The project was completed as a part of UTSA Data Analytics and Visualization Program.
I was given the following prompt:
"You are the new Chief Data Scientist for your city's school district. In this capacity, you'll be helping the school board and mayor make strategic decisions regarding future school budgets and priorities. As a first task, you've been asked to analyze the district-wide standardized test results. You'll be given access to every student's math and reading scores, as well as various information on the schools they attend. Your task is to aggregate the data to showcase obvious trends in school performance."
Additionally, I was provided:
- A dataset of students scores in their standardized test in mathematics and reading, and
- Starter code for a report on the school district's standardized test scores and budgeting.
This responsitory contains the following files:
- README.md = That's this file! It's an overview of the respository.
- Support Documentation folder = This folder contains pdfs of websites and other support documentation used to create the code. Also included are instructions for the project.
- PyCitySchools folder = This folder contains the documents for the project.
- Example Template.ipynb = This template was provided for the project and serves as a baseline for the formatting of the project.
- Responses in Template.ipynb= The template above was used to create this version of the code. Troubleshooting was completed in this document.
- PyCitySchools.ipynb = This file presents the findings of the project in a report fashion. Code from the 'Responses in Template.ipynb' file was copied to the document and re-run.
- Resources folder = This folder contains two csv files.
- schools_complete.csv = contains each school's name, budget, type (Charter School or District School), size (student enrollment), and a unique ID.
- students_complete.csv = contains each student's name, grade level, gender, school name, reading score, math score, and a unique ID.
In the report that I have created, I will personify the Chief Data Scientist role and present that information in a report-style (in contrast to the cell-by-cell format for each calculation in the template).