baribal 0.2.1

Helper functions for pandas data analysis, inspired by R

baribal 🐻

A Python package extending pandas and polars with helper functions for simpler exploratory data analysis and data wrangling, inspired by R's tidyverse packages.

Why Baribal?

While pandas and polars are incredibly powerful, some R functions like glimpse(), tabyl(), or clean_names() make data exploration and manipulation particularly smooth. Baribal brings these functionalities to Python, helping you to:

• Get quick, insightful overviews of your DataFrames
• Perform common data cleaning tasks with less code
• Handle missing values more intuitively
• Generate summary statistics with minimal effort
• Optimize memory usage with smart type inference

Features

Core Functions

🔍 glimpse()

R-style enhanced DataFrame preview that works with both pandas and polars:

import pandas as pd
import baribal as bb

df = pd.DataFrame({
    'id': range(1, 6),
    'name': ['John Doe', 'Jane Smith', 'Bob Wilson', 'Alice Brown', 'Charlie Davis'],
    'age': [25, 30, 35, 28, 42],
    'score': [92.5, 88.0, None, 95.5, 90.0]
})

bb.glimpse(df)

Output:

Observations: 5
Variables: 4
DataFrame type: pandas
$ id    <int> 1, 2, 3, 4, 5
$ name  <chr> "John Doe", "Jane Smith", "Bob Wilson", "Alice Brown", "Charlie Davis"
$ age   <int> 25, 30, 35, 28, 42
$ score <num> 92.5, 88.0, NA, 95.5, 90.0

📊 tabyl()

Enhanced cross-tabulations with integrated statistics:

import baribal as bb

# Single variable frequency table
result, _ = bb.tabyl(df, 'category')

# Two-way cross-tabulation with chi-square statistics
result, stats = bb.tabyl(df, 'category', 'status')

Data Cleaning

🧹 clean_names()

Smart column name cleaning with multiple case styles:

import baribal as bb

df = pd.DataFrame({
    "First Name": [],
    "Last.Name": [],
    "Email@Address": [],
    "Phone #": []
})

# Snake case (default)
bb.clean_names(df)
# → columns become: ['first_name', 'last_name', 'email_address', 'phone']

# Camel case
bb.clean_names(df, case='camel')
# → columns become: ['firstName', 'lastName', 'emailAddress', 'phone']

# Pascal case
bb.clean_names(df, case='pascal')
# → columns become: ['FirstName', 'LastName', 'EmailAddress', 'Phone']

🔄 rename_all()

Batch rename columns using patterns:

import baribal as bb

# Using regex pattern
bb.rename_all(df, r'Col_(\d+)')  # Extracts numbers from column names

# Using case transformation
bb.rename_all(df, lambda x: x.lower())  # Convert all to lowercase

Analysis Tools

🔍 missing_summary()

Comprehensive missing values analysis:

import baribal as bb

summary = bb.missing_summary(df)
# Returns DataFrame with missing value statistics for each column

Installation

pip install baribal

Dependencies

• Python >= 3.8
• pandas >= 1.0.0
• polars >= 0.20.0 (optional)
• numpy
• scipy

Development

This project uses modern Python development tools:

• uv for fast, reliable package management
• ruff for lightning-fast linting and formatting
• pytest for testing

To set up the development environment:

make install

To run tests:

make test

Contributing

Contributions are welcome! Whether it's:

• Suggesting new R-inspired features
• Improving documentation
• Adding test cases
• Reporting bugs

Please check out our Contributing Guidelines for details on our git commit conventions and development process.

License

MIT License

Acknowledgments

Inspired by various R packages including:

• dplyr
• janitor
• tibble
• naniar