By Hadley Wickham.
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Extra resources for Advanced R
If you need more details, you can ﬁnd them in R’s documentation. R’s base data structures can be organised by their dimensionality (1d, 2d, or nd) and whether they’re homogeneous (all contents must be of the same type) or heterogeneous (the contents can be of diﬀerent types). This gives rise to the ﬁve data types most often used in data analysis: Homogeneous Heterogeneous 1d Atomic vector List 2d Matrix Data frame nd Array Almost all other objects are built upon these foundations. In Chapter 7 you’ll see how more complicated objects are built of these simple pieces.
It is truly a community eﬀort: many people read drafts, ﬁxed typos, suggested improvements, and contributed content. Without those contributors, the book wouldn’t be nearly as good as it is, and I’m deeply grateful for their help. Special thanks go to Peter Li, who read the book from cover-to-cover and provided many ﬁxes. Other outstanding contributors were Aaron Schumacher, @crtahlin, Lingbing Feng, @juancentro, and @johnbaums. Thanks go to all contributers in alphabetical order: Aaron Schumacher, Aaron Wolen, @aaronwolen, @absolutelyNoWarranty, Adam Hunt, @agrabovsky, @ajdm, @alexbbrown, @alko989, @allegretto, @AmeliaMN, @andrewla, Andy Teucher, Anthony Damico, Anton Antonov, @aranlunzer, @arilamstein, @avilella, @baptiste, @blindjesse, @blmoore, @bnjmn, Brandon Hurr, @BrianDiggs, @Bryce, C.
This is because when [ is applied to a list it always returns a list: it never gives you the contents of the list. ” — @RLangTip Because it can return only a single value, you must use [[ with either a single positive integer or a string: 41 Subsetting a <- list(a = 1, b = 2) a[] #>  1 a[["a"]] #>  1 # If you do supply a vector it indexes recursively b <- list(a = list(b = list(c = list(d = 1)))) b[[c("a", "b", "c", "d")]] #>  1 # Same as b[["a"]][["b"]][["c"]][["d"]] #>  1 Because data frames are lists of columns, you can use [[ to extract a column from data frames: mtcars[], mtcars[["cyl"]].