Skip to main content
Author Profile

Chokkhu

A Professional Statistical EDA Toolkit for Computer Vision & Tabular Datasets

PyPI version Python versions License Build Status Format Status

Industry-grade data analysis and visual reports generation.


Overview

Chokkhu is a high-performance Python package designed to streamline Exploratory Data Analysis (EDA).

Designed to be incredibly lightweight without relying on massive machine learning frameworks (No TensorFlow, PyTorch, or Scikit-Learn dependencies), it perfectly generates unified, modular statistical reports.


Installation

Install Chokkhu via pip.

pip install chokkhu

Quick Start: Exploratory Data Analysis (EDA)

Chokkhu provides a unified, clean API for generating EDA reports.

1. Tabular EDA

Generate a comprehensive suite of statistical charts (Univariate, Bivariate, Multivariate, Outliers) to understand your CSV datasets in one simple call:

import chokkhu as ck

csv_dataset_path = '/kaggle/input/datasets/laveshjadon/ai-impact-on-students/ai_student_impact_dataset (1).csv'

tabular_eda = ck.eda.tabular(
    dataset_path=csv_dataset_path, 
    save_reports=True, 
    save_dir='/kaggle/working/tabular_reports',
    target_col='Pre_Semester_GPA'
)

Parameters:

  • dataset_path (str): Path to your CSV file.
  • save_reports (bool): Whether to save the plots to the disk.
  • save_dir (str): Directory where reports will be saved automatically.
  • target_col (str, optional): If provided, Chokkhu performs target-based analysis.

2. Image EDA

Analyze image data quality, structural integrity, spatial textures, and color profiles for your datasets. Each topic metric is plotted cleanly and saved directly.

import chokkhu as ck

image_dataset_path = '/kaggle/input/datasets/nirmalsankalana/sugarcane-leaf-disease-dataset'

image_eda = ck.eda.image(
    dataset_path=image_dataset_path, 
    save_reports=True, 
    save_dir='/kaggle/working/image_reports'
)

Parameters:

  • dataset_path (str): Path to the root folder of your image dataset.
  • save_reports (bool): Whether to save the plots to the disk.
  • save_dir (str): Directory where all EDA reports will be saved automatically.

Contributing

We welcome contributions! Please check out the Issues page if you'd like to help improve Chokkhu.

License

Distributed under the MIT License. See LICENSE for more information.

Metadata

Release files for chokkhu 0.3.35

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for chokkhu 0.3.35
File Size Uploaded
chokkhu-0.3.35.tar.gz 39.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for chokkhu 0.3.35
File Interpreter ABI Platform
chokkhu-0.3.35-py3-none-any.whl Python 3 none any Details

Total release size: 88.9 kB

Release files / chokkhu-0.3.35.tar.gz

Download URL chokkhu-0.3.35.tar.gz
Size 39.1 kB
Tags Source
SHA-256 checksum
How to use checksums
3e1bac5f39c60eb4e19d42fb4819aeda98b1dac5597ff0f44f98d03c7996a587
BLAKE2b-256 checksum
How to use checksums
c5f8d31328b84b174b486f2fcd834d109d6dd85a72de7f0742064d614f32255e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.14

Release files / chokkhu-0.3.35-py3-none-any.whl

Download URL chokkhu-0.3.35-py3-none-any.whl
Size 49.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
46f614308d3a526cdb3544d24ff916f73fa03f88643b2988d4e64618034940fc
BLAKE2b-256 checksum
How to use checksums
feaccd71ef08c6ed06c7a2ab3026a67d710a240021e7022ec34bbe29c318820d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.13.14

Release history Release notifications | RSS feed

1.6.0

2 release files

1.5.21

2 release files

1.5.20

2 release files

1.5.19

2 release files

1.5.18

2 release files

1.5.17

2 release files

1.5.16

2 release files

1.5.15

2 release files

1.5.14

2 release files

1.5.13

2 release files

1.5.12

2 release files

1.5.11

2 release files

1.5.10

2 release files

1.5.9

2 release files

1.5.8

2 release files

1.5.7

2 release files

1.5.6

2 release files

1.5.5

2 release files

1.5.4

2 release files

1.5.3

2 release files

1.5.2

2 release files

1.5.1

2 release files

1.5.0

2 release files

1.4.0

2 release files

1.3.0

2 release files

1.2.0

2 release files

1.1.0

2 release files

1.0.1

2 release files

1.0.0

2 release files

0.9.2

2 release files

0.9.1

2 release files

0.9.0

2 release files

0.8.0

2 release files

0.7.3

2 release files

0.7.2

2 release files

0.7.1

2 release files

0.7.0

2 release files

0.6.7

2 release files

0.5.2

2 release files

0.3.42

2 release files

0.3.41

2 release files

0.3.40

2 release files

0.3.39

2 release files

0.3.38

2 release files

0.3.37

2 release files

0.3.36

2 release files

This release

0.3.35 This release

2 release files

0.3.34

2 release files

0.3.33

2 release files

0.3.32

2 release files

0.3.31

2 release files

0.3.30

2 release files

0.3.29

2 release files

0.3.28

2 release files

0.3.27

2 release files

0.3.26

2 release files

0.3.9

2 release files

0.3.8

2 release files

0.3.7

2 release files

0.3.6

2 release files

0.3.5

2 release files

0.3.4

2 release files

0.3.3

2 release files

0.3.2

2 release files

0.3.1

2 release files

0.3.0

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.6

2 release files

0.1.5

2 release files

0.1.4

2 release files

0.1.3

2 release files

0.1.2

2 release files

0.1.1

2 release files

0.1.0

2 release files

0.0.8

2 release files

0.0.6

2 release files

0.0.5

2 release files

0.0.4

2 release files

0.0.3

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page