Nimble - Python data science package

Nimble provides a unified framework for data science, data analysis, and machine learning in Python that can be used as a more elegant alternative to the standard stack (numpy, pandas, scikit-learn/sklearn, scipy, etc.). Nimble can also be used alongside these standard tools to make it faster and easier to make predictions and manipulate, analyze, process and visualize data.

Getting Started

You can check the Installation page for detailed options or just started with this:

pip install nimble\[quickstart\]

Once Nimble is installed, you can load data in a script by calling nimble.data with a URL or local path.

import nimble
urlOrPath = "https://storage.googleapis.com/nimble/Metro_Interstate_Traffic_Volume.csv"
loaded = nimble.data(urlOrPath)

From there, you can explore the examples below or check out the the cheatsheet and API Docs to see what’s possible!

Examples

• Cleaning Data
• Supervised Learning
• Exploring Data
• Unsupervised Learning
• Neural Networks
• Merging and Tidying Data
• Additional Functionality

Resources

• Installation
• API Documentation
• Cheatsheet
• Example Datasets

Contact

Feel free to get in touch with us at:

or through the Nimble Github page.