A developer recreates a real-time data visualization, plotting geotagged tweets about Trump on a 3D globe using d3, socket.io, and the Twitter API.
A summary of a D3.js data visualization workshop for gifted high-school students, covering materials and projects.
A data analysis of a radio station's song rotation patterns using vector math and statistical methods to test anecdotal claims about repetitive playtimes.
A former PhD scientist shares his positive transition to data science freelancing, detailing the freedom and variety of his new career.
A technical article presenting a mathematical function for creating smooth, differentiable pulses, with R code examples.
A tutorial on analyzing Seattle's Pronto CycleShare data using Python, Pandas, and the PyData stack for data science.
Video presentation from JuliaCon 2015 on using Julia for data analytics and visualization, featuring a Citi Bike API analysis and the Vega.jl package.
A summary of the second Nilearn sprint, highlighting new features and improvements for this neuroimaging machine learning library.
A developer revives the Vega.jl package for Julia, updating it for v0.4, adding Jupyter Notebook support, and planning new visualizations.
A tutorial on creating reusable D3.js chart components within Angular directives, demonstrating composition with a line chart and scatter plot.
A tutorial introducing the ggplot2 package for data visualization in R, presented at a user group meeting.
A guide to analyzing Oracle Data Integrator (ODI) runtime performance data using Elasticsearch and Kibana for visualization and trend analysis.
A tutorial on creating maps using R, based on a presentation by Ryan Peek and Michele Tobias at the Davis R Users' Group.
A step-by-step tutorial for creating a basic area chart using the D3.js JavaScript library, focusing on simplicity and core concepts.
A tutorial on creating interactive Small Multiples line charts with D3.js and Angular.js, including brushing for synchronized views.
A Python tutorial showing how to download your Twitter timeline and visualize it as a word cloud using data science libraries.
A Python tutorial showing how to download your Twitter timeline and visualize it as a word cloud using data science libraries.
Part 3 of a series on visualizing data in Kibana after loading it from Hadoop via Elasticsearch, comparing Kibana 3 and 4.
Introduction to using Kibana and Elasticsearch with Hadoop for visualizing and analyzing big data from web logs, tweets, and blog metadata.
A critique of the 'jet' colormap in data visualization, with a Python function to convert colormaps to grayscale for analysis.
