Attributes
You have made it to the last exercise in the course! Congrats! Let's finish up with an easy one.
Attributes are a bit of extra metadata about your data structure. Some of the most common attributes are: row names and column names, dimensions, and class. You can use the attributes() function to return a list of attributes about the object you pass in. To access a specific attribute, you can use the attr() function.
Exploring the attributes of cash:
attributes(cash)
$names
[1] "company" "cash_flow" "year"
$row.names
[1] 1 2 3 4 5 6 7
$class
[1] "data.frame"
attr(cash, which = "names")
[1] "company" "cash_flow" "year"
This is a part of the course
“Introduction to R for Finance”
Exercise instructions
- The matrix
my_matrixand the factormy_factorare defined for you. - Use
attributes()onmy_matrix. - Use
attr()onmy_matrixto return the"dim"attribute. - Use
attributes()onmy_factor.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# my_matrix and my_factor
my_matrix <- matrix(c(1,2,3,4,5,6), nrow = 2, ncol = 3)
rownames(my_matrix) <- c("Row1", "Row2")
colnames(my_matrix) <- c("Col1", "Col2", "Col3")
my_factor <- factor(c("A", "A", "B"), ordered = T, levels = c("A", "B"))
# attributes of my_matrix
# Just the dim attribute of my_matrix
# attributes of my_factor
This exercise is part of the course
Introduction to R for Finance
Learn essential data structures such as lists and data frames and apply that knowledge directly to financial examples.
Wouldn't it be nice if there was a way to hold related vectors, matrices, or data frames together in R? In this final chapter, you will explore lists and many of their interesting features by building a small portfolio of stocks.
Exercise 1: What is a list?Exercise 2: Create a listExercise 3: Named listsExercise 4: Access elements in a listExercise 5: Adding to a listExercise 6: Removing from a listExercise 7: A few list creating functionsExercise 8: Split itExercise 9: Split-Apply-CombineExercise 10: AttributesExercise 11: Congratulations!What is DataCamp?
Learn the data skills you need online at your own pace—from non-coding essentials to data science and machine learning.