# Table > Called by /plot to upgrade regression and summary tables to top-journal standards. - Skill: `zhouziyue233/table` (Agent Skill) - Install (CLI): `npx skillmds@latest add zhouziyue233/table` - Raw SKILL.md: https://api.skillmd.com/api/skills/zhouziyue233/table/raw - Safety review: PASS (external: skill-scanner PASS, skillspector PASS) - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: zhouziyue233 (https://skillmd.com/u/zhouziyue233) - Updated: 2026-08-19 - Page: https://skillmd.com/skills/zhouziyue233/table --- # LaTeX Table Formatting Skill This skill generates publication-quality regression tables, summary statistics tables, and multi-panel layouts for economics journals. Covers the major table-making tools: `pyfixest` (Python, primary), `esttab/estout` (Stata), `modelsummary/fixest::etable` (R), and `stargazer` (R/Python). ## Step 0: Workflow Interface When called by `/plot` or another upstream command, this skill accepts a structured context block. **Do not re-ask the user for information already present in the context.** ``` table_type: table1_descriptive | table2_balance | table3_main | table_robustness | table_heterogeneity strategy: DiD | RDD | IV | PanelFE | SC | OLS model_results: path to regression output .csv (e.g., tables/table3_main_results.csv) software: python | r | stata cluster_var: variable name or "none" fe_list: e.g., ["unit FE", "time FE"] or [] sample_desc: e.g., "Firm-year panel, 2000–2015, N=12,450" project_name: string ``` When called standalone (not via `/plot`), prompt the user for `table_type`, `strategy`, and `software` before proceeding. **Software → tool routing (execute only the matching section; skip all others):** | `software` | Primary tool | Section to execute | |---|---|---| | `python` | `pyfixest.etable()` | [Python — pyfixest.etable()](#python--pyfixedetable-primary) | | `r` | `modelsummary` + `fixest::etable` | [R — modelsummary](#r--modelsummary) / [R — fixest::etable](#r--fixestetable) | | `stata` | `esttab/estout` | [Stata — esttab/estout](#stata--esttabstout) | **Routing rules:** 1. Generate code **only** for the `software` specified in the caller context. Do not generate parallel versions in other languages unless the user explicitly requests them. 2. For `software = r`: if the upstream `/code` command used `fixest::feols`, prefer `fixest::etable()` (native, zero conversion); use `modelsummary` when the user needs `.docx` or `.html` output in addition to `.tex`. 3. For `software = python`: `pyfixest` objects (`feols`, `fepois`, `iv2sls`) pass directly to `etable()`. Do not use `statsmodels` or `pystout` unless `pyfixest` is unavailable. 4. For `software = stata`: `reghdfe` → `eststo` → `esttab` is the standard chain. Always call `ssc install estout` check at the top of the do-file. **Output convention (always dual-format):** Every table must be saved in two files: - `tables/tableN_name.tex` — body-only file for `\input{}` in the paper - `tables/tableN_name.csv` — raw numbers for manual verification **Table type → template routing:** | `table_type` | Template | Key Features | |---|---|---| | `table1_descriptive` | Descriptive stats | Variable groups, mean/sd/min/max/N, \multicolumn section headers | | `table2_balance` | Balance test | Pre-treatment filter enforced, normalized diff column, ✅/⚠️ flag | | `table3_main` | Main regression | Multi-column, FE rows, controls Yes/No, clustered SE note | | `table_robustness` | Robustness | Panel layout (Panel A/B/C), same dep. var across specs | | `table_heterogeneity` | Heterogeneity | Subgroup headers, interaction terms, p-value of difference | ## Quick Decision: Which Tool to Use | Tool | Language | Best For | |------|----------|----------| | `pyfixest.etable()` | Python ⚡ | Primary tool; works with feols/fepois/iv2sls from /code | | `esttab/estout` | Stata | Most flexible; Stata-native workflows | | `modelsummary` | R | Modern, clean API; many output formats | | `fixest::etable` | R | Fast tables from `fixest` regressions | | `stargazer` | R | Classic; widely used in econ | ## Regression Tables ### Stata — esttab/estout ```stata * Stata — multi-model regression table ssc install estout * Run models eststo clear eststo m1: reg y x1, robust eststo m2: reg y x1 x2, robust eststo m3: reg y x1 x2 x3, robust eststo m4: reghdfe y x1 x2 x3, absorb(fe_var) cluster(cluster_var) * Export to LaTeX esttab m1 m2 m3 m4 using "results.tex", replace /// b(3) se(3) /// // 3 decimal places star(* 0.10 ** 0.05 *** 0.01) /// // significance stars title("Main Results") /// mtitles("OLS" "OLS" "OLS" "FE") /// // column titles label /// // use variable labels keep(x1 x2 x3) /// // show only key vars order(x1 x2 x3) /// stats(N r2 r2_a, fmt(%9.0fc %9.3f %9.3f) /// labels("Observations" "R-squared" "Adj. R-squared")) /// addnotes("Robust standard errors in parentheses." /// "*** p<0.01, ** p<0.05, * p<0.1") /// booktabs /// // professional formatting fragment // no \begin{table} wrapper * --- CSV dual-output (always run alongside LaTeX export) --- * Export coefficient table as CSV for manual verification esttab m1 m2 m3 m4 using "tables/table3_main_results.csv", replace /// b(3) se(3) star(* 0.10 ** 0.05 *** 0.01) /// csv plain noobs * Multi-panel table esttab m1 m2 using "panel_a.tex", replace booktabs fragment /// prehead("\begin{table}[htbp]" "\centering" "\caption{Results}" /// "\begin{tabular}{lcc}" "\toprule" /// "& \multicolumn{2}{c}{\textit{Panel A: Full Sample}} \\" /// "\cmidrule(lr){2-3}") esttab m3 m4 using "panel_b.tex", replace booktabs fragment /// prehead("\midrule" /// "& \multicolumn{2}{c}{\textit{Panel B: Subsample}} \\" /// "\cmidrule(lr){2-3}") /// postfoot("\bottomrule" "\end{tabular}" /// "\begin{tablenotes}" "\small" /// "\item Standard errors in parentheses." /// "\end{tablenotes}" "\end{table}") ``` ### R — modelsummary > **Workflow note:** `modelsummary` accepts `fixest::feols` objects directly — no conversion needed. If `/code` used `feols`, pass those objects straight into `modelsummary()` or `fixest::etable()`. Prefer `fixest::etable()` for speed; use `modelsummary()` when you need `.docx` or `.html` output alongside `.tex`. ```r # R — modelsummary (modern, flexible) library(modelsummary) m1 <- lm(y ~ x1, data = df) m2 <- lm(y ~ x1 + x2, data = df) m3 <- lm(y ~ x1 + x2 + x3, data = df) # LaTeX output modelsummary( list("(1)" = m1, "(2)" = m2, "(3)" = m3), coef_map = c("x1" = "Treatment", "x2" = "Control 1", "x3" = "Control 2"), gof_map = c("nobs", "r.squared", "adj.r.squared"), stars = c('*' = .1, '**' = .05, '***' = .01), title = "Main Results", notes = "Robust standard errors in parentheses.", output = "tables/table3_main_results.tex" ) # --- CSV dual-output --- modelsummary( list("(1)" = m1, "(2)" = m2, "(3)" = m3), output = "tables/table3_main_results.csv" # same call, different extension ) # Add fixed effects indicators modelsummary( list("(1)" = m1, "(2)" = m2, "(3)" = m3), add_rows = tribble( ~term, ~"(1)", ~"(2)", ~"(3)", "Year FE", "No", "Yes", "Yes", "Industry FE", "No", "No", "Yes" ), output = "results.tex" ) ``` ### R — fixest::etable ```r # R — etable (fast, built into fixest) library(fixest) m1 <- feols(y ~ x1, data = df, vcov = "HC1") m2 <- feols(y ~ x1 + x2 | year, data = df, vcov = ~cluster_var) m3 <- feols(y ~ x1 + x2 | year + industry, data = df, vcov = ~cluster_var) etable(m1, m2, m3, tex = TRUE, file = "results.tex", dict = c(x1 = "Treatment", x2 = "Control"), order = c("Treatment", "Control"), drop = "Intercept", fixef.group = list("Year FE" = "year", "Industry FE" = "industry"), style.tex = style.tex("aer"), # AER journal style title = "Main Results", notes = "Clustered standard errors in parentheses.") ``` ### R — stargazer ```r # R — stargazer (classic) library(stargazer) stargazer(m1, m2, m3, type = "latex", out = "results.tex", title = "Main Results", dep.var.labels = "Outcome Variable", covariate.labels = c("Treatment", "Control 1", "Control 2"), keep = c("x1", "x2", "x3"), add.lines = list( c("Year FE", "No", "Yes", "Yes"), c("Industry FE", "No", "No", "Yes") ), omit.stat = c("f", "ser"), notes = "Robust standard errors in parentheses.", notes.align = "l", star.cutoffs = c(0.1, 0.05, 0.01)) ``` ### Python — pyfixest.etable() (Primary) `pyfixest` is the standard Python estimation tool used by the `/code` command. Its `etable()` function produces booktabs-ready LaTeX and a tidy DataFrame simultaneously, enabling dual-format output with no extra work. ```python # Python — pyfixest regression table (primary workflow) import pyfixest as pf import pandas as pd from pathlib import Path TABLES_DIR = Path("tables") TABLES_DIR.mkdir(exist_ok=True) # Run models (mirrors /code output) m1 = pf.feols("y ~ x1", data=df, vcov="HC3") m2 = pf.feols("y ~ x1 + x2 | unit_id", data=df, vcov={"CRV1": "unit_id"}) m3 = pf.feols("y ~ x1 + x2 | unit_id + year", data=df, vcov={"CRV1": "unit_id"}) m4 = pf.feols("y ~ x1 + x2 | unit_id + year", data=df, vcov={"CRV1": "unit_id^year"}) # double-clustered # --- LaTeX output (.tex) --- etable_tex = pf.etable( [m1, m2, m3, m4], digits=3, stars=True, # *** 0.01, ** 0.05, * 0.10 coef_fmt="b (se)", # coefficient with SE below dict={ # rename variables "x1": "Treatment", "x2": "Log Income", "Intercept": "", # hide intercept label }, keep=["Treatment", "Log Income"], # show only key vars drop_intercept=True, tex=True, # Fixed effects and controls indicators added manually below ) # Add FE / controls indicator rows fe_block = r""" \midrule Unit FE & No & Yes & Yes & Yes \\ Year FE & No & No & Yes & Yes \\ Controls & No & No & No & Yes \\ """ # Inject FE block before \bottomrule, then wrap in full table environment def build_table_tex(etable_str, fe_block, caption, label, notes): """Wrap pyfixest etable fragment in a complete booktabs table.""" # etable(tex=True) returns a tabular fragment; inject FE rows + wrap body = etable_str.replace(r"\bottomrule", fe_block + r"\bottomrule") return ( r"\begin{table}[htbp]" + "\n" r"\centering" + "\n" rf"\caption{{{caption}}}" + "\n" rf"\label{{{label}}}" + "\n" + body + "\n" r"\begin{tablenotes}[flushleft]\footnotesize" + "\n" rf"\item \textit{{Notes:}} {notes}" + "\n" r"\end{tablenotes}" + "\n" r"\end{table}" ) notes_str = ( "Robust standard errors in parentheses, clustered at the unit level " "(columns 2--4). All regressions include the controls listed in row " "\\textit{Controls}. Sample: {sample_desc}. " "*** p$<$0.01, ** p$<$0.05, * p$<$0.10." ) full_tex = build_table_tex( etable_tex, fe_block, caption="Main Results: Effect of Treatment on Outcome", label="tab:main", notes=notes_str ) tex_path = TABLES_DIR / "table3_main_results.tex" tex_path.write_text(full_tex) print(f"Saved: {tex_path}") # --- CSV output (.csv) — always save for verification --- coef_df = pf.etable([m1, m2, m3, m4], digits=3, type="df") csv_path = TABLES_DIR / "table3_main_results.csv" coef_df.to_csv(csv_path, index=False) print(f"Saved: {csv_path}") ``` **FE indicator pattern:** Always add fixed-effects and controls indicator rows manually after `etable()` — `pyfixest` does not auto-generate these rows. The `fe_block` pattern above is the standard template. **IV / 2SLS tables with pyfixest:** ```python # First stage + Second stage in one table first = pf.feols("d ~ z + x1 | unit_id + year", data=df, vcov={"CRV1": "unit_id"}) second = pf.feols("y ~ 1 | unit_id + year | d ~ z", data=df, vcov={"CRV1": "unit_id"}) reduced = pf.feols("y ~ z + x1 | unit_id + year", data=df, vcov={"CRV1": "unit_id"}) iv_tex = pf.etable([first, second, reduced], digits=3, dict={"d": "Treatment (D)", "z": "Instrument (Z)", "fit_d": "Treatment (D) — IV"}, tex=True) # Add first-stage F-stat row manually: fstat = first.F_stat() # pyfixest attribute iv_tex = iv_tex.replace( r"\bottomrule", rf"First-stage F & {fstat:.1f} & & \\" + "\n" + r"\bottomrule" ) ## Journal-Specific Styles ### AER (American Economic Review) ```r # fixest style etable(m1, m2, m3, style.tex = style.tex("aer"), tex = TRUE) ``` Key conventions: booktabs rules, no vertical lines, significance noted in footnote not with stars (AER discourages stars). ### QJE / ReStud / Econometrica ```stata * Stata — clean academic style esttab m1 m2 m3 using "results.tex", replace /// b(3) se(3) star(* 0.10 ** 0.05 *** 0.01) /// booktabs fragment /// alignment(D{.}{.