ML-data-profile 0.1.4.2

Data profiling utilities

data_profile

data_profile is a lightweight Python utility for quickly profiling tabular datasets (Pandas DataFrames).
It helps you understand basic data quality and structure by summarising:

• Column names
• Data types
• Null (missing) counts
• Null percentages
• Number of unique values
• Sample of unique values

This is especially useful in EDA (Exploratory Data Analysis) and data quality checks before modelling.

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🚀 Features

• Simple DataReader class that wraps a pandas.DataFrame
• One-call data_summary() method to generate a clean summary table
• Custom exception handling via CustomPacakgeException
• Logging support via logging from data_profile.logging.logger

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📦 Installation

Notebook

!pip install ML-data-profile

🧩 Usage

1️⃣ Import and prepare your data

import pandas as pd
import data_profile
from data_profile import DataReader


# Example DataFrame
df = pd.DataFrame({
    "age": [25, 30, 35, None],
    "gender": ["M", "F", "M", "F"],
    "income": [50000, 60000, None, 80000]
})

#Initialize DataReader
data_reader = DataReader(df)

#Generate summary
summary = data_reader.data_summary()
summary