Third-party data APIs

The SigTech platform now supports a number of third-party data APIs, which you can install and use in your research environment.

In most cases, it should be quick and straightforward to install them: either by running the relevant line of code in a notebook or the terminal in the SigTech platform. Please refer to the relevant API documentation for more information on authentication and libraries.

Note: If you want to use a third-party API that is not listed here, it’s probably still restricted on our platform due to security reasons. Contact support@sigtech.com or your technical account manager if there’s a particular API you require access to.

FRED API

fredapi is a Python API created by the Economic Research Division of the Federal Reserve Bank of St. Louis. It lets you write programs that retrieve Federal Reserve Economic Data (FRED) and Archival Federal Reserve Economic Data (ALFRED) from the St. Louis Fed’s servers. It also provides methods for parsing and analyzing point-in-time data.

FRED contains regularly updated US macro and regional economic time series data, at daily, weekly, monthly, quarterly, and annual frequencies.

FRED API uses the pandas library, meaning data is returned in a pandas Series or DataFrame.

Installation

To install the FRED API, run the following code block in a notebook in the SigTech research environment:

%pip install fredapi

Alternatively, you can open a terminal in the SigTech research environment and run the following command:

pip install fredapi

You can follow the above example to install any other APIs via the terminal.

Pandas Datareader

A spin-off library from the main pandas library, pandas_datareader provides up-to-date remote data access for pandas. This API contains functions that extract data from various Internet sources, returning a pandas DataFrame.

Read the pandas documentation for a full list of supported sources.

Installation

To install the pandas datareader API, run the following code block in a notebook in the SigTech research environment:

%pip install pandas-datareader

Macrobond Data API

macrobond_data_api (or mb_api) is a Python API that lets you retrieve time series data, which is returned as a pandas Series.

It sources this information from either the Macrobond Web REST API or the Macrobond Client data API, and provides both shared and unique functions for these underlying APIs.

The Macrobond Data API is a paid data provider, and can only be used with a Data+ license.

Installation

To install the Macrobond Data API, run the following code block in a notebook in the SigTech research environment:

%python -m pip install macrobond-data-api

DBnomics API

The dbnomics API provides access to its database of publicly available macroeconomic data. All data is time series data, which you can download as a pandas DataFrame You can download any time series data as a pandas DataFrame.

DBNomics data is aggregated from a number of worldwide providers, including researchers, private companies, and national and international statistical institutions. See the DBnomics documentation for a full list.

Installation

To install the DBNomics API, run the following code block in a notebook in the SigTech research environment:

%pip install dbnomics

pandaSDMX API

The pandaSDMX API is a Python library that implements SDMX 2.1. Standing for Statistical Data and Metadata eXchange, SDMX is an ISO standard designed to facilitate the improved exchange of statistical data and metadata between central banks, national statistical agencies, and international organizations.

You can use pandaSDMX to access data from the World Bank, BIS, OECD, United Nations, and other data providers. Data and metadata are converted into pandas objects, which can then be used in analysis and plotting.

Installation

To install the pandasSDMX API, run the following code block in a notebook in the SigTech research environment:

%pip install pandasdmx