Data Science

Speeding Up Your Code with Parallel Computing in Python

macro photography of black circuit board
Parallel computing is essential for handling large datasets efficiently. In this post, we explore Python's threading, multiprocessing, and joblib libraries to speed up code execution. Learn the differences between threading and multiprocessing, and understand how to use joblib for optimized parallel processing, especially with NumPy arrays.

Topographic map clipped by coastlines in Python

Learn how to create visually compelling relief maps in Python by clipping topographic data to specific geographic boundaries, such as coastlines. This tutorial walks you through the process of using matplotlib and Basemap to focus your visualizations on land features within the Taiwan coastline, or alternatively, highlight bathymetric features by masking the land.

Creating Dynamic Visualizations in Python Using Bokeh: A Step-by-Step Tutorial

Bokeh is a robust Python library for creating interactive, visually appealing web visualizations without requiring JavaScript. It excels in interactivity, integration with web frameworks, customization, and performance. This tutorial covers installation, basic and advanced plotting, styling, data management, and layout configurations, providing a comprehensive guide for data scientists and developers.