https://github.com/jmetrics86/lazy_fred
A wrapper for the fredapi package to pull in the most popular timeseries across daily, weekly and monthly granularities. Great for storing economic data for modeling and analysis!
https://github.com/jmetrics86/lazy_fred
economic economic-data economics-models fredapi macroeconomics us
Last synced: 3 months ago
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A wrapper for the fredapi package to pull in the most popular timeseries across daily, weekly and monthly granularities. Great for storing economic data for modeling and analysis!
- Host: GitHub
- URL: https://github.com/jmetrics86/lazy_fred
- Owner: Jmetrics86
- License: mit
- Created: 2024-05-28T19:10:54.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2024-06-25T19:55:11.000Z (almost 2 years ago)
- Last Synced: 2025-12-17T04:11:04.395Z (6 months ago)
- Topics: economic, economic-data, economics-models, fredapi, macroeconomics, us
- Language: Python
- Homepage: https://pypi.org/project/lazy_fred/
- Size: 4.94 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
 
# lazy_fred: Effortless FRED Data Collection
lazy_fred is a Python library designed to simplify the process of collecting economic data from the Federal Reserve Economic Data (FRED) API. It automates searching for relevant series, filtering by frequency and popularity, and exporting the data into convenient CSV files.
## Features
- **Automated Search:** Searches FRED across various economic categories.
- **Filtered Selection:** Selects series based on popularity and frequency (daily, weekly, monthly).
- **Error Handling:** Includes retry mechanisms and logging for robust data collection.
- **CSV Export:** Saves the collected data in separate CSV files for easy analysis.
## Installation
1. **Clone the Repository:**
```bash
git clone https://github.com/your-username/lazy_fred.git
```
2. **Install Dependencies:**
```bash
pip install -r requirements.txt
```
3. **Obtain a FRED API Key:**
- Visit the [FRED website](https://fred.stlouisfed.org/docs/api/fred/) and get your free API key.
## Usage
1. **Configure Search Categories:**
- Modify the `search_categories` list in the script to include the categories of interest. The defualt list of 30 items have been chosen from the structure of the FRED website navigation and some personal decisions.
2. **Run the Script:**
```bash
python lazy_fred.py
```
3. **Output:**
- The script will create three CSV files in your project directory:
- `filtered_series.csv`: Contains the search results from FRED cleaned to popularity over 50 and observation starts after 1900.
- `daily_data.csv`: Contains daily time series data.
- `monthly_data.csv`: Contains monthly time series data.
- `weekly_data.csv`: Contains weekly time series data.
## Code Structure
- **`AccessFred` Class:**
- Handles API key retrieval and validation.
- **`collect_categories` Class:**
- Executes searches across categories and consolidates results.
- **`daily_export`, `monthly_export`, and `weekly_export` Classes:**
- Filter series by frequency and popularity.
- Collect and export time series data.
## Packaging: pypi.org/project/lazy_fred/
The code has been packaged and can also be pip installed as
```bash
pip install lazy_fred
```
Make sure you are on the latest version (https://pypi.org/project/lazy_fred/).
## Package Instructions
The code is simple, create and instance and add your API key!
```bash
import lazy_fred as lf
lf.run_fred_data_collection("insert_api_key_here")
```
## Contributions
Contributions are welcome! Feel free to open issues or submit pull requests.
## License
This project is licensed under the MIT License.
## Disclaimer
This library is not affiliated with or endorsed by the Federal Reserve Bank of St. Louis or the FRED project.
## Acknowledgments
- This project utilizes the `fredapi` and `fred` libraries for interacting with the FRED API.
## Contact
For any questions or feedback, please open an issue in the repository.