# Script Translator > Use this skill whenever the user wants to translate, convert, or port a script from one statistical programming language to another — STATA, Python (pandas/numpy/statsmodels), or R (tidyverse/base R). Trigger even if the user says 'rewrite in R', 'convert to Python', 'port to STATA', or asks how code would look in another language. - Skill: `majiayu000/script-translator` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds add majiayu000/script-translator` - Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/script-translator/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Data & Analytics - Author: majiayu000 (https://skillmd.com/u/majiayu000) - Updated: 2026-09-09 - Page: https://skillmd.com/skills/majiayu000/script-translator --- # Script Translator Faithful line-by-line translation between Stata, Python, and R. ## 1. Detect Source and Target Languages **From the user message:** Look for keywords like "to Python", "in R", "port to Stata", "convert to R", "rewrite in Python". **From file extension:** - `.do` → Stata - `.py` → Python - `.R` / `.r` → R **If ambiguous:** Ask the user to confirm source and target before proceeding. ## 2. Load the Language-Pair Body File Before writing ANY translated code, read the relevant body file: | Direction | File to read | |-----------|-------------| | Python → R | `bodies/python-to-r.md` | | Python → Stata | `bodies/python-to-stata.md` | | R → Python | `bodies/r-to-python.md` | | R → Stata | `bodies/r-to-stata.md` | | Stata → Python | `bodies/stata-to-python.md` | | Stata → R | `bodies/stata-to-r.md` | The body file contains the construct mapping table, idiomatic equivalences, required imports, and known traps for that specific pair. Follow it closely. ## 3. Core Translation Rules (All Language Pairs) These rules are absolute and override any instinct to "improve" the code: ### 3a. Structure and Logic 1. **Translate line by line**, preserving the order and structure of the original 2. **Keep variable names identical** — never rename columns, variables, or macros 3. **Preserve all data filters and conditions exactly** — same logic, same thresholds 4. **DO NOT refactor, optimize, or restructure** the code 5. **DO NOT change the order of operations** unless strictly required by the target language 6. **If the original has a bug, translate the bug faithfully** and add `# REVIEW: possible bug in original` 7. **Add short inline comments** when a translated line is non-obvious (e.g., `# Stata's egen mean() equivalent`) 8. **Flag with `# REVIEW:`** any construct that has no direct equivalent or requires manual verification ### 3b. Methodology (Non-Negotiable) The translated script must produce **statistically identical results**: 9. **Same estimator** — OLS stays OLS, logit stays logit, probit stays probit. Never substitute. 10. **Same standard errors** — `robust` (HC1) stays HC1. `cluster(var)` stays clustered at the same variable. Never change the SE type or clustering level. Verify the target language's default matches (e.g., Stata `robust` = HC1, statsmodels `HC1` = HC1, but statsmodels default is not robust). 11. **Same fixed effects** — `areg, absorb(fe)` → must absorb the same variable, not include as dummies unless no absorb equivalent exists. Flag with `# REVIEW:` if the approach differs. 12. **Same merge logic** — left join stays left join, m:1 stays m:1. Preserve `validate` checks. Add `_merge` diagnostics if the original inspects them. 13. **Same sample restrictions** — every `keep if`, `drop if`, filter, and subsetting condition must be translated exactly. Missing value handling differs across languages — explicitly handle this (see body files for language-specific traps). 14. **Same weighting** — `[pw=wt]`, `[aw=wt]`, `[fw=wt]` must map to the exact equivalent. Flag if the target language doesn't distinguish weight types. 15. **Same test statistics** — F-tests, t-tests, Wald tests, correlation tests must use the same test. `pwcorr, sig` → Pearson with p-values, not Spearman. 16. **Same confidence level** — if the original uses 95% CI, the translation uses 95% CI. Same for significance stars (* 0.10 ** 0.05 *** 0.01). ### 3c. Visual Fidelity (Non-Negotiable) The translated figure must be **visually identical** to the original. Go through every visual property line by line: 17. **Same plot type** — scatter stays scatter, bar stays bar, line stays line 18. **Same colors** — `blue` stays `blue`, `red` stays `red`. Match the exact color name or hex code. 19. **Same transparency/alpha** — `alpha=0.7` → `%70` in Stata, `alpha = 0.7` in R. Never omit. 20. **Same marker properties** — marker shape, size, edge color, edge width. If the original has `edgecolors="white", linewidth=0.5`, the translation must replicate this (Stata: `mlcolor(white) mlwidth(vthin)`). 21. **Same grid** — if the original has `ax.grid(True, alpha=0.3)`, the translation must include grid lines. If there is no grid, the translation must not add one. 22. **Same axis labels, title, and legend** — identical text, same position, same ordering 23. **Same legend position** — `position(5) ring(0)` = lower right inside. Default upper-right → translate to upper-right. Never leave to default if the original specifies a position. 24. **Same point labels/annotations** — if points are labeled with state names, font size, position offset, and alignment must all be replicated as closely as the target language allows. 25. **Same axis range and ticks** — if the original sets `ylim`, `xlim`, or custom tick marks, replicate them. If it uses auto-scaling, let the target auto-scale too. 26. **Same figure size** — `figsize=(8, 6)` → target equivalent (Stata: `xsize(8) ysize(6)`; R: `width = 8, height = 6`) 27. **Same background** — white background must be explicitly set in every language (it is NOT the default in Stata or base R) 28. **Same output format and resolution** — PNG at 300 DPI. Always. **If a visual property cannot be exactly replicated**, add a `# REVIEW: [property] has no exact equivalent in [target language]` comment explaining the closest approximation used. ## 4. Apply Project Boilerplate After translation, wrap the script in the project's conventions: **Python target:** - `import config as cfg` for paths - `cfg.FIGURES / "name.png"` for figure output - `dpi=300`, `bbox_inches='tight'`, `plt.close(fig)` - Module docstring with inputs/outputs **Stata target:** - `version 17`, `clear all`, `set more off` - `do "$root/code/stata/config_local.do"` for `$data_root` - `log using "$root/quality_reports/stata_logs/[name].log", replace` - `graphregion(color(white)) bgcolor(white)`, `width(2400)` - `log close` at end **R target:** - `library()` calls at top - `here::here()` for paths - `ggsave(width = 8, height = 6, dpi = 300)` - `set.seed(42)` if stochastic ## 5. Output Format Present the translation as: 1. **Translated script** in a fenced code block 2. **Translation notes** section listing: - Any `# REVIEW:` items and why they were flagged - Differences in default behavior between languages (e.g., 0-vs-1 indexing) - Packages/libraries the target script requires ## 6. Run and Verify After writing the translated script, run it and check for errors: - **Python:** `python code/py/