This project is a part of the Data Science and Business Analytics Internship at Sparks Foundation. The objective of this project is to perform Exploratory Data Analysis on the Global Terrorism dataset.
As a security/defense analyst, the goal is to analyze the dataset and derive insights regarding terrorism incidents worldwide. The main objectives of this EDA project are:
Identify hot zones of terrorism: Analyze the dataset to identify regions or countries with a high frequency of terrorism incidents. Explore security issues: Identify patterns and trends in the data that can provide insights into security issues related to terrorism. Perform data visualization: Utilize libraries such as Matplotlib and Seaborn to create visualizations that effectively communicate the findings. Dataset
The dataset used for this project is the Global Terrorism Database (GTD), which contains information on terrorist attacks worldwide. The dataset can be accessed from the following link: Dataset: Global Terrorism Dataset
The following tools and libraries were used in this project:
Jupyter Notebook: Integrated development environment used for coding and data analysis.
Python: Programming language used for data manipulation and analysis.
Numpy: Library for numerical computing in Python.
Pandas: Library for data manipulation and analysis. Matplotlib: Library for creating static, animated, and interactive visualizations.
Seaborn: Library based on Matplotlib, providing additional visualization capabilities.
global_terrorism_eda.ipynb: Jupyter Notebook containing the code for data loading, cleaning, exploratory data analysis, and visualization.
globalterrorismdb_0718dist.csv: CSV file containing the Global Terrorism Database.
README.md: Markdown file providing an overview of the project and instructions for running the code.
Download the 'globalterrorismdb_0718dist.csv' dataset from the provided link and place it in the same directory as the Jupyter Notebook.
Install the necessary libraries (NumPy, Pandas, Matplotlib, Seaborn) if not already installed.
Open the Jupyter Notebook (global_terrorism_eda.ipynb) using Jupyter Notebook or any other compatible environment.
Run the code cells in the notebook sequentially to perform the data analysis and generate the visualizations.
Please note that the code and the dataset provided are for educational purposes and should not be used for any other purposes without appropriate permissions.
Through this Exploratory Data Analysis project on the Global Terrorism dataset, you will gain insights into hot zones of terrorism and discover security issues related to terrorism incidents worldwide. The visualizations created in the project will help in understanding the patterns and trends in terrorism data.
For any questions or suggestions, please feel free to reach out.
Happy exploring and analyzing the data!