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📊 Exporting Pandas DataFrames to LaTeX with Style

This project demonstrates how to export pandas.DataFrame objects to LaTeX format with styling, captions, labels, and formatting. It's perfect for generating publication-quality tables for scientific papers, reports, or documentation.

🛠️ Requirements

pip install pandas

A LaTeX distribution (like TeX Live or MikTeX) is required to compile .tex files into PDFs.

📁 Loading the Data

Make sure your CSV files are available in your working directory:

import pandas as pd

df_employee_data = pd.read_csv('employee_data.csv')
df_experiment_data = pd.read_csv('experiment_data.csv')
df_large_table_1 = pd.read_csv('large_table_1.csv')
df_large_table_2 = pd.read_csv('large_table_2.csv')

📄 Exporting a Basic LaTeX Table

from your_module import save_latex_table

save_latex_table(
    df_employee_data,
    filename="table.tex",
    float_format="%.2f",
    caption="Employee Data",
    label="tab:employee_data",
    center=True
)

🎨 Highlighting Specific Values in LaTeX

Apply custom formatting:

def highlight_high_values(val):
    return "\\textbf{" + str(val) + "}" if val > 90 else str(val)

df_styled = df_experiment_data.style.format({
    "Temperature (°C)": highlight_high_values,
    "Success Rate ($\\%$)": highlight_high_values
})

Save styled table:

from your_module import save_latex_table_styled

save_latex_table_styled(
    df_styled,
    filename="styled_table.tex",
    caption="Styled table with bolded values",
    label="tab:styled"
)

📑 Creating Multi-Column Tables

df_employee = pd.DataFrame({
    "ID": [101, 102, 103],
    "Name": ["Alice", "Bob", "Charlie"],
    "Department": ["HR", "IT", "Finance"],
    "Joining Date": ["2020-01-10", "2019-07-23", "2021-06-15"]
})

df_employee.columns = pd.MultiIndex.from_tuples([
    ("Employee Info", "ID"),
    ("Employee Info", "Name"),
    ("Work Details", "Department"),
    ("Work Details", "Joining Date"),
])

save_latex_table(
    df_employee,
    filename="employee_table.tex",
    caption="Employee Details",
    label="tab:employee"
)

🔬 Controlling Float Precision

print(df_experiment_data.to_latex(float_format="%.1f"))

save_latex_table(
    df_experiment_data,
    filename="precision_table1.tex",
    float_format="%.4f",
    caption="Scientific Notation Example",
    label="tab:precision_table1"
)

save_latex_table(
    df_large_table_1,
    filename="precision_table2.tex",
    float_format="%.3f",
    caption="Presentation of employee data.",
    label="tab:data_emp"
)

🚀 Command Line Interface (CLI)

You can also export tables using the command line!

▶️ Usage

python export_table_cli.py \
  --input employee_data.csv \
  --output employee_table.tex \
  --caption "Employee Overview" \
  --label tab:employee \
  --float_format "%.2f" \
  --center \
  --position h!

🔧 CLI Options

Option Description Required Default
--input Path to the input CSV file ✅ —
--output Output .tex filename ❌ table.tex
--caption Table caption ❌ "Table Caption"
--label LaTeX reference label ❌ tab:label
--float_format Format for float numbers ❌ "%.2f"
--center Add \\centering for table alignment ❌ False
--position Float position (e.g., h!, t, b, etc.) ❌ "h!"

📂 File Output

All exports will generate:

  • A standalone .tex file (compilable with LaTeX)
  • Includes required packages (booktabs, longtable, graphicx, adjustbox)
  • Centered tables with optional float formatting

To compile:

pdflatex table.tex

✨ Advanced Ideas to Extend

  • Add support for longtables
  • Wrap wide tables using adjustbox
  • Auto-compile to PDF or image format
  • Combine multiple tables into one report
  • Highlight using Styler.applymap() or highlight_max()
  • Create a Python package (pip install latex-table-exporter)

📚 License

MIT License — Free to use, modify, and distribute.

Let me know if you'd like the CLI script bundled in a module with installable CLI support via setup.py or pyproject.toml.