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webkid is a Berlin based data visualization agency specialized in data driven applications and interactive maps

The case for less rigor and more nuance

Pesticides, nitrates, substances chimiques, hydrocarbures, médicaments… « Le Monde » a réalisé une cartographie inédite de l’état des eaux de notre sous-sol.

Read writing from Piotr Migdał on Medium. PhD in quantum physics, deep learning & data viz specialist. Founder at Quantum Flytrap. https://p.migdal.pl/ / https://quantumflytrap.com/.

An interactive exploration of how long things take.

Community website for Apache Superset™, a data visualization and data exploration platform

Why my favourite API is a zipfile on the European Central Bank's website

Are 25 year olds really more random than 60 year olds?

A visual essay about the famous figures who represent today’s currencies around the world

Dimension reduction (DR) techniques such as t-SNE, UMAP, and TriMAP have demonstrated impressive visualization performance on many real world datasets. One tension that has always faced these methods is the trade-off between preservation of global structure and preservation of local structure: these methods can either handle one or the other, but not both. In this work, our main goal is to understand what aspects of DR methods are important for preserving both local and global structure: it is difficult to design a better method without a true understanding of the choices we make in our algorithms and their empirical impact on the lower-dimensional embeddings they produce. Towards the goal of local structure preservation, we provide several useful design principles for DR loss functions based on our new understanding of the mechanisms behind successful DR methods. Towards the goal of global structure preservation, our analysis illuminates that the choice of which components to preserve is important. We leverage these insights to design a new algorithm for DR, called Pairwise Controlled Manifold Approximation Projection (PaCMAP), which preserves both local and global structure. Our work provides several unexpected insights into what design choices both to make and avoid when constructing DR algorithms.

This is the first million integers, represented as binary vectors indicating their prime factors, and laid out using the UMAP dimensionality reduction algorithm by Leland McInnes. Each integer is represented in a high-dimensional space, and gets squished down to 2D so that numbers with similar prime factorisations are closer together than those with dissimilar factorisations.

Force-directed algorithms are among the most flexible methods for calculating layouts of simple undirected graphs. Also known as spring embedders, such algorithms calculate the layout of a graph using only information contained within the structure of the graph itself, rather than relying on domain-specific knowledge. Graphs drawn with these algorithms tend to be aesthetically pleasing, exhibit symmetries, and tend to produce crossing-free layouts for planar graphs. In this survey we consider several classical algorithms, starting from Tutte's 1963 barycentric method, and including recent scalable multiscale methods for large and dynamic graphs.