python-dataviz-guide
Publication-quality data visualization with matplotlib, seaborn, and plotly
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill python-dataviz-guide --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Python Data Visualization Guide ## Overview Data visualization is how researchers communicate quantitative findings. A well-designed figure can convey complex relationships instantly, while a poor one buries the signal in clutter. Python's visualization ecosystem -- anchored by matplotlib, seaborn, and plotly -- provides everything needed to produce publication-quality figures for journals, conf
What does the python-dataviz-guide skill do?
Publication-quality data visualization with matplotlib, seaborn, and plotly
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill python-dataviz-guide --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.