'
pq_example_mtcars.R
===================
Author: |author_names|
Release: |version|
Date: |today|
Purpose
=======
|description|
Runs some basic stats and plots as examples using the mt_cars dataset available in R.
Usage and options
=================
These are based on docopt_ for R:
https://github.com/docopt/docopt.R
https://cran.r-project.org/web/packages/docopt/index.html
To run, type:
Rscript pq_example_mtcars.R [options]
Usage: pq_example_mtcars.R [--session=<R_SESSION_NAME>]
pq_example_mtcars.R [-h | --help]
Options:
--session=<R_SESSION_NAME>      R session name if to be saved
-h --help                       Show this screen
Input:
None needed, the script loads the data "mtcars"
Output:
A boxplot and scatterplot from the R dataset mtcars as svg files
and an html table of a linear regression output.
Requirements:
library(docopt)
library(stargazer)
Documentation
=============
For more information see:
|url|
' -> doc
# Load docopt:
library(docopt, quietly = TRUE)
# Retrieve the command-line arguments:
args <- docopt(doc)
# See:
# https://cran.r-project.org/web/packages/docopt/docopt.pdf
# docopt(doc, args = commandArgs(TRUE), name = NULL, help = TRUE,
# version = NULL, strict = FALSE, strip_names = !strict,
# quoted_args = !strict)
# Print to screen:
str(args)
suppressMessages(library(stargazer, quietly = TRUE)) # tables for linear regressions
input_data <- data('mtcars')
input_name <- 'mtcars'
class(input_data)
dim(input_data) # nrow(), ncol()
str(input_data)
data('mtcars')
class(input_data)
dim(input_data) # nrow(), ncol()
str(input_data)
head(input_data)
tail(input_data)
data('mtcars')
input_data <-
# Explore data:
class(input_data)
dim(input_data) # nrow(), ncol()
str(input_data)
head(input_data)
input_data <- data.frame(data('mtcars'))
class(input_data)
dim(input_data) # nrow(), ncol()
str(input_data)
input_name <- 'mtcars'
input_data <- as.data.frame(data('mtcars'))
class(input_data)
dim(input_data) # nrow(), ncol()
str(input_data)
head(input_data)
input_data <- as.data.frame(data(input_name))
mtcars
data('mtcars')
input_data <- as.data.frame(mtcars)
class(input_data)
dim(input_data) # nrow(), ncol()
str(input_data)
head(input_data)
tail(input_data)
colnames(input_data)
nrow(input_data)
length(which(complete.cases(input_data) == TRUE))
summary(input_data)
summary(input_data[, c('wt', 'qsec', 'gears')])
summary(input_data)
summary(input_data[, c('wt', 'qsec', 'gear')])
cyl_factor <- factor(input_data$cyl)
cyl_factor
gear_factor <- factor(input_data$gear)
gear_factor
boxplot(input_data$mpg ~ cyl_factor)
plot(input_data$qsec ~ cyl_factor)
pass_formula <- 'qsec ~ cyl_factor + hp + wt + gear_factor'
lm_input_data <- lm(formula = pass_formula, data = input_data)
summary(lm_input_data)
