Unlock the full potential of AI with Building LLMs for Production—our 470+ page guide to mastering LLMs with practical projects and expert insights!

Publication

Introduction to the Pandas Library
Latest   Machine Learning

Introduction to the Pandas Library

Last Updated on July 24, 2023 by Editorial Team

Author(s): Saiteja Kura

Originally published on Towards AI.

Introduction to the Pandas Library
Source — Nimble Coding

Before beginning, I would suggest you read my previous article on NumPy here. Although NumPy’s arrays are better than Python’s data structures several limitations hinder its usage.1. NumPy’s high dimensional arrays support only single data type per array which makes it difficult to deal with data having both numbers and strings.In general real-time data is a combination of one or more data types.2. Numpy has hardware-level methods but there are no pre-built methods for analysis patterns used regularly.

The Pandas library is also known as the “Python Data Analysis Library” solves the above problems. Pandas is a python… Read the full blog for free on Medium.

Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.

Published via Towards AI

Feedback ↓