README.md

metadata

license: mit
task_categories:
  - text-classification
language:
  - en
size_categories:
  - 1K<n<10K

📦 Water Potability Dataset

A curated dataset of water quality measurements labeled for potability.
This dataset is ideal for building and testing water quality prediction models using Machine Learning or Deep Learning.

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🧠 Overview

• File Name: water_potability.csv
• Total Entries: 3,200+ water samples
• Format: CSV (Comma Separated Values)
• Columns:
  • Potability → Indicates whether the water is potable (1) or not potable (0)
  • pH → Water pH value
  • Hardness → Hardness of water (mg/L)
  • Solids → Total dissolved solids (ppm)
  • Chloramines → Chloramines concentration (ppm)
  • Sulfate → Sulfate content (mg/L)
  • Conductivity → Electrical conductivity (µS/cm)
  • Organic_carbon → Organic carbon content (ppm)
  • Trihalomethanes → Trihalomethanes concentration (µg/L)
  • Turbidity → Turbidity level (NTU)

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📊 Dataset Features

Feature	Description
Potability	Binary label: 1 for potable, 0 for non-potable
Water Quality Metrics	Real-world measurements of water properties
Cleaned Data	Pre-processed and structured for ML usage
Balanced Data	Contains a mix of potable and non-potable samples

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⚙️ Use Cases

• Water quality prediction using ML or DL models
• Regression and classification problems
• Feature analysis and correlation studies
• Experimenting with model accuracy, precision, and F1-scores

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📁 File Structure

• Dataset —> water_potability.csv

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🧩 Example Rows

Potability	pH	Hardness	Solids	Chloramines	Sulfate	Conductivity	Organic_carbon	Trihalomethanes	Turbidity
1	7.2	204	21200	7.0	333	420	10	80	3.5
0	6.8	180	18900	5.5	295	390	8	65	4.2

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📜 License (MIT)

This dataset is provided for educational and research purposes only.

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🙌 Author

Gaurav Pandey (Mr. Def@ult)
Co-founder of DarkNeuronAI
📧 darkneuronai.official@gmail.com

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Developed With ❤️ By DarkNeuronAI