The Applied Data Science Workshop - Second Edition

2. Data Exploration with Jupyter

Overview

In this chapter, we'll finally get our hands on some data and work through an exploratory analysis, where we'll compute some informative metrics and visualizations. By the end of this chapter, you will be able to use the pandas Python library to load tabular data and run calculations on it, and the seaborn Python library to create visualizations.

Introduction

So far, we have taken a glance at the data science ecosystem and jumped into learning about Jupyter, the tool that we'll be using throughout this book for our coding exercises and activities. Now, we'll shift our focus away from learning about Jupyter and start actually using it for analysis.

Data visualization and exploration are important ...