qualiframe 0.1.1

# QualiFrame

**QualiFrame** is a Python package for automated **data-quality auditing and exploratory data analysis**.

It analyzes a Pandas DataFrame and generates a structured PDF report containing key data-quality insights, statistics, visualizations, and recommendations.

## Features

* Dataset summary

* Automatic datatype detection

* Missing-value analysis

* Empty and constant column detection

* Duplicate-row analysis

* Descriptive statistics

* Correlation analysis

* Automated data-quality recommendations

* Professional PDF report generation

## Installation

Install QualiFrame directly from PyPI:

pip install qualiframe

## Usage

from qualiframe import audit



audit(data.csv)

QualiFrame analyzes the dataset and generates a PDF audit report.

## What the Report Provides

The generated report includes:

* Dataset overview

* Column-level information

* Missing-data analysis

* Duplicate analysis

* Statistical summary

* Correlation visualization

* Data-quality recommendations

## Example Workflow

CSV / Pandas DataFrame

        │

        ▼

    QualiFrame

        │

        ├── Data Quality Analysis

        ├── Statistics

        ├── Correlation Analysis

        └── Recommendations

        │

        ▼

    PDF Audit Report

## Requirements

* Python 3.10+

* pandas

* matplotlib

* seaborn

* reportlab

## Intended Use

QualiFrame can be used for:

* Data-quality screening

* Exploratory data analysis

* Research datasets

* Sensor and environmental datasets

* Time-series datasets

* Machine-learning preprocessing

## Note

QualiFrame is a **screening and reporting tool**. Its recommendations should be reviewed before making changes to the original dataset.

## Version

**0.1.0**

## Author

**Heshva**

[Github](https://github.com/Heshva)

**QualiFrame — Automated Data Quality Auditing for Python**