## ----template:attach_packages, warning=FALSE, message=FALSE--------------
# Load required packages from local library into the R session.

library(C50)          # Original C5.0 decision tree builder.
library(Hmisc)        # Escape special LaTeX charaters.
library(ROCR)         # Use prediction() for evaluation.
library(ada)          # Model: Adaptive boosting ada().
library(caret)        # Unified model builder.
library(ckanr)        # Access data from CKAN.
library(diagram)      # Produce a flowchart.
library(directlabels) # Dodging labels for ggplot2.
library(dplyr)        # Wrangling: tbl_df(), group_by(), print().
library(glue)         # Format strings.
library(ggplot2)      # Visualise data.
library(grid)         # Layout of plots: viewport().
library(lubridate)    # Dates and time.
library(magrittr)     # Data pipelines: %>% %<>% %T>% equals().
library(nnet)         # Neural network model builder.
library(party)        # Conditional trees ctree() cforest().
library(pryr)         # Meta tools: object_size(), mem_used().
library(randomForest) # Model: randomForest() na.roughfix() for missing data.
library(rattle)       # Support: normVarNames(), riskchart(), errorMatrix().
library(readr)        # Modern and efficient data reader.
library(readxl)       # Read Excel spreadsheets: read_excel().
library(rpart)        # Model: decision tree rpart().
library(rvest)        # Scrape data from the Internet.
library(scales)       # commas(), percent().
library(stringi)      # String concat operator: %s+%.
library(stringr)      # str_replace_all().
library(tibble)       # Table data frame: rownames_to_column(), glimpse().
library(tidyr)        # Tidy the dataset: gather().
library(xtable)       # Generate LaTeX tables.
library(tidyverse)    # ggplot2, tibble, tidyr, readr, purr, dplyr, stringr

## ----template:iris_summary, out.lines=7----------------------------------
summary(iris)

## ----template:iris_glimpse, out.lines=NULL-------------------------------
glimpse(iris)

## ----template:scatter, fig.height=3.5, echo=FALSE------------------------
iris %>%
  ggplot(aes(x=Sepal.Length, y=Sepal.Width, colour=Species)) +
  geom_point()