Congratulations
Introduzione alla scrittura di funzioni in R
Richie Cotton
Data Evangelist at DataCamp
In Chapter 1 you learned
- Writing your own functions lets you reuse code.
- There is a simple process for turning scripts into functions.
- Data arguments come before detail arguments.
In Chapter 2 you learned
- Defaults can be set using
name = valuesyntax. - Arguments can be passed between functions using their name or
.... - Checking user inputs can be done using
assertive.
In Chapter 3 you learned
- You can return early from a function using
return(). - You can prevent return values being printed with
invisible(). - Functions can return multiple values using lists or attributes.
- R has rules about scope that determine which variables can be seen.
In Chapter 4 you learned
- Writing your own functions can be useful for your data analyses.
- Even simple, one-line functions can be helpful.
More modeling
Logistic Regression is covered in
- Introduction to Regression in R
- Intermediate Regression in R
- Generalized Linear Models in R
Generalized additive models are covered in
- Nonlinear Modeling in R with GAMs
Tidying models
Tidying models with broom is covered in
- Case Study: Exploratory Data Analysis in R
- Machine Learning in the Tidyverse
- Reshaping Data with tidyr
Unit testing
Unit testing code is covered in
- Developing R Packages
Environments
Environments are covered in
- Object-Oriented Programming with S3 and R6 in R
Thanks for taking the course!
Introduzione alla scrittura di funzioni in R
