A full-day course covering the key concepts of how to leverage the R programming language for data analysis using open data. The course will cover the basic syntax of R as it relates to performing basic exploratory data analysis, as well as how to create impactful charts, graphs, and other information visualizations using NYC Open Data for operational decision making.
- Participants will understand what R is and why it's useful
- Participants will understand how R structures data, and why that's different than Excel
- Participants will open a dataset in R and shape into a usable structure for analysis
- Participants will create a visualization and calculate summary statistics of a dataset in R
- Participants will be exposed to elementary programming concepts and supplementary programming libraries in R
- Participants will apply skills to conduct a simple analysis of a dataset from the NYC Open Data Portal
- Participants will model how R can be used to build a data driven culture in their workplace
Analysts working in city government with basic programming knowledge and/or experience performing advanced analysis in Excel (nested formulas with conditionals, PivotTables, and macros)
- Introduction (Richard)
- Class Schedule and Expectations
- What is R?
- R vs Excel
- Getting Started
- Overview of Data Analysis
- NOLA Example
- Today's Question (Julia)
- Understanding Noise Complaints in 311 Data
- See Finished Example
- Data Collection (Julia)
- Open Old Faithful Dataset in R Studio
- Data Exploration (Julia)
- Calculate Summary Statistics
- Identify Columns, Levels, and Known Issues
- Explore R Studio Console
- Working with R (Richard)
- Explore Data Structures and Types
- Learn Basic Syntax
- Morning Break (15 mins)
- Exercise 311 Data (Julia)
- Lunch (1 hour)
- Working with Data (Richard)
- Data Wrangling
- Packages
- Algorithms
- Form Hypotheses
- Data Manipulation Practical (Julia)
- Debugging (Richard)
- Understand Difference Between Syntax and Semantic Errors
- Review Pro-tips for Problem-solving and Debugging
- Code Review (Richard/Julia)
- Wrap Up (Julia)
- Resources (Julia)