data-journalism
Data journalism workflows for analysis, visualization, and storytelling. Use when analyzing datasets, creating charts and maps, cleaning messy data, calculating statistics or building data-driven stories. Essential for reporters, newsrooms and researchers working with quantitative information.
npx skills add majiayu000/claude-skill-registry --skill data-journalism --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.
# Data journalism methodology Systematic approaches for finding, analyzing and presenting data in journalism. ## Story structure for data journalism ### Data journalism framework ```markdown The framework for data journalism was established by Philip Meyer, a journalist for Knight-Ridder, Harvard Nieman Fellow and professor at UNC-Chapel Hill. In his book <i>The New Precision Journalism</i>, which outlines his ideas, Meyer encourages journalists to treat journalism "as if it were a science" by adopting the scientific method: - Making observation(s) / formulating a questiom - Researching the question / Collect, store and retrieve data - Formulate a hypothesis - Test the hypothesis, using both qualitative (interviews, documents etc.) and quantitative (data analysis etc.) methods - Analyze the results and reduce them to the most important findings - Present them to the audience This process should be thought of as iterative, rather than sequential. ## The data story arc ### 1. The hook (nut graf) - What's the key finding(s)? - Why should readers care? - What's the human impact? ### 2. The evidence - Show the data - Explain the methodology - Acknowledge limitations ### 3. The context -
- Story structure for data journalism
- Data journalism framework
- Methodology documentation template
- Data acquisition
- Public data sources
- Data request strategies
- Data cleaning and preparation
- Common data problems
- Data validation checklist
- Statistical analysis for journalism
- Basic statistics with context
- Comparisons and context
- Correlation vs causation
- Data visualization
pip install folium mapclassify matplotlib
What does the data-journalism skill do?
Data journalism workflows for analysis, visualization, and storytelling. Use when analyzing datasets, creating charts and maps, cleaning messy data, calculating statistics or building data-driven stories. Essential for reporters, newsrooms and researchers working with quantitative information.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill data-journalism --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 majiayu000/claude-skill-registry, a repository with 534 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.