TidyPeek

TidyPeek is a lightweight CLI tool for quick CSV sanity checks.

It helps you inspect a dataset's structure, missing values, duplicates, likely identifier columns, and basic actionable insights - all from the terminal.

Features

• View total rows and columns
• Inspect column names and data types
• Check missing values per column
• Detect exact duplicate rows
• Detect likely identifier columns
• Check duplicate values in likely ID Columns
• Check duplicate email values in email-like columns
• Generate simple insights based on data quality issues

Installation

pip install tidypeek

🚀 Usage

Run with FilePath

tidypeek path/to/file.csv

Example:

tidypeek "/home/user/Datasets/UFC Fighters/UFCFighters.csv"

Run without a file path:

tidypeek

⚠️ Note

If your filepath consists of spaces, wrap it up in quotes:

tidypeek "/path/to/My Dataset/data.csv"

🧠 What it does

TidyPeek performs a quick analysis of your dataset and highlights:

• Missing values
• Duplicate rows
• Potential identifier columns
• Data inconsistencies

It then generates simple insights to help guide cleaning and analysis.

📊 Example Output

=== GENERAL CHECKS ===
Total Columns: 18
Total Rows: 4111

=== IDENTIFIER CHECKS ===
Likely ID columns:
 - name (Uniqueness: 99.85%, Missing: 0.00%)

Duplicate ID counts:
 - name: 6 duplicates

=== INSIGHTS ===
1. 4 columns have high missing values
2. 12 columns have low uniqueness
3. Column 'name' likely acts as an identifier but has duplicates

🎯 Use Cases

• Quick dataset inspection
• Data cleaning workflows
• Learning data analysis basics
• Pre-analysis sanity checks

📌 Current Scope

tidypeek focuses on lightweight inspection, not full data cleaning or transformation.

🤝 Contributing

Feel free to fork the repo and open a pull request.

📄 License MIT