Exploratory Data Analysis
spacering-net/codeg
Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats.
A skill your agent uses when executing and reporting the analysis for a Population and Development Review (PDR, Wiley / Population Council) manuscript so it survives expert, double-anonymized review…
Install Popdevr Data Analysis
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popdevr-data-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/Population-and-Development-Review-Skills/skills/popdevr-data-analysis .claude/skills/popdevr-data-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "popdevr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Population-and-Development-Review-Skills/skills/popdevr-data-analysis into .claude/skills/popdevr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popdevr-data-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Population-and-Development-Review-Skills/skills/popdevr-data-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popdevr-data-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/Population-and-Development-Review-Skills/skills/popdevr-data-analysis .agents/skills/popdevr-data-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "popdevr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Population-and-Development-Review-Skills/skills/popdevr-data-analysis into .agents/skills/popdevr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popdevr-data-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popdevr-data-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/Population-and-Development-Review-Skills/skills/popdevr-data-analysis .cursor/skills/popdevr-data-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "popdevr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Population-and-Development-Review-Skills/skills/popdevr-data-analysis into .cursor/skills/popdevr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popdevr-data-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/brycewang-stanford/Awesome-Journal-Skills.git --path Population-and-Development-Review-Skills/skills/popdevr-data-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popdevr-data-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/Population-and-Development-Review-Skills/skills/popdevr-data-analysis .gemini/skills/popdevr-data-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "popdevr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Population-and-Development-Review-Skills/skills/popdevr-data-analysis into .gemini/skills/popdevr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popdevr-data-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popdevr-data-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/Population-and-Development-Review-Skills/skills/popdevr-data-analysis .github/skills/popdevr-data-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "popdevr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Population-and-Development-Review-Skills/skills/popdevr-data-analysis into .github/skills/popdevr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popdevr-data-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install brycewang-stanford/Awesome-Journal-Skills popdevr-data-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/brycewang-stanford/Awesome-Journal-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/Population-and-Development-Review-Skills/skills/popdevr-data-analysis .opencode/skills/popdevr-data-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "popdevr-data-analysis" agent skill from https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Population-and-Development-Review-Skills/skills/popdevr-data-analysis into .opencode/skills/popdevr-data-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "popdevr-data-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
popdevr-data-analysis- GitHub stars
- 1.2k
- Token cost
- ~1.8k tokens
- SKILL.md length
- 731 words
- Files
- 1
- Skills in repo
- 2,387
- Repo updated
- First seen
- Licence
- MIT
At a glance
A skill your agent uses when executing and reporting the analysis for a Population and Development Review (PDR, Wiley / Population Council) manuscript so it survives expert, double-anonymized review…
- Works in 7 steps: Get the denominators right. Exposure… → Report uncertainty honestly.… → Decomposition with clear components.… → …
- Executing and reporting the analysis for a Population and Development Review (PDR
- SKILL.md covers When to trigger, Analysis norms PDR expects, Demographic and comparative… and Reproducibility while you work…, plus 5 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Popdevr Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when executing and reporting the analysis for a Population and Development Review (PDR, Wiley / Population Council) manuscript so it survives expert, double-anonymized review — correct rate construction, honest uncertainty, and demographic methods done right, with the development/policy meaning of each quantity made clear. Guides analysis and reporting norms; it does not fabricate results.
Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Data analysis. The repository describes itself as: Journal-specific Claude Code/Codex skill packs covering mainstream journals — AER, QJE, Nature, Cell, 管理世界, 经济研究 & 200+ more — your fast track to getting published. ｜ 覆盖主流期刊的… The licence is MIT.
When your agent uses it
- Executing and reporting the analysis for a Population and Development Review (PDR
- Wiley / Population Council) manuscript so it survives expert
- Double-anonymized review — correct rate construction
- Honest uncertainty
Example prompts
- “/popdevr-data-analysis”
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Get the denominators right. Exposure (person-years), the correct base population, and
- Report uncertainty honestly. Confidence/credible intervals for rates, life-expectancy
- Decomposition with clear components. State precisely what each component (rate vs. composition,
- APC discipline. Be explicit about the identification problem; report under the stated constraint
- Survival/event-history rigor. Check proportional hazards; handle censoring, truncation, and
- Right inference for the data. Survey/design weights and complex-design variance where applicable;
- Make the development meaning explicit. For each headline quantity, say what it implies for the
What it can do on your machine
Read from SKILL.md and the folder at commit 932eb23. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Popdevr Data Analysis loads about 1.8k tokens when it runs. Until then it costs about 105 tokens; SKILL.md has 731 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from brycewang-stanford/Awesome-Journal-Skills at commit 932eb23, republished under its MIT licence (© brycewang-stanford). 731 words, ~1,810 tokens.
