R for Data Scienceの例題を解く- Chapter 10 tibble

神Hadley R for Data Science の例題たちとその解答を書き残します。
今回はChapter 10 Tibblesです。

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この章では下記のライブラリを使う。

library(tidyverse)

Chapter 10 Tibbles

10.5 Exercises

1. How can you tell if an object is a tibble? (Hint: try printing macars, which is a rgular data frame).

is_tibble(mtcars)
# FALSE

is_tibble(diamonds)
# TRUE

2. Compare and contrast the following operations on a data.frame and equivalent tibble. What is different? Why might the default data frame behaviors cause you frustration?

df <- data.frame(abc = 1, xyz = "a")
df$x
df[, "xyz"]
df[, c("abc", "xyz")]
  1. 変数はxyzしかないのに、"$"が部分一致に対応しているため$xが作用してしまう。
  2. 同一のデータフレームdfに同一の関数"["を作用させているのに、引数の数の違い(ここでは"xyz"c("abc", "xyz")の違い)によって関数が返す値がベクトルとデータフレームと変化する。

3. If you have the name of a variable stored in an object, e.g. var <- "mpg", how can you extract the reference varible from a tibble?

as_tibble(mtcars)[var]

4. Practice referring to non-syntactic names in the following data frmae by:

  1. Extracting the varible called 1.
  2. Plotting a scatterplot of 1 vs 2.
  3. Creating a new column called 3 which is 2 divided by 1.
  4. Renaming the columns to one, two, and three.
annoying <- tibble(
	`1` = 1:10,
	`2` = `1` * 2 + rnorm(length(`1`))
	)
#1.
select(annoying, `1`) #as tibble
annoying$`1` #as vector

#2.
plot(annoying$`1`, annoying$`2`)
ggplot(annoying) + geom_point(aes(`1`, `2`))

#3.
mutate(annoying, `3` = `2`/`1`)

#4.
rename(annoying, one = `1`, two = `2`)

5. What does tibble::enframe() do? When might you use it?

名前付きベクトルを名前と値の二つの列を持つtibbleに変換する関数。
変数にname, valueの二つがあり、それぞれ変換後のtibbleの列名を指定できる。

6. What option controls how many additional column names are printed at the footer of a tibble?

print関数のn_extraオプションでコントロールする。

参考サイト

Chapter 10 Tibbles

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