M-Lab Knowledge Base Research & Analysis
6 articles
A curated starting path for academic researchers and data scientists using M-Lab data — covering data access, key datasets, measurement methodology, and common research patterns.
Methods, tools, and best practices for using M-Lab's open datasets in academic research, policy analysis, and community broadband advocacy.
An introduction to what M-Lab is, what it measures, and how its open data can help you understand internet performance.
What the Monthly Stats dataset is, how it's derived from NDT measurements, what the parquet files contain, and how to access them without BigQuery.
How to interpret percentile columns in M-Lab Monthly Stats data, including the counterintuitive polarity of latency and loss, and what p50 vs p95 tells you.
A practical guide to loading, filtering, and visualising M-Lab Monthly Stats parquet files in Python using pandas, without needing BigQuery or a Google Cloud account.