Readable Code with R

pipes.R

# install
install.packages('magrittr')
install.packages('readr')

# library
library(magrittr)
library(readr)

# read data
ecom <- readr::read_csv('https://raw.githubusercontent.com/rsquaredacademy/datasets/master/web.csv')

# view data
head(ecom, 10)
ecom %>% head(10)

# calculate square root
y <- ecom$n_pages
y <- sqrt(y)

y <- ecom %$% n_pages
y %<>% sqrt()

y <- ecom %$% 
  n_pages %>% 
  sqrt()

# calculate correlation
ecom1 <- subset(ecom, purchase == 'true')
cor(ecom1$n_pages, ecom1$duration)

ecom %>%
  subset(purchase == 'true') %$% 
  cor(n_pages, duration)

# visualization
barplot(table(subset(ecom, purchase == 'true')$referrer))

ecom %>%
  subset(purchase == 'true') %>%
  extract('referrer') %>%
  table() %>%
  barplot()

# regression
summary(lm(duration ~ n_pages, data = ecom))

ecom %$%
  lm(duration ~ n_pages) %>%
  summary()

# string manipulation
email <- 'jovialcann@anymail.com'

toupper(strtrim(strsplit(email, '@')[[1]][1], 6))

email %>%
  strsplit(split = '@') %>%
  extract2(1) %>%
  extract(1) %>%
  strtrim(width = 6) %>%
  toupper()

# extract column by name
head(ecom['n_pages'], 3)

ecom %>%
  extract('n_pages') %>%
  head(3)

# extract column by index
head(ecom[6], 3)

ecom %>%
  extract(6) %>%
  head(3)

# extract column as vector
head(ecom$n_pages)

ecom %>%
  use_series('n_pages') %>%
  head()

# extract list element by name
mt <- as.list(mtcars)

mt[['mpg']]

mt %>%
  extract2('mpg')

# extract list element by index
mt[[1]]

mt %>%
  extract2(1)

# extract list element as vector
mt$mpg

mt %>%
  use_series(mpg)

# addition
1:10 %>%
  `+`(1)

1:10 %>%
  add(1)

# multiplication
1:10 %>%
  `*`(3)

1:10 %>%
  multiply_by(3)

# division
1:10 %>%
  `/`(2)

1:10 %>%
  divide_by(2)

# power
1:10 %>%
  `^`(2)

1:10 %>%
  raise_to_power(2)

# greater than
1:10 %>%
  `>`(5)

1:10 %>%
  is_greater_than(5)

# weakly greater than
1:10 %>%
  `>=`(5)

1:10 %>%
  is_weakly_greater_than(5)