H2O Filter Analysis

Overview

H2O Filter Analysis is my internship project that focuses on analyzing water constituent data to provide filtration advice based on government guidelines. This application takes input data about water quality, processes it through statistical analysis using Python and its libraries, and outputs recommendations on the filtration frequency and methods. The project integrates data science techniques with environmental science knowledge, ensuring decisions are informed, data-driven, and aligned with health and safety standards.

Features

• Data analysis based on input water constituent data for statistical analysis and decision-making.
• Reads in filtered datasets for trend analysis.
• Outputs data for assessing and proposing actions based on stats and counts.

Technologies Used

This project is built using Python and various libraries:

• Pandas for data manipulation
• Seaborn and Matplotlib for data visualization
• Lifelines for survival analysis
• PymannKendall for trend analysis

Installation

Before running the project, ensure you have the following packages installed:

• pandas
• seaborn
• matplotlib
• numpy
• lifelines
• pymannkendall
• openpyxl

You can install these packages using pip:

pip install pandas seaborn matplotlib numpy lifelines pymannkendall openpyxl

Usage

To run the H2O Filter Analysis project:

1. Navigate to the scripts directory.
2. Run the Complete_Script file, which orchestrates the data analysis and filtration advice process: bash python Complete_Script.py

Built With

• python