}{-1}) /// prehead("\begin{table}[htbp]" "\centering" /// "\caption{Title Here}\label{tab:main}" /// "\begin{tabular}{l*{3}{D{.}{.}{-1}}}" "\toprule") /// postfoot("\bottomrule" "\end{tabular}" /// "\begin{tablenotes}[flushleft]\footnotesize" /// "\item \textit{Notes:} Standard errors in parentheses." /// " *** p$<$0.01, ** p$<$0.05, * p$<$0.1" /// "\end{tablenotes}" "\end{table}") ``` ## Multi-Panel and Complex Layouts ### Side-by-Side Panels ```stata * Panel A: OLS, Panel B: IV esttab m_ols1 m_ols2 using "table.tex", replace booktabs fragment /// prehead("\begin{table}[htbp]\centering" /// "\caption{OLS and IV Estimates}" /// "\begin{tabular}{lcc}\toprule" /// "& \multicolumn{2}{c}{\textit{Panel A: OLS}} \\" /// "\cmidrule(lr){2-3}") esttab m_iv1 m_iv2 using "table.tex", append booktabs fragment /// prehead("\midrule" /// "& \multicolumn{2}{c}{\textit{Panel B: IV/2SLS}} \\" /// "\cmidrule(lr){2-3}") /// postfoot("\bottomrule\end{tabular}\end{table}") ``` ### Interaction Effects Table ```r # R — interaction table library(modelsummary) m_interaction <- lm(y ~ x1 * group, data = df) modelsummary(m_interaction, coef_rename = c("x1" = "Treatment", "group" = "Group", "x1:group" = "Treatment × Group"), output = "interaction.tex") ``` ## Tips for Clean Tables | Tip | Details | |-----|---------| | Use `booktabs` | `\toprule`, `\midrule`, `\bottomrule` instead of `\hline` | | No vertical lines | Standard in economics journals | | Align decimals | Use `dcolumn` package with `D{.}{.}{-1}` column type | | Stars in notes | Clearly state significance levels in table notes | | Variable labels | Use descriptive names, not variable codes | | Fixed effects rows | Show Yes/No indicators for FE inclusions | | Consistent decimals | 3 decimals for coefficients/SE; 0 for N | | Notes placement | Below the table, left-aligned, smaller font | ## Standardized Notes Format Every table **must** include a Notes line below the bottom rule. Notes are not optional — journals reject tables without them. Use this template, filling in the bracketed fields: ``` Notes: [SE type] in parentheses[, clustered at the [unit] level]. [FE description.] [Sample description: unit, time period, N.] [Any variable transformation or winsorization.] *** p<0.01, ** p<0.05, * p<0.1. ``` **Strategy-specific Notes templates:** | Strategy | Notes Template | |---|---| | DiD / TWFE | "Standard errors double-clustered by unit and year in parentheses. Regressions include unit and year fixed effects. Sample: [panel, years, N]." | | Event Study | "Standard errors clustered at the [unit] level. Reference period: t = −1. Coefficients plot relative effects; pre-period joint test p-value = [p]." | | RDD | "Bias-corrected robust standard errors (rdrobust) in parentheses. Bandwidth h = [h] selected by MSE-optimal selector. Local linear polynomial." | | IV / 2SLS | "Two-stage least squares. Standard errors clustered at the [unit] level. First-stage F-statistic = [F] (Stock-Yogo weak instrument critical value 10% = 16.38)." | | Panel FE | "Standard errors clustered at the [unit] level. Hausman test p-value = [p] (favors FE over RE). Regressions include [FE list]." | | OLS | "Heteroskedasticity-robust standard errors (HC3) in parentheses." | **LaTeX Notes implementation:** ```latex % Recommended: threeparttable + tablenotes (renders correctly in all TeX distributions) \usepackage{threeparttable} \begin{table}[htbp] \centering \caption{...} \begin{threeparttable} \begin{tabular}{...} ... \end{tabular} \begin{tablenotes}[flushleft] \footnotesize \item \textit{Notes:} Standard errors double-clustered by firm and year in parentheses. Regressions include firm and year fixed effects. Sample covers manufacturing firms, 2000--2015 ($N = 12{,}450$ firm-year observations). Revenue is winsorized at the 1st and 99th percentiles. *** $p<0.01$, ** $p<0.05$, * $p<0.1$. \end{tablenotes} \end{threeparttable} \end{table} ``` **Avoid:** bare `\footnote{}` for table notes (misplaces the note); `tabular` note rows (breaks alignment); notes that only say "Standard errors in parentheses" with no clustering or FE information. ## Common Pitfalls - **Too many decimals**: 3 is standard for coefficients; more is noise - **Missing clustering info**: Always state what SE are clustered on - **Forgetting FE indicators**: Reviewers need to know which FE are included - **Stars without notes**: Always define significance levels - **Cramming too many models**: 4–6 columns is typical maximum - **No CSV dual-output**: Always save `.csv` alongside `.tex` for verification ## LaTeX Integration: Paper-Ready Output When the output will be `\input{}`-ed into a compiled paper (rather than compiled standalone), three things consistently cause failures. Address them upfront. ### 1. Body-Only Files — No Document Wrapper Tools like `esttab`, `stargazer`, and manual Python scripts often emit a standalone `.tex` file with `\documentclass...\begin{document}...\end{document}`. This breaks `\input{}` in the parent paper because LaTeX cannot nest document environments. Always generate two versions: the full standalone file for spot-checking, and a **body-only** file stripped of the document wrapper for inclusion in the paper. ```python # Python — strip wrapper and save body-only file import re def save_body_only(tex_path): """Strip \documentclass...\\end{document} wrapper; keep only the table content.""" with open(tex_path) as f: txt = f.read() m = re.search(r'\\begin\{document\}(.*?)\\end\{document\}', txt, re.DOTALL) body = m.group(1).strip() if m else txt body_path = tex_path.replace('.tex', '_body.tex') with open(body_path, 'w') as f: f.write(body) return body_path ``` In the parent paper, include as: ```latex \input{tables/table2_main_results_body} % no .tex extension needed ``` Make sure each body file contains the full `\begin{table}...\end{table}` block — not just the `\begin{tabular}` fragment. A missing `\begin{table}` wrapper causes `\multicolumn` and `\caption` errors at compile time. ### 2. Avoid siunitx by Default The `siunitx` package (used for the `S` decimal-aligned column type) is absent in many TeX distributions and causes `! LaTeX Error: File 'siunitx.sty' not found`. Prefer standard column types: ```latex % Instead of: \begin{tabular}{l S S S} (requires siunitx) % Use: \begin{tabular}{l c c c} (always works) % For strict decimal alignment without siunitx, use the dcolumn package: \usepackage{dcolumn} % ships with every standard TeX distro \begin{tabular}{l D{.}{.}{-1} D{.}{.}{-1}} ``` For most robustness and heterogeneity tables, `c` columns are sufficient — the numbers are clearly readable without strict decimal alignment. Also avoid Unicode characters in Python-generated `.tex` files. Characters like `>=`, `->`, `<=` typed directly will break LaTeX. Always use their LaTeX equivalents: `$\geq$`, `$\rightarrow$`, `$\leq$`. ### 3. Overflow Prevention for Wide Tables A table with 6 or more columns, or with a text description column, will almost certainly overflow the page width in portrait mode. Apply these fixes together: ```latex % Rule: >=6 columns → wrap in landscape; text description column → use p{Xcm} not l \usepackage{pdflscape} % add to preamble % In the body file: \begin{landscape} \begin{table}[ht] \centering \caption{...} \begin{threeparttable} {\footnotesize\setlength{\tabcolsep}{4pt} % shrink font + column padding \begin{tabular}{p{4.5cm} c c c c c c} % p{} for text col, c for data cols ... \end{tabular}} \begin{tablenotes}[flushleft]\small \item \textit{Notes}: ... \end{tablenotes} \end{threeparttable} \end{table} \end{landscape} ``` **Quick reference for portrait mode** (1.25in margins, ~16.5cm text width): | Columns | First column | Approach | |---------|-------------|----------| | 3-4 | `l` | Portrait, no special treatment needed | | 5-6 | `p{4.5cm}` + `{\footnotesize\setlength{\tabcolsep}{4pt}}` | Portrait, tight | | 7+ | `p{Xcm}` + `\footnotesize` | Landscape always | Keep `\begin{tablenotes}` text concise — a long inline math expression that cannot line-break (e.g., a full regression formula) will produce an `Overfull \hbox` even when the table itself fits. Summarize the spec in plain language in the note and put the equation in the methods section instead.