NYC Schools Perceptions
- Guided Project
- 0.4 hours
- Intermediate
- R
Practice using R Notebooks to clean, reshape and visualize survey data to analyze perceptions of NYC schools.
Overview
In this project, you'll take on the role of a data analyst tasked with exploring perceptions of school quality in New York City. Using a real-world dataset of survey responses from parents, teachers, and students, you'll apply your skills in data cleaning, reshaping, visualization, and correlation analysis using R Notebooks.
By working hands-on with a large, complex dataset, you'll showcase your ability to extract meaningful insights from raw data - a highly valued skill in data analytics roles. You'll enhance your data wrangling and exploration skills while building an impressive project for your portfolio.
Objective: Analyze survey data to uncover insights into parent, teacher, and student perceptions of NYC school quality.
What You'll Learn
- ✓ Employ R Notebooks to showcase your work
- ✓ Reshape a large survey dataset
- ✓ Interpret metadata to inform your data cleaning
- ✓ Explore perceptions of NYC schools using data visualization and correlation
Before You Start
- ✓ Manipulating DataFrames in R, including modifying variables and observations
- ✓ Defining and combining relational data using joins
- ✓ Resolving missing data through omission and imputation techniques
- ✓ Reshaping data between wide and long formats using tidyr
Project Steps
7 steps
- 1 Cleaning and Analyzing Data: Show Off Your Skills and Start Building a Portfolio
- 2 New York City Schools Survey Data
- 3 Simplifying the Dataframes
- 4 Creating a Single Dataframe for Analysis
- 5 Look for Interesting Correlations and Examine Relationships Using Scatter Plots
- 6 Differences in Student, Parent, and Teacher Perceptions: Reshape the Data
- 7 Next Steps
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