Python Client for Interfacing with the Federal Reserve Bank of St. Louis' Economic Data API (FRED®)

An R client for the Federal Reserve Economic Data (FRED) API

Pull data from Federal Reserve Economic Data (FRED) directly into Julia

Jupyter notebooks for analysis of US federal debt levels, tax revenues, budget deficit, evolution of yields on treasury borrowings, treasury yield curves and inflation expectations, unemployment and participation rates, quantitative easing, industrial production, personal consumption and savings. All analysis is based on data provided by FRED.

Download FRED data in Julia.

A fully-featured FRED Command Line Interface & Python API wrapper.

Python code for pricing European and American options with examples for individual stock, index, and FX options denominated in USD and Euro. Jupyter notebooks for pricing options using free publicly available datasets.

Testing for data ingestion

Custom Function (Google Sheets) to Import FRED® Economical Data

DEM assignment.

CLI tool to interface with the FRED (Federal Reserve Economic Data) API.

🎉 How to crawl the FRED big data in a rapid and methodical way

The project aims to analyze and visualize economic indicators, including the S&P 500 index and unemployment rates across U.S. states, using data retrieved from the FRED API.

Machine learning driven algorithmic trading ideas through Tradier API

Similar to https://github.com/kylebinder-public/daily_market_update: here are scripts (.py, .bat) for automated sending of weekly emails of economic statistics that interest me. ETL mostly from https://fred.stlouisfed.org/

Financial Data Analysis with FRED API - USA Federal Reserve Economic Data

We created an interactive web application in Python for determing the best states to live in based on user preferences. We sourced data from the FRED Economic Database with custom API wrappers and integrated it into a Python Dash Application framework. Users can filter states, data catageories and even apply weights to parameters for use in the …

This project utilizes the Federal Reserve Economic Data (FRED) API and Python's Pandas library to gather, clean, and analyze economic data. The project walks through the process of pulling down data for various economic indicators, cleaning and joining the data, and using the FRED API to obtain up-to-date data.

This project shows the data analysis of economic data using Fred API (Federal Reserve Economic Data) by cleaning the data, fetching data from the API, exploring and analyzing.