Download SKILL.mdSave it as
.claude/skills/popdevr-data-analysis/SKILL.md (or your agent's skills folder).- name
- popdevr-data-analysis
- description
- Use when executing and reporting the analysis for a Population and Development Review (PDR, Wiley / Population Council) manuscript so it survives expert, double-anonymized review — correct rate construction, honest uncertainty, and demographic methods done right, with the development/policy meaning of each quantity made clear. Guides analysis and reporting norms; it does not fabricate results.
Data Analysis (popdevr-data-analysis)
PDR reviewers are expert demographers and development scholars, and the journal expects analyses that
are reproducible and interpretable to a broad readership. Analyze as if a methodologist will re-derive
your rates and an economist will ask what each number means for development — because both may. This
skill covers execution and reporting norms; method choice lives in popdevr-research-design.
When to trigger
- Constructing rates and life tables; building the results section
- Running a decomposition, event-history, APC, or projection analysis
- A reviewer asked for robustness, sensitivity, or alternative specifications
- Making the analysis reproducible and its development meaning explicit before deposit
Analysis norms PDR expects
- Get the denominators right. Exposure (person-years), the correct base population, and age/period alignment are where demographic analyses live or die. Document how rates were built.
- Report uncertainty honestly. Confidence/credible intervals for rates, life-expectancy contributions, projection scenarios, and derived quantities — not just point estimates or stars. Bootstrap or delta-method intervals for decomposition components and life-table functions.
- Decomposition with clear components. State precisely what each component (rate vs. composition, age contribution, factor) represents and which maps to a development channel; ensure components sum to the total being explained.
- APC discipline. Be explicit about the identification problem; report under the stated constraint and show sensitivity to plausible alternatives — never imply a unique decomposition.
- Survival/event-history rigor. Check proportional hazards; handle censoring, truncation, and competing risks correctly; report on the right time scale (age, duration, period).
- Right inference for the data. Survey/design weights and complex-design variance where applicable; cluster at the appropriate level; small-sample corrections when groups (e.g., countries) are few.
- Make the development meaning explicit. For each headline quantity, say what it implies for the social, economic, or environmental outcome — the PDR bar is not a clean estimate alone.
Demographic and comparative computation specifics
- Document data version/vintage (e.g., HMD/HFD/WPP release, DHS round), harmonization steps, and any smoothing/graduation applied to rates.
- For projections: report the scenarios, base population, transition-rate assumptions, and sensitivity; tie scenarios to development or policy futures where that is the contribution.
- For cross-country work: be explicit about comparability (definitions, coverage, data quality) before reading a cross-national contrast as a development effect.
Reproducibility while you work (not at the end)
- One master script regenerates every table, figure, life table, decomposition, and projection from the (raw or constructed) data.
- Set and report seeds for bootstrap and simulation.
- Pin software/package versions (
renv.lock,requirements.txt, recordedssc/netinstalls). - Keep table/figure numbers in the manuscript matched to script outputs (see
popdevr-transparency-and-data).
Show full SKILL.md (317 more words)Show less
Execution bridge (StatsPAI / Stata MCP)
Run the battery, don't just enumerate it. Full map:
execution-with-mcp. PDR is population studies blending quantitative and policy work; apply the chain to its empirical-causal papers.
- Many outcomes / specifications:
romano_wolf(step-down FWER) orbenjamini_hochberg— report the adjusted threshold. - OVB sensitivity:
oster_delta/sensemakr. - Inference:
wild_cluster_bootstrap(few clusters),twoway_cluster/conley; multilevel data → cluster at the right level. - Re-fit off one handle:
audit_result(result_id)lists the missing checks and the exactsuggest_functionfor each. - Exhibits:
etable/did_summary_to_latexfrom the handle — no retyped numbers.
Keep the decisive checks in the body and the exhaustive battery in the supplement. See the executed chain in the JF execution walkthrough.
Anti-patterns
- Mismatched numerator/denominator or wrong exposure (the classic demographic error)
- Point estimates of life expectancy, decomposition components, or projections with no uncertainty
- An APC model presented as the uniquely correct partition
- Reading a cross-country correlation as a development effect without addressing comparability
- A results section whose rates and decompositions the code cannot reproduce
Evidence pass for PDR
Run this as a concrete capability pass. First lock the population process, the development/policy linkage, the data and time scale, the selection/measurement issue, and the uncertainty; then test whether the manuscript addresses PDR's broad audience who inspect both the population evidence and its development meaning.
- Primary move: Audit unit, comparison, uncertainty, missingness, sensitivity, comparability, and reproducibility before making any prose or submission recommendation.
- Decision ledger: return
claim / evidence / blocker / next editrows so the next pass can patch the manuscript directly. - Sibling comparison: compare against Demography and Population Studies (methods-forward), Population Research and Policy Review (applied policy), and Studies in Family Planning (programs); if a neighbor has the stronger audience claim, recommend re-routing before polishing.
