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Anushka-Sinh / repository
This an ETL analysis project on Ganga water quality. Data is extract, store and tranform in Jupyter notebook in python and loaded into Microsoft SQL Server management studio for SQL queries
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🌊 Ganga Water Quality ETL Project
📋 Overview
This project creats an ETL pipeline water quality data to evaluate Ganga's water body in different state on India safety and environmental health. The project includes data collection, preprocessing, statistical analysis, and visualizations to help monitor and assess water quality parameters like pH, FC, dissolved oxygen, etc.
The system enables scientists, environmentalists, and the public to easily visualize and analyze trends in water quality.
🧪 Features
Data Exract: Easily load data from CSV and XML source. Data Transformation: Clean and normalize datasets (handle missing values, standardize units). Statistical Analysis: Calculate key metrics like mean, median, and standard deviation for each water quality parameter. Water Quality Indicators: Assess water quality against standard thresholds (pH, turbidity, dissolved oxygen).
Interactive Visualizations: Plot trends using various visual libraries (e.g., Matplotlib, Seaborn) to visualize water quality across different locations and time frames.
Data Loading: Exporting the data into Microsoft SQL Server Management System
🚀 Technologies Used
Python: Pandas,NumPy,Matplotlib/Seaborn
Jupyter Notebook: For creating and sharing code, visualizations, and reports.
Exract CSV and XML file using (xml.etree) import xml.etree.ElementTree as ET
Analysis of Data
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