PyCon UK 2022

Introduction to Data Analysis Using Pandas
2022-09-16 , Room A

Data often doesn’t come in the best format for analysis, and understanding it enough to extract insights requires both time and the skills to filter, aggregate, reshape, and visualize it. This session will equip you with the knowledge you need to effectively use pandas to make this process easier.


This tutorial is for anyone with basic knowledge of Python and an interest in learning how to analyze data in Python. We will be working with Jupyter Notebooks, so attendees should familiarize themselves with the interface (i.e., know how to run/edit a cell) beforehand.

Section 1: Getting Started With Pandas

We will begin by introducing the Series, DataFrame, and Index classes, which are the basic building blocks of the pandas library, and showing how to work with them. By the end of this section, you will be able to create DataFrames and perform operations on them to inspect and filter the data.

Section 2: Data Wrangling

To prepare our data for analysis, we need to perform data wrangling. In this section, we will learn how to clean and reformat data (e.g. renaming columns, fixing data type mismatches), restructure/reshape it, and enrich it (e.g. discretizing columns, calculating aggregations, combining data sources).

We will take breaks for exercises throughout and all solutions, slides, and notebooks will be provided.

Environment Setup

Follow the setup instructions here to get your environment up and running before the session.


Is your proposal suitable for beginners?: yes

Stefanie Molin is a software engineer and data scientist at Bloomberg in New York City, where she tackles tough problems in information security, particularly those revolving around data wrangling/visualization, building tools for gathering data, and knowledge sharing. She is also the author of "Hands-On Data Analysis with Pandas," which is currently in its second edition. She holds a bachelor’s of science degree in operations research from Columbia University's Fu Foundation School of Engineering and Applied Science. She is currently pursuing a master’s degree in computer science, with a specialization in machine learning, from Georgia Tech.