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NCES_Data_Set

Comprehensive Analysis of US Tech & Vocational Education Funding (2010-2020)

Project Status: Advanced Stages of Analysis

Project Overview

This repository encapsulates an in-depth analysis of a decade's worth of US technical and vocational education funding data, sourced from the National Center for Education Statistics' Local Education Agency (LEA) Finance Survey. It demonstrates a sophisticated data analysis workflow, from crafting a PostgreSQL database to creating nuanced visualizations that render complex data into intelligible insights.

Repository Contents

  • src/: Jupyter Notebooks detailing the analytical pipeline with Python scripts for data processing and visualization.
  • PDF Documentation/: In-depth dataset documentation from NCES and an Entity-Relationship Diagram (ERD) outlining the database architecture.
  • SQL Queries/: SQL scripts crafted for precise data extraction and rigorous analysis.
  • Local Education Agency Finance Survey – School District Data ERD.pdf: Detailed ERD visualizing the relational database design.

Features

  • A meticulously designed PostgreSQL database ensuring efficient data handling.
  • Comprehensive Python-based data cleansing, ETL processes, and normalization techniques.
  • Interactive, Plotly-based visualizations that highlight trends and funding trajectories in an engaging manner.
  • Statistical analysis techniques applied to draw out patterns, growth rates, and significant fluctuations in funding streams.

Interactive Notebooks

Experience the project's data visualizations interactively through Binder-hosted Jupyter Notebooks. Click the corresponding Binder badges to launch a virtual instance where you can run and interact with the notebooks directly from your browser, no local setup required.

National Level Analysis:
Binder

Regional Level Analysis:
Binder

Please Note: Binder may take a few moments to prepare the environment. I appreciate your patience. Upon loading, execute the notebook by selecting "Restart Kernel and Run All Cells" to see the analysis in action.

Interactive Tableau Dashboard:
Explore the disparities in tech and vocational educational expenses from 2010 to 2020 through this Tableau Public Dashboard.

Setup

To delve into this analysis:

  1. Clone the repository to your local machine.
  2. Install the necessary libraries as specified in requirements.txt.
  3. Navigate through the Jupyter Notebooks for a step-by-step breakdown of the analyses.
  4. Refer to the PDF documentation for a deeper understanding of the dataset nuances.
  5. Review the ERD to comprehend the database schema.

Key Insights

A noteworthy finding is the substantial 114.38% increase in the cost per student between 2014 and 2016, largely attributable to the introduction of new expenditure categories. The analysis also discerns a significant growth in teacher salaries for vocational education, marked by a 7.35% upswing in 2020.

Acknowledgments

  • Data: Sourced from the National Center for Education Statistics (NCES).
  • Tools: Utilized Python, Jupyter, Plotly, PostgreSQL, among other open-source software.