文章目錄

• 例子1
• 例子2
• 例子3：回歸函數(shù)lm中
• 例子4：繪圖函數(shù)ggplot中

parse函數(shù)解析字符串為表達(dá)式；eval函數(shù)執(zhí)行表達(dá)式輸出結(jié)果；parse函數(shù)和eval函數(shù)在自定義函數(shù)中常常非常有用

library(ggplot2) rm(list = ls())

例子1

b為字符換：“character”

b <- " for (i in 1:5) {print(i) } " class(b) # [1] "character"

parse函數(shù)將b轉(zhuǎn)化為表達(dá)式：“expression”

parsed_b <- parse(text = b) parsed_b # expression(for (i in 1:5) { # print(i) # })class(parsed_b) # [1] "expression"

eval函數(shù)執(zhí)行表達(dá)式

eval(parsed_b) # [1] 1 # [1] 2 # [1] 3 # [1] 4 # [1] 5

例子2

mtcars為R自帶的有關(guān)汽車的數(shù)據(jù)集

class(mtcars) # [1] "data.frame"class(parse(text = "mtcars")) # [1] "expression"class(eval(parse(text = "mtcars"))) # [1] "data.frame"head(eval(parse(text = "mtcars"))) # mpg cyl disp hp drat wt qsec vs am gear # Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 # Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 # Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 # Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 # Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 # Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 # carb # Mazda RX4 4 # Mazda RX4 Wag 4 # Datsun 710 1 # Hornet 4 Drive 1 # Hornet Sportabout 2 # Valiant 1

例子3：回歸函數(shù)lm中

使用mtcars數(shù)據(jù)集，以wt為因變量，欲分別建立mpg、cyl、disp、hp、drat與wt的回歸模型

以wt與mpg的回歸模型為例，可以直接這樣寫

lm(wt ~ mpg, data = mtcars) # # Call: # lm(formula = wt ~ mpg, data = mtcars) # # Coefficients: # (Intercept) mpg # 6.0473 -0.1409

如果建模過程語句較多，而不同模型僅僅是自變量發(fā)生了變化，那么編寫函數(shù)可以簡(jiǎn)化過程。

編寫函數(shù)時(shí)該如何指明自變量那？

以下函數(shù)編寫方式行不通，"mpg"或mpg無法正確識(shí)別

# lm_func <- function(var) { # lm(wt ~ var, data = mtcars) # } # # lm_func(var = mpg) # lm_func(var = "mpg")

查閱幫助可知，lm函數(shù)的第一個(gè)參數(shù)為formula

# lm(formula = , data = )

使用parse函數(shù)和eval函數(shù)將字符串形式的"wt ~ mpg"轉(zhuǎn)換為formula，再帶入lm函數(shù)后可以正確運(yùn)行

class(eval(parse(text = "wt ~ mpg"))) # [1] "formula" lm(eval(parse(text = "wt ~ mpg")), data = mtcars) # # Call: # lm(formula = eval(parse(text = "wt ~ mpg")), data = mtcars) # # Coefficients: # (Intercept) mpg # 6.0473 -0.1409

根據(jù)上述信息，lm_func函數(shù)可編寫為

lm_func <- function(var) {lm(eval(parse(text = paste0("wt ~ ", var))), data = mtcars) }lm_func(var = "mpg") # 正確執(zhí)行了 # # Call: # lm(formula = eval(parse(text = paste0("wt ~ ", var))), data = mtcars) # # Coefficients: # (Intercept) mpg # 6.0473 -0.1409

除了使用parse函數(shù)和eval函數(shù)，另一種方法是使用formula函數(shù)將字符串"wt ~ mpg"直接轉(zhuǎn)換為formula

class(formula("wt ~ mpg")) # [1] "formula" lm(formula("wt ~ mpg"), data = mtcars) # # Call: # lm(formula = formula("wt ~ mpg"), data = mtcars) # # Coefficients: # (Intercept) mpg # 6.0473 -0.1409

使用formula函數(shù)，lm_func可編寫為

lm_func <- function(var) {lm(formula(paste0("wt ~ ", var)), data = mtcars) }lm_func(var = "mpg") # 正確執(zhí)行了 # # Call: # lm(formula = formula(paste0("wt ~ ", var)), data = mtcars) # # Coefficients: # (Intercept) mpg # 6.0473 -0.1409

例子4：繪圖函數(shù)ggplot中

使用mtcars數(shù)據(jù)集，以wt為因變量，欲分別繪制mpg、cyl、disp、hp、drat與wt的散點(diǎn)圖

以wt與mpg的散點(diǎn)圖為例，可以直接這樣寫

ggplot(data = mtcars, aes(x = mpg, y = wt)) +geom_point() +labs(x = "mpg", y = "wt") +theme_bw()

這樣編寫繪圖函數(shù)，結(jié)果表明行不通

# plot_func <- function(var) { # ggplot(data = mtcars, aes(x = var, y = wt)) + # geom_point() + # labs(x = var, y = "wt") + # theme_bw() # } # # plot_func(var = mpg) # plot_func(var = "mpg")

嘗試使用eval函數(shù)和parse函數(shù)，結(jié)果表明這樣可以正確運(yùn)行

ggplot(data = mtcars, aes(x = eval(parse(text = "mpg")),y = eval(parse(text = "wt")))) + geom_point() + labs(x = "mpg", y = "wt") + theme_bw()

根據(jù)上述信息，plot_func函數(shù)可編寫為

plot_func <- function(var) {ggplot(data = mtcars, aes(x = eval(parse(text = var)),y = eval(parse(text = "wt")))) + geom_point() + labs(x = var, y = "wt") + theme_bw() }plot_func(var = "mpg") # 正確運(yùn)行了

另一種方法：ggplot函數(shù)參數(shù)中，將aes改為aes_string可以正確處理字符串對(duì)象

ggplot(data = mtcars, aes_string(x = "mpg", y = "wt")) +geom_point() +labs(x = "mpg", y = "wt") + theme_bw()

使用aes_string，繪圖函數(shù)還可編寫為

plot_func <- function(var) {ggplot(data = mtcars, aes_string(x = var, y = "wt")) + geom_point() + labs(x = var, y = "wt") + theme_bw() }plot_func(var = "mpg") # 正確運(yùn)行了

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