This project is an exploration and analysis of the Students dataset using data science techniques. It includes data visualization, preprocessing, and various insights derived from the dataset. The code is written in Python and uses popular libraries such as NumPy, Pandas, Matplotlib, and Seaborn.

The project contains the following files:

• hello_world.ipynb: Jupyter Notebook containing the code for the project.
• the-hello-dataset-fa22: Dataset containing students information.
• cleanedHelloWorldData.csv: Cleaned dataset obtained after preprocessing.
• graphs_hello/: Directory containing the generated graphs and visualizations.

To run this project locally, you need to have the following prerequisites installed:

• Python 3
• Jupyter Notebook
• Required Python libraries: NumPy, Pandas, Matplotlib, Seaborn

To set up the project environment, follow these steps:

1. Clone the repository:

git clone https://github.com/yalmaz-ali/Data-Analytics.git

2. Navigate to the project directory:

cd Data-Analytics

3. Usage:

• Launch Jupyter Notebook:

jupyter notebook

• Open the Data_Analytic.ipynb notebook in Jupyter Notebook.
• Run the notebook cells to execute the code step-by-step.
• The generated visualizations can be found in the graphs_hello/ directory.

Acknowledgments

• The hello_world dataset used in this project is not to be used without permission.