Module Information

Description: Fred Data Connector of QuantJourney Framework

This utility class facilitates the fetching of financial and economic data from the Federal Reserve Economic Data (FRED) API for use in quantitative analysis. Leveraging FRED's extensive repository, it supports the retrieval of various datasets including macroeconomic indicators, interest rates, employment data, and more, making it a valuable tool for data-driven decision-making in finance and economics.

The FRED Data Connector is designed with async capabilities to enhance performance when dealing with large volumes of data or fetching data from multiple series concurrently. It abstracts the complexity of asynchronous programming and the FRED API, providing a straightforward interface for data retrieval.

Features: - Support for fetching a wide range of financial and economic datasets from FRED. - Asynchronous data retrieval for improved performance and efficiency. - Easy integration with financial analysis and quantitative research projects. - Flexible date range specification for historical data analysis. - Utilizes the official FRED API, requiring an API key for access.

Author: jpolec

Date: 18-03-2024

Class: FredConnector()

Method: search

def search(
            search_string: str
        ) -> List[Dict]

Search the FRED API for a given search string.

Examples:

search_results = dc.fred.search("GDP")
search_results = dc.fred.search("unemployment rate")

Parameters:

Name	Type	Description
search_string	str	The string to search the FRED API for.

Returns:

Type	Description
List[Dict]	A list of dictionaries containing the search results.

Method: get_series

def get_series(
            search_id: str,
            observation_start: Optional[str] = None,
            observation_end: Optional[str] = None
        ) -> pd.DataFrame

Get series data between a start and end date.

Examples:

series_data = dc.fred.get_series("GDP", observation_start="2020-01-01", observation_end="2020-12-31")
series_data = dc.fred.get_series("unemployment rate", observation_start="2020-01-01", observation_end="2020-12-31")

Parameters:

Name	Type	Description
search_id	str	The ID of the series to fetch.
observation_start	Optional[str]	The start date for the data in 'YYYY-MM-DD' format. Defaults to None.
observation_end	Optional[str]	The end date for the data in 'YYYY-MM-DD' format. Defaults to None.

Returns:

Type	Description
pd.DataFrame	The series data.

Method: get_series_as_of_date

def get_series_as_of_date(
            search_id: str,
            date: str
        ) -> pd.DataFrame

Get series data for a specific date.

Examples:

series_data = dc.fred.get_series_as_of_date("GDP", "2023-04-01")

Parameters:

Name	Type	Description
search_id	str	The ID of the series to fetch.
date	str	The date for the data in 'YYYY-MM-DD' format.

Returns:

Type	Description
pd.DataFrame	The series data for the specified date.

Method: get_series_info

def get_series_info(
            search_id: str
        ) -> dict

Get information about a series.

Examples:

series_info = dc.fred.get_series_info("GDP")

Parameters:

Name	Type	Description
search_id	str	The ID of the series to fetch.

Returns:

Type	Description
dict	Information about the series.

Method: get_release_series

def get_release_series(
            release_id: str,
            limit: int = 1000,
            order_by: str = 'popularity'
        ) -> pd.DataFrame

Get series data for a specific release.

Examples:

release_series = dc.fred.get_release_series("BACDINA066MNFRBNY", limit=10, order_by="popularity")

Parameters:

Name	Type	Description
release_id	str	The ID of the release to fetch.
limit	int	The maximum number of series to return. Defaults to 1000.
order_by	str	The order of the series. Can be "popularity" or "series_id". Defaults to "popularity".

Returns:

Type	Description
pd.DataFrame	The series data for the specified release.

Method: get_series_first_release

def get_series_first_release(
            search_id: str
        ) -> pd.DataFrame

Get the first release of a series.

Examples:

first_release = dc.fred.get_series_first_release("GDP")

Parameters:

Name	Type	Description
search_id	str	The ID of the series to fetch.

Returns:

Type	Description
pd.DataFrame	The first release of the series.

Method: get_series_latest_release

def get_series_latest_release(
            search_id: str
        ) -> pd.DataFrame

Get the latest release of a series.

Examples:

latest_release = dc.fred.get_series_latest_release("GDP")

Parameters:

Name	Type	Description
search_id	str	The ID of the series to fetch.

Returns:

Type	Description
pd.DataFrame	The latest release of the series.

Method: get_series_all_releases

def get_series_all_releases(
            search_id: str
        ) -> pd.DataFrame

Get all releases of a series.

Examples:

all_releases = dc.fred.get_series_all_releases("GDP")

Parameters:

Name	Type	Description
search_id	str	The ID of the series to fetch.

Returns:

Type	Description
pd.DataFrame	All releases of the series.