Master Data Prompt Pack
Demographic, NHANES, Survey, World-in-Data, Mapping & Modeling Prompts
1 📦 MASTER DATA PROMPT PACK — Demographic & Survey Data Analysis (R + AI)
For a 5-Day Workshop: NHANES, World-in-Data, Demographic Surveys, EDA, Modeling & Maps
2 1️⃣ Foundation Prompts — Starting Any Data Task
2.1 🔹 Prompt 1: Understand My Dataset
You are a data analysis expert. I will upload a dataset.
Please examine its structure, variable types, missingness, and give me:
1. Summary of dataset
2. Data quality issues
3. Potential analytic directions
4. Suggested plots and modeling steps
5. Which variables look demographic and which look health/socioeconomic
Use clear bullet points.2.2 🔹 Prompt 2: Generate a Full EDA Plan
Create a complete EDA plan for a demographic/health dataset.
Include:
- Descriptive statistics
- Missing data treatment options
- Outlier detection methods
- Grouped summaries (gender/age/income)
- Plots (histogram, boxplot, barplot, correlations)
- Survey-weight considerations (if applicable)
- Recommendations for modeling
Output in step-by-step format.3 2️⃣ Prompts for NHANES Analysis
3.1 🔹 Prompt 3: NHANES Cleaning & Recoding
You are NHANES specialist.
I want to clean NHANES data and prepare it for analysis.
Give me R code for:
- Recoding demographics (age groups, BMI categories, race)
- Creating comorbidity indicators (hypertension, diabetes, obesity)
- Handling missing survey weights
- Preparing survey design object (svydesign)3.2 🔹 Prompt 4: NHANES Risk Factor Index
Using NHANES variables, generate an R script to create a composite
health risk index (hypertension, obesity, diabetes, inactivity, smoking).
Include:
- Binary indicators
- Row-sum risk score
- Distribution summary
- Visualization 4 3️⃣ Prompts for Demographic Survey Data (DHS/Custom Surveys)
4.1 🔹 Prompt 5: Survey EDA + Weighting
You are a survey data modeling expert.
I have a DHS-style demographic dataset.
Create R code to:
- Apply sample weights
- Produce weighted frequencies and cross-tabs
- Generate fertility, mortality, and household indicators
- Visualize distributions
- Summarize key demographic trends 4.2 🔹 Prompt 6: Complex Survey Modeling
Help me build survey-weighted regression models using R's survey package.
Provide:
- Logistic model example
- Poisson/negative binomial example
- Guidance on interpretation
- Goodness-of-fit diagnostics
- How to use strata and PSU variables 5 4️⃣ Prompts for World-in-Data + Global Datasets
5.1 🔹 Prompt 7: Country-Level EDA (World in Data)
I want to analyze country-level demographic indicators using World in Data.
Generate an R workflow that:
- Downloads selected indicators (fertility, GDP per capita, life expectancy)
- Merges them
- Cleans and creates harmonized country-year panel
- Performs EDA, trends, and comparative analysis
- Highlights Pakistan vs regional peers 5.2 🔹 Prompt 8: Cross-Country Modeling
Develop a cross-country demographic model using:
- fertility rate
- GDP per capita
- female education
- urbanization
- health spending
Provide R code for:
- Panel regression setup
- Fixed vs random effects choice
- Diagnostics
- Interpretation in simple language 6 5️⃣ Prompts for Choropleth Maps (R)
6.1 🔹 Prompt 9: Choropleth Map Creation
Act as a mapping expert in R.
Generate code to:
- Load shapefiles (Pakistan districts or any country map)
- Merge demographic indicators with spatial data
- Create choropleth maps using tmap / ggplot2
- Add titles, legends, and color scales
- Produce high-resolution exportable maps6.2 🔹 Prompt 10: Comparative Spatial Patterns
Create a side-by-side spatial comparison map for two demographic variables:
example: literacy rate vs child mortality.
Provide R code for:
- Data merge
- Two-panel tmap layout
- Summary interpretation for policymakers 7 6️⃣ Prompts for Full AI-Driven Analysis Workflows
7.1 🔹 Prompt 11: End-to-End AI-Guided Data Analysis
You are my AI data analyst.
Given this dataset, produce a full workflow:
1. Understand dataset
2. Clean & preprocess
3. EDA visualizations
4. Feature engineering
5. Regression/classification/clustering
6. Model interpretation
7. Policy-relevant narrative
Generate R code and explanations.7.2 🔹 Prompt 12: “Vibe Coding” — Improve Diagnostics
Review my R code and “vibe it up.”
Improve:
- efficiency
- readability
- narrative labeling
- interpretability
- comments for students
Suggest alternative plots and better coding style.7.3 🔹 Prompt 13: AI-Generated Storytelling for Data
Based on my dataset summary, write a short, simple, policy-friendly
story that explains the demographic trends and their implications.
Tone: accessible, non-technical.8 7️⃣ Prompts Specific to the 5-Day Workshop Flow
8.1 Day 1 – Data Literacy & EDA
Create hands-on beginner exercises for demographic EDA:
- Gender/age structure
- Fertility patterns
- Mortality indicators
- Nutritional categories (BMI)
Include R solutions and explanations.8.2 Day 2 – NHANES Deep-Dive
Design NHANES mini-projects for students with:
- health disparities
- age comparisons
- risk scoring
- survey-weighted models
Include R code templates.8.3 Day 3 – Survey Data Modeling
I need 4 survey-modeling case studies:
- Child health
- Women fertility
- Household deprivation
- Education outcomes
Provide R code and interpretation.8.4 Day 4 – World-in-Data & Country Analysis
Generate cross-country comparative exercises using WDI or OWID.
Focus on Pakistan vs Vietnam, Bangladesh, India.
Include simple interpretations.8.5 Day 5 – Mapping & Final Projects
Prepare final project ideas involving:
- choropleth maps
- demographic trends
- NHANES risk models
- survey analysis
Provide clear instructions + outcomes expected.9 ✔️ What This Prompt Pack Covers
- EDA prompts
- NHANES prompts
- Survey modeling prompts
- Mapping prompts
- Vibe-coding prompts
- Full workflows
- Pakistan-focused cross-country prompts