School Data Cleaning for Google Looker Studio Dashboard

This repository contains two Jupyter notebooks aimed at cleaning and visualizing school data for integration into a Google Looker Studio Dashboard. The data used in these notebooks are sourced from various platforms including Education Data Explorer, Civil Rights Data, and the U.S. Department of Education

Google Looker Studio Dashboard

The dashboard is accessible via the following link: Dashboard Link

Notebooks

1. Notebook clean_data.ipynb: Data Cleaning: This notebook focuses on cleaning and preprocessing the raw school data obtained from the Education Data Explorer, Civil Rights Data, and the U.S. Department of Education. It includes steps for handling missing values, data transformations, and merging datasets.

2. Notebook 2: Data Visualization. The second notebook is dedicated to testing various types of graphs using Seaborn and Matplotlib libraries. It serves as a visualization playground where different graphs and visualizations can be experimented with before integration into the Google Looker Studio Dashboard.

Usage

To use the notebooks:

1. Clone the repository to your local machine.
2. Install Jupyter Notebook or JupyterLab.
3. Open the notebooks using Jupyter Notebook or JupyterLab.
4. Follow the instructions within each notebook to execute the respective tasks.

Data Sources

The data used in these notebooks are sourced from the following platforms:

• Education Data Explorer,
• Civil Rights Data
• U.S. Department of Education

Dependencies

The notebooks require the following Python libraries:

• Pandas
• NumPy
• Matplotlib
• Seaborn

These dependencies can be installed using pip:

pip install pandas numpy matplotlib seaborn

License

This project is licensed under the MIT License.