Custom Database#

morningstar_data.direct.my_database.save_historical_values( values: DataFrame, key_column: str = 'SecId', date_column: str = 'Date', blank: Blank | str = Blank.warning, ) → Dict[str, bool | str]#

Saves historical time series values for data points in the user’s or firm’s database in Morningstar Direct.

Parameters:

values (DataFrame) –

A DataFrame object with the time series values to be saved in the user’s or firm’s database. The DataFrame columns should include:

SecId - Column containing investment ID values. If a column named SecId is not present, the column name specified in the key_column argument will be used.
DataPointName - Data point name which will be updated. Multiple data points can be updated in one request.
Date - Column containing date values. If a column named Date is not present, the column name specified in the date_column argument will be used.

For example:

====================  ========  ===============  ===============  ===============
SecId                   Date    DataPointName1   DataPointName2   DataPointName3
====================  ========  ===============  ===============  ===============
<InvestmentId>         <date>       <value>          <value>          <value>
<InvestmentId>         <date>       <value>          <value>          <value>
====================  ========  ===============  ===============  ===============

key_column (str) – Name of the column containing investment ID values. If not specified, the column SecId will be used.
date_column (str) – Name of the column containing date values. If not specified, the column Date will be used.
blank (md.direct.data_type.Blank) –
Argument specifying how blank values in the DataFrame should be handled. Valid enum values for this argument are:
- warning - Raises an error if the DataFrame contains at least one null or empty (str) value.
- ignore - Saves all DataFrame values except for null or empty (str) values.
- update - Replaces/updates all existing values with the provided values. Deletes any value that is sent as null, None or empty (str) values.

Returns:

DataFrame:

Examples:

import morningstar_data as md
from pandas import DataFrame

df = DataFrame({"SecId": ["FOUSA00C3M", "F000010NJ5"],
                "Date": ["2022-02-10","2022-04-2"],
                "DataPointNameText": ["2","9"],
                "DataPointNameNumber": [12.2178, 78514]})

md.direct.my_database.save_historical_values(values=df, key_column="SecId", blank=md.direct.data_type.Blank.warning)

import morningstar_data as md
from pandas import DataFrame

df = DataFrame({"SecId": ["FOUSA00C3M", "F000010NJ5"],
                "Date": ["2022-02-10","2022-04-2"],
                "DataPointNameText": ["2","9"],
                "DataPointNameNumber": [12.2178, 78514]})

md.direct.firm_database.save_historical_values(values=df, key_column="SecId", blank=md.direct.data_type.Blank.warning)

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.my_database.save_values( values: DataFrame, key_column: str = 'SecId', blank: Blank | str = Blank.warning, ) → Dict[str, bool | str]#

Saves values for data points in the user’s or firm’s database.