Analyzing NYC High School Data
- Guided Project
- 0.9 hours
- Beginner
- Python
Practice analyzing NYC high school data using Python, pandas, and Matplotlib to uncover insights and build data science skills.
Overview
In this project, you'll take on the role of a data scientist to analyze relationships between student demographics and SAT scores at New York City public schools. Using Python, pandas, and Matplotlib, you'll examine correlations between factors like race, gender, and socioeconomic status to determine if the SAT is a fair assessment.
This project provides hands-on experience in data analysis and visualization, allowing you to apply your skills to a real-world dataset. You'll clean and combine multiple datasets, create informative plots, and draw meaningful conclusions. If you're new to Jupyter Notebook, consider taking our Jupyter Notebook Guided Project first.
Objective: Use data analysis to uncover insights into SAT score demographic trends and evaluate the fairness of the SAT as a college admissions test.
What You'll Learn
- ✓ How to combine and clean multiple datasets to create a comprehensive analysis
- ✓ How to identify and visualize correlations between different variables
- ✓ How to analyze demographic factors like race, gender, and socioeconomic status in relation to test scores
- ✓ How to draw meaningful insights from data visualizations
- ✓ How to organize an exploratory data analysis workflow in Python
Before You Start
- ✓ Cleaning and preparing data using the pandas library
- ✓ Combining datasets using joins in pandas
- ✓ Computing summary statistics and correlations to analyze data
- ✓ Visualizing data using matplotlib to generate plots
Project Steps
6 steps
- 1 Introduction
- 2 Exploring Safety and SAT Scores
- 3 Exploring Race and SAT Scores
- 4 Exploring Gender and SAT Scores
- 5 Exploring AP Scores vs. SAT Scores
- 6 Next Steps
Join 1M+ data learners on Dataquest.
- 1
Create a free account
- 2
Choose a learning path
- 3
Complete exercises and projects
- 4
Advance your career