- Verification floor: before submission-ready advice, re-open
resources/official-source-map.mdfor volatile rules and name the one unresolved fact that could change the recommendation.
Output format
【Main quantity】rate / e0 / decomposition / hazard / projection + magnitude + interval
【Development meaning】what it implies for the social/economic/environmental outcome
【Exposure / denominator check】correctly constructed? [Y/N]
【Decomposition】components defined + sum to total? [Y/N/NA]
【APC / comparability】constraint stated / cross-country comparability addressed? [Y/N/NA]
【Inference】weights/clustering/competing risks handled? [Y/N]
【Reproducible】master script + seeds + pinned versions? [Y/N]
【Next】popdevr-tables-figuresSupplementary resources
../../resources/external_tools.md— life-table, decomposition, survival, APC, and projection packages../../resources/official-source-map.md— data-availability and reproducibility expectations
© brycewang-stanford, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in Population-and-Development-Review-Skills/skills/popdevr-data-analysis of brycewang-stanford/Awesome-Journal-Skills.
Open the folder on GitHubat commit 932eb23
Compare with similar skills
Popdevr Data Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Popdevr Data Analysis this skillbrycewang-stanford/Awesome-Journal-Skills | 1.2k | — | ~1.8k | Automated safety check: Pass | MIT | |
| Exploratory Data Analysisspacering-net/codeg | 3.8k | 15 repos | ~3.6k | Automated safety check: Pass | MIT | |
| Excel and CSV Data Analysisbytedance/deer-flow | 83k | 4 repos | ~2.2k | Automated safety check: Pass | MIT | |
| Exploratory Data AnalysisOleafly/Oleafly | 205 | 2 repos | ~3.4k | Automated safety check: Notes | MIT | |
| Python Executorcortega26/chile-hub | 113 | 2 repos | ~1.5k | Automated safety check: Pass | MIT | |
| Agentic Kaggle WorkflowFrankS-IntelLab/agentic-kaggle-skill | 188 | — | ~4k | Automated safety check: Pass | MIT |
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Questions about Popdevr Data Analysis
What does Popdevr Data Analysis do?
A skill your agent uses when executing and reporting the analysis for a Population and Development Review (PDR, Wiley / Population Council) manuscript so it survives expert, double-anonymized review…. Popdevr Data Analysis is an agent skill from brycewang-stanford/Awesome-Journal-Skills. Use when executing and reporting the analysis for a Population and Development Review (PDR, Wiley / Population Council) manuscript so it survives expert, double-anonymized review — correct rate construction, honest uncertainty, and demographic methods done right, with the development/policy meaning of each quantity made clear.
When should I use Popdevr Data Analysis?
Popdevr Data Analysis fits situations like: executing and reporting the analysis for a Population and Development Review (PDR; wiley / Population Council) manuscript so it survives expert; double-anonymized review — correct rate construction; honest uncertainty.
How do I install Popdevr Data Analysis in Claude Code?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a claude-code`. Or copy the skill folder (Population-and-Development-Review-Skills/skills/popdevr-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .claude/skills/popdevr-data-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Popdevr Data Analysis in Codex?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a codex`. Or copy the skill folder (Population-and-Development-Review-Skills/skills/popdevr-data-analysis in brycewang-stanford/Awesome-Journal-Skills) into .agents/skills/popdevr-data-analysis in your project. Codex loads it when a task matches its description.
Can I use Popdevr Data Analysis in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill popdevr-data-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/popdevr-data-analysis, .gemini/skills/popdevr-data-analysis, .github/skills/popdevr-data-analysis and .opencode/skills/popdevr-data-analysis in your project.
What does Popdevr Data Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Popdevr Data Analysis is instructions for the agent only.
Does Popdevr Data Analysis access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Popdevr Data Analysis safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Popdevr Data Analysis use?
Popdevr Data Analysis is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Popdevr Data Analysis use?
About 1.8k tokens (SKILL.md is roughly 7.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Popdevr Data Analysis?
Skills that share tags, products or a category with Popdevr Data Analysis: Exploratory Data Analysis (spacering-net/codeg, 3.8k stars), Excel and CSV Data Analysis (bytedance/deer-flow, 83k stars), Exploratory Data Analysis (Oleafly/Oleafly, 205 stars) and Python Executor (cortega26/chile-hub, 113 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Popdevr Data Analysis?
brycewang-stanford (a GitHub user) maintains it in brycewang-stanford/Awesome-Journal-Skills, which has 1,216 GitHub stars. The repository holds 2,387 skills in this directory. The repository was last updated on September 27, 2026.
Source: brycewang-stanford/Awesome-Journal-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.