A guide to the Lomb-Scargle periodogram, explaining its use, common misconceptions, and practical considerations for analyzing astronomical data.
Explores implementing group-by operations from scratch in Python, comparing performance of Pandas, NumPy, and SciPy for data aggregation.
A technical analysis using sentiment analysis on Warren Buffett's shareholder letters from 1977-2016 to identify trends in tone and market influence.
A quick PowerShell script to count the frequency of first letters in a list of surnames from a text file.
A video series on transitioning from interactive Jupyter data exploration to reproducible, packaged, and tested code for data analysis.
A technical guide on analyzing personal Google Location History data using Python, Pandas, and visualization libraries to map and gain insights from location data.
Analyzing the relationship between age and desired job roles among new coders using the 2016 Kaggle survey data.
A technical guide on using Google BigQuery to analyze GitHub pull request data, including SQL queries for repository statistics.
The author reflects on R's rise in programming language rankings and its unexpected adoption across diverse fields over 20 years.
A curated list of insightful programming blogs covering topics like JVM internals, performance, ML, engineering culture, and computer architecture.
Release notes for RSiteCatalyst 1.4.8, featuring segment stacking, date range parameters, and bug fixes for the Adobe Analytics R package.
A technical guide demonstrating how to call the RSiteCatalyst R package from Python using the rpy2 library for data analysis.
Release notes for RSiteCatalyst versions 1.4.6 and 1.4.7, detailing bug fixes and new features for the Adobe Analytics R package.
A data analysis of a radio station's song rotation patterns using vector math and statistical methods to test anecdotal claims about repetitive playtimes.
Analyzing a classic probability problem involving dice rolls, its historical context with Newton and Pepys, and the mathematical intuition behind it.
Analyzing patterns in Bob Ross Twitch chat data using n-gram frequency, percentiles, and spikiness scores to identify event-driven viewer reactions.
A tutorial on analyzing Seattle's Pronto CycleShare data using Python, Pandas, and the PyData stack for data science.
A data-driven critique of a popular Kenyan tech blog, analyzing its content focus using R programming and text mining techniques.
DataKind Singapore's Project Accelerator connects volunteer data scientists with nonprofits to solve data challenges, like analyzing water consumption data.
A scientist explains why Python is their preferred language for machine learning and data analysis, arguing for productivity over language wars.
