Lookup#
- morningstar_data.direct.get_data_point_settings(
- data_point_ids: List[str],
Returns a DataFrame of settings for a given set of data points. This settings DataFrame can then be manipulated to reflect the specific settings to be used for data retrieval.
- Parameters:
data_point_ids (
list
) – A list of unique identifiers for data points. The format is an array of data point id. Example: [“OS01W”, “HP010”]- Returns:
A DataFrame object with data point settings data. The DataFrame columns include:
datapointId
datapointName
type
universe
isTsdp
isFilterable
isEpdp
isCustomCalc
isPortfolioCalc
canBeAddedToDataset
mstarIpType
nonstandardDisplayType
hasOptions
requireValueSearch
displayName
scale
reverseSign
decimalPlaces
currency
preEuroConversion
displayOptions
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
align
width
cellType
sortLocal
displayType
percentileRank
hide
custom
fixFormat
customType
generalFrequency
calcCurType
calcSdType
calcUse5Days
calcS1
calcS2
calcCfgDataSource
calcBestReturnNum
calcWorstReturnNum
calcRollingTimePeriod
calcReinvestDateType
calcReinvestSource
calcAdditionalSource
calcIsApplyIsraelsenModification
calcDaysOfAnnuYear
calcMnav
showType
transType
- Return type:
DataFrame
Examples
Get data point setting for data point id “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