Geospatial-Data-Analysis-in-Python

This repository contains a Jupyter notebook focused on geospatial data analysis using Python. It covers the installation of necessary dependencies, data manipulation, visualization, and analysis techniques commonly used in geospatial projects.

Table of Contents

• Introduction
• Installation
• Usage
• Features
• License

Introduction

Geospatial data analysis is an essential aspect of understanding spatial patterns and relationships in various domains. This notebook provides a step-by-step guide to performing geospatial analysis in Python, leveraging powerful libraries like GeoPandas, Shapely, and Folium.

Installation

To run this notebook, you have to just clone it. You can do this by running the following command:

git clone https://github.com/cizodevahm/Geospatial-Data-Analysis-in-Python.git

Ensure you have Jupyter installed, and then launch the notebook using:

jupyter notebook

Usage

Clone this repository and open the Geospatial Data Analysis in Python.ipynb notebook in Jupyter. The notebook includes the following sections:

• Data Loading: Instructions on loading geospatial datasets.
• Data Manipulation: Techniques for manipulating geospatial data using Python.
• Visualization: Visualization of spatial data using various plotting libraries.
• Analysis: Performing spatial analysis, including spatial joins and aggregations.

Features

• Loading and exploring geospatial datasets
• Manipulating spatial data using GeoPandas
• Visualizing spatial data with Folium and Matplotlib
• Conducting spatial analysis, including spatial joins and aggregations

Example

License

This project is licensed under the GPL-3.0 license - see the LICENSE file for details.