By Wickham, Hadley
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Attr(*, "class")= chr "AsIs" dfl[2, "y"] #> [] #>  1 2 3 I() adds the AsIs class to its input, but this can usually be safely ignored. frame': 3 obs. of 2 variables: #> $ x: int 1 2 3 #> $ y: 'AsIs' int [1:3, 1:3] 1 2 3 4 5 6 7 8 9 dfm[2, "y"] #> [,1] [,2] [,3] #> [1,] 2 5 8 Use list and array columns with caution: many functions that work with data frames assume that all columns are atomic vectors. 5 Exercises 1. What attributes does a data frame possess? 2. matrix() do when applied to a data frame with columns of diﬀerent types?
What makes them diﬀerent to 1:5? pdf) makes data analysis easier. Under the hood, a data frame is a list of equal-length vectors. This makes it a 2-dimensional structure, so it shares properties of both the matrix and the list. This means that a data frame has names(), colnames(), and rownames(), although names() and colnames() are the same thing. The length() of a data frame is the length of the underlying list and so is the same as ncol(); nrow() gives the number of rows. As described in Chapter 3, you can subset a data frame like a 1d structure (where it behaves like a list), or a 2d structure (where it behaves like a matrix).
1. What is the result of subsetting a vector with positive integers, negative integers, a logical vector, or a character vector? 33 © 2015 by Taylor & Francis Group, LLC 34 Advanced R 2. What’s the diﬀerence between [, [[, and $ when applied to a list? 3. When should you use drop = FALSE? 4. If x is a matrix, what does x <- 0 do? How is it diﬀerent to x <- 0? 5. How can you use a named vector to relabel categorical variables? 1 starts by teaching you about [. You’ll start by learning the six types of data that you can use to subset atomic vectors.
Advanced R by Wickham, Hadley