ASC
(ascending, default).percentiles (
list
, optional) – Percentiles default to a list [1,2,3,…,100] if not provided, values should be within 1-100 range.methodology (
md.direct.data_type.PeerGroupMethodology
, optional) – Breakpoint calculation methodology, can be set tomd.direct.data_type.PeerGroupMethodology.MORNINGSTAR
ormd.direct.data_type.PeerGroupMethodology.SIMPLE
. Defaults to the global setting “Custom Peer Group Ranking” in Morningstar Direct if not provided.
- Returns:
DataFrame: A DataFrame object with peer group breakpoint data. The columns include the alias that the user input in the data_points parameter.
- Examples:
Get peer group breakpoint data for the standard deviation data point.
import morningstar_data as md df = md.direct.get_peer_group_breakpoints( investments='740284aa-fcd3-43f6-99d1-8f3d4a179fcc', data_points=[ {"datapointId": "41", "alias": "Z1"}, {"datapointId": "41", "alias": "Z2", "startDate": "2021-07-01", "endDate": "2021-12-31", "windowType": "2", "windowSize": "3", "stepSize": "2"} ], order=md.direct.data_type.Order.ASC, percentiles=[25, 50, 75, 100] ) df
- Output:
Alias
StartDate
EndDate
25
50
75
100
Z1
2019-04-01
2022-03-31
17.301437
12.720889
7.055372
-3.460187
Z2
2021-07-01
2021-09-30
1.827371
-0.804269
-4.899745
-52.143678
Z2
2021-09-01
2021-11-30
-0.030321
-4.336051
-10.618009
-40.980480
- Errors:
AccessDeniedError: Raised when the user lacks permission or is not authorized to access the resource.
BadRequestException: Raised due to invalid/incorrect request, malformed request syntax, or deceptive request routing.
NetworkExceptionError: Raised when there is an issue with the internet connection or if the request is made from an unsecure network.
ResourceNotFoundError: Raised when the requested resource does not exist in Direct.