Correlations and Reshaping Data

Continue learning techniques for such as reshaping data for data cleaning and analysis as you work with real-world data.


  • Learn about tidyverse tools for reshaping data.
  • Use correlation analysis to understand relationships between variables.
  • Create correlation matrices to identify trends in your data.

Mission Outline

1. Analyzing New York City Public Schools Data
2. Visualizing Relationships Between Variables Using Scatter Plots
3. Reshaping Data for Visualization
4. Gathering Data into Columns
5. Comparing the Strength of Relationships Among Pairs of Variables
6. Correlation Analysis: Measuring the Strength of Relationships Between Variables
7. Creating and Interpreting Correlation Matrices
8. Identifying Interesting Relationships
9. Next Steps
10. Takeaways


Course Info:

Data Cleaning in R


The average completion time for this course is 10-hours.

This course is free. This course includes 4 missions and 1 guided project. It is the fourth course in the Data Analyst in R path.


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