Every leaf is a headline number from Wes McKinney’s public GitHub. The canopy fills out as the work grows - sway and all.
Data from GitHub API · refreshed in real time
Based on public GitHub activity · how this is calculated
Python is the largest language share across analyzed repositories, at 48%.
High confidence
Public visibility is concentrated: the top 3 analyzed repositories account for 97% of total stars, led by pydata-book.
Medium confidence
Public GitHub activity is implementation-heavy: commits account for 67% of tracked contribution activity.
Medium confidence
Most analyzed repositories (21 of 32) show no public activity in over a year.
Medium confidence
Signals from analyzed public data
Strong
Needs work
Needs work
Needs work
Developing
A skim of public evidence, not a hiring judgement
Largest language shares across analyzed repositories
Analyzed repositories rated established or maintained
Public pull requests and code reviews in the trailing year
Summed across analyzed repositories
Calendar months with at least one tracked contribution
Strongest signals
Wes McKinney is a developer on GitHub whose public work is written mostly in Python, which accounts for roughly 48% of their committed code, alongside C++ and HTML. Their account holds 32 public repositories, collecting 28,769 stars in total, led by pydata-book at 24,950. In the trailing year the account logged 7,693 contributions, including a longest run of 125 consecutive active days. Wes McKinney has been on GitHub since 2010 and is followed by 16,934 developers.
This overview is generated from Wes McKinney’s public GitHub activity at the time of the last refresh. Figures cover public repositories and the trailing twelve months of contributions.
Add topics to pydata-book
Low impactpydata-book has no topic tags, making its technology harder to discover.
pydata-book →Add topics to feather
Low impactfeather has no topic tags, making its technology harder to discover.
feather →Add topics to moneyflow
Low impactmoneyflow has no topic tags, making its technology harder to discover.
moneyflow →Add topics to vbench
Low impactvbench has no topic tags, making its technology harder to discover.
vbench →Add topics to vldb-2019-apache-arrow-workshop
Low impactvldb-2019-apache-arrow-workshop has no topic tags, making its technology harder to discover.
vldb-2019-apache-arrow-workshop →How these are calculated: see the methodology page .
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Feather: fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow
Moneyflow: Personal Finance Data Interface for Power Users (supporting backends like Monarch Money, YNAB)
vbench: A tool for benchmarking your code through time, for showing performance improvement or regressions
Design documents and code for the pandas 2.0 effort.
Materials for Apache Arrow workshop at VLDB 2019
Bayesian State Space and Dynamic Models
Browse, search, and revisit your AI coding sessions.
Materials for PyData at Strata/Hadoop World San Jose 2015
Archive a lifetime of email and chat. Offline search, analytics, and AI query over your full message history. Powered by SQLite and DuckDB
Continuous background code review database for agents, work faster and smarter with accountability for every line of generated code.
Local-first issue tracking for AI-assisted software work, with an agent-friendly CLI and human-facing TUI
Local-first session search, analytics, insights, and token use statistics for coding agents, supporting Claude Code, Codex, and more than 20 other agents.
Apache Arrow is the universal columnar format and multi-language toolbox for fast data interchange and in-memory analytics
Local-first maintainer console with built-in agent workspaces: triage PRs, issues, and CI across GitHub, GitLab, Forgejo, and Gitea, then turn any item into a worktree session running your coding agent. One binary, no inbox.
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
Feather: fast, interoperable binary data frame storage for Python, R, and more powered by Apache Arrow
Design documents and code for the pandas 2.0 effort.
Moneyflow: Personal Finance Data Interface for Power Users (supporting backends like Monarch Money, YNAB)
vbench: A tool for benchmarking your code through time, for showing performance improvement or regressions
Browse, search, and revisit your AI coding sessions.
Public visibility is concentrated in a small number of projects - these are the strongest candidates to feature on a resume.
Leading repository: pydata-book (24,950 stars, 28,769 total across analyzed repositories)
Derived from repository languages and topics - horizontal bars, never a pie.
README, contributing-guide and GitHub Actions badges below are detected by exact filename on each repository’s default branch - they report presence, not quality.
Seus projetos e habilidades já estão preenchidos a partir do GitHub. Adicione o que o GitHub não publica - dados de contato, experiência e educação - e exporte um PDF de uma página compatível com ATS.
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| Name | Language | Stars | Forks | Size | Updated |
|---|
No repositories match those filters.
Best coding day: Mon
Created the @wesm account.
Published statlib, the oldest repository still on the account.
statlib is the earliest-created repository to have earned stars.
strata-sj-2015 was the 10th public repository created.
6,868 contributions recorded in 2026, more than any other year on record.
conbench-tmp is the most recently created repository.
Your GitHub career, year by year.
→Shifted from Python to Jupyter Notebook.
Shifted from Jupyter Notebook to Python.
Went deeper into Python.
Shifted from Python to JavaScript.
Shifted from JavaScript to C++.
Went deeper into C++.
Shifted from C++ to Jupyter Notebook.
Shipped 2 repositories.
Started with Python.
Went deeper into Python.
Went deeper into Python.
Built from wesm’s public, non-fork repositories. Star totals reflect current counts, not historical snapshots.
7 / 9 unlocked
The primary languages of repositories created each year.
Repositories created per year, and the running total.
Built automatically from repository languages and topics.
