Writing Efficient Code with pandas

Course Description

The ability to efficiently work with big datasets and extract valuable information is an indispensable tool for every aspiring data scientist. When working with a small amount of data, we often don’t realize how slow code execution can be. This course will build on your knowledge of Python and the pandas library and introduce you to efficient built-in pandas functions to perform tasks faster. Pandas’ built-in functions allow you to tackle the simplest tasks, like targeting specific entries and features from the data, to the most complex tasks, like applying functions on groups of entries, much faster than Python's usual methods. By the end of this course, you will be able to apply a function to data based on a feature value, iterate through big datasets rapidly, and manipulate data belonging to different groups efficiently. You will apply these methods on a variety of real-world datasets, such as poker hands or restaurant tips.

In the following tracks

Python Programming

Datasets

PokerPopular Baby NamesRestaurant

Collaborators

Hadrien LacroixHillary Green-Lerman

Prerequisites

Data Manipulation with pandas

Leonidas Souliotis

PhD @ University of Warwick

Leonidas Souliotis is a PhD student at the University of Warwick, UK. His research interests lie in the field of bioinformatics, machine learning, and deep learning. Before that, he completed his MSc in Statistics degree from Imperial College London, UK, and his BSc in Statistics and Insurance Science from the University of Piraeus. He has worked in different areas of applied statistics and machine learning, both inside and outside academia. This includes stock trading, epidemiology and biology.

See More