Plot many variables with lapply and ggplot

I want to visualise all series in the example dataset airquality: Ozone, Solar.R, Temp and Wind. There are 2 ways to do it:

• Call ggplot many times on each column name
• Call ggplot once on a reshaped dataset in long format

Call ggplot many times with lapply

In 2 steps:

1. Create a function that plots a given variable.
2. Apply this function to all interesting column in the dataset.

library(ggplot2)
#' @param yvar character name of the y variable
plotserieslines <- function(yvar){
    ggplot(airquality, aes_(x=~Day,y=as.name(yvar))) +
        geom_line() +
        facet_wrap(~Month)
}
lapply(names(airquality[c(1:4)]), plotserieslines)

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Reshape the table in long format and call ggplot only once

library(tidyr)
library(dplyr)

## 
## Attaching package: 'dplyr'

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

airquality %>% 
    gather(key, value, -Month, -Day) %>% 
    ggplot(aes(x = Day, y = value)) +
    geom_line() +
    facet_grid(key ~ Month, scales = "free")