Kineret Dataset Exploration and Analysis Project Title Impact of Rainfall on the Kinneret's Water Quality and Level
Description:
This project delves into the exploration and analysis of the Kineret (Sea of Galilee) dataset. The primary focus is to understand the relationship between the annual rainfall, the Kinneret's water level, and its chloride concentration. Through a series of visualizations and statistical analyses, the project aims to shed light on how environmental factors influence the lake's health and water reserve.
Key Features:
Data Cleaning and Preprocessing: The raw dataset underwent a series of cleaning and transformation processes to ensure accuracy in the subsequent analyses.
Exploratory Data Analysis (EDA): Comprehensive exploration of individual variables and their interrelationships.
Visualizations: A variety of plots, including scatter plots, line graphs, histograms, and 3D visualizations, were used to visually represent and interpret the data's patterns and correlations.
Statistical Analysis: Regression analyses were performed to understand and quantify the relationships between the key variables.
Conclusions:
The analysis revealed a significant correlation between the annual rainfall and the Kinneret's water level. Years with higher rainfall typically resulted in a rise in the Kinneret's water level. Additionally, the chloride concentration in the water, an indicator of water quality, also showed variations based on environmental factors. The insights from this project can be instrumental in water resource management and environmental conservation efforts related to the Kinneret.
Tools and Libraries Used: Python Pandas Numpy Seaborn Matplotlib Jupyter Notebook
How to Run the Project Clone the repository to your local machine. Ensure you have the required libraries installed. Open the Kineret dataset exploration.ipynb file in Jupyter Notebook. Run the cells in sequence to view the analysis and visualizations. Author Dor Josef