AgentSkillsCN

data-analysis

端到端的 R 数据分析流程，从探索性分析一路贯穿回归分析，直至产出可供发表的表格与图表。

SKILL.md
--- frontmatter
name: data-analysis
description: End-to-end R data analysis workflow from exploration through regression to publication-ready tables and figures.
disable-model-invocation: true
argument-hint: "[dataset path or description of analysis goal]"
allowed-tools: ["Read", "Grep", "Glob", "Write", "Edit", "Bash", "Task"]

Data Analysis

Run an end-to-end data analysis in R through 5 phases.

Phase 1: Setup and Data Loading

  • •Read R code conventions from .claude/rules/r-code-conventions.md
  • •Create script with proper header (title, author, purpose, inputs, outputs)
  • •Load packages with library() (never require())
  • •Set set.seed() if stochastic elements are involved
  • •Load data using relative paths

Phase 2: Exploratory Data Analysis

  • •Summary statistics (mean, sd, min, max, N)
  • •Missingness patterns
  • •Distributions of key variables
  • •Bivariate relationships
  • •Time patterns (if panel data)
  • •Group comparisons
  • •Save diagnostics to output/diagnostics/

Phase 3: Main Analysis

  • •Use fixest for panel data with fixed effects (see /econometrics-r for detailed patterns)
  • •Use lm/glm for cross-section
  • •Cluster standard errors appropriately
  • •Run multiple specifications (simple to complex)
  • •Report both statistical and economic significance
  • •For causal inference (IV, DiD, RDD), see /causal-inference-r for diagnostics and modern estimators
  • •For spatial econometrics, see /econometrics-r for spdep/spatialreg patterns

Phase 4: Publication-Ready Output

  • •Tables: modelsummary (preferred) or stargazer, export as .tex and .html
  • •Figures: ggplot2 with project theme, explicit dimensions, white background, 300 DPI
  • •Export figures as .pdf and .png

Phase 5: Save and Review

  • •saveRDS() for all computed objects
  • •Run r-reviewer agent on generated script
  • •Address Critical/High issues

Script Structure Template

r
# ==============================================================================
# Title: [Analysis Name]
# Author: [Name]
# Date: [YYYY-MM-DD]
# Purpose: [What this script does]
# Inputs: [Data files]
# Outputs: [Tables, figures, RDS files]
# ==============================================================================

# 0. Setup ----
library(tidyverse)
library(fixest)
library(modelsummary)

# 1. Data Loading ----

# 2. Exploratory Analysis ----

# 3. Main Analysis ----

# 4. Tables and Figures ----

# 5. Export ----

All scripts saved to scripts/R/, all outputs to output/.