Data Science Desktop Survival Guide by Graham Williams
Desktop Survival Project Home Preface Data Science Introducing R R Constructs R Tasks R Strings R Read, Write, and Create Data Template Data Exploration Data Wrangling Data Visualisation Statistics ML Template ML Scenarios ML Activities ML Applications ML Algorithms Cluster Analysis Decision Trees Computer Vision Graph Data Privacy Literate Data Science Coding with Style Resources Bibliography Index

CLICK HERE TO VISIT THE UPDATED SURVIVAL GUIDE

KnitR Setup

20200602

Packages used in this chapter include diagram, dplyr, ggplot2, magrittr, xtable, Hmisc, and rattle.

Packages are loaded into the currently running R session from your local library directories on disk. Missing packages can be installed using utils::install.packages() within R. On Ubuntu, for example, R packages can be installed using wajig install r-cran-<pkgname>.

# Load required packages from local library into the R session.

library(rattle)       # Dataset: weatherAUS.
library(magrittr)     # Data pipelines: %>% %T>% %<>%.
library(ggplot2)      # Visualise data.
library(xtable)       # Format R data frames as LaTeX tables.
library(Hmisc)        # Escape special LaTeX charaters.
library(diagram)      # Produce a flowchart.
library(dplyr)        # Data wrangling.
library(scales)

The rattle::weatherAUS dataset is loaded into the template variable ds and further template variables are setup as introduced in Williams (2017). See Chapter 7 for details.

dsname <- "weatherAUS"
ds     <- get(dsname)

nobs   <- nrow(ds)

vnames <- names(ds)
ds    %<>% clean_names(numerals="right")
names(vnames) <- names(ds)

vars   <- names(ds)
target <- "rain_tomorrow"
vars   <- c(target, vars) %>% unique() %>% rev()

A random sample of the dataset:

ds %>% sample_frac()

## # A tibble: 176,747 x 24
##    date       location min_temp max_temp rainfall evaporation sunshine
##    <date>     <chr>       <dbl>    <dbl>    <dbl>       <dbl>    <dbl>
##  1 2009-12-31 Perth        15.2     26.6      0          11.2     12.1
##  2 2014-01-16 MountGa~     22.8     44.1      0           9       12.1
##  3 2009-02-08 Sydney       21.4     28.6      0          14.2     12.2
##  4 2014-08-23 NorahHe~     10.9     17.8      8.4        NA       NA  
##  5 2014-12-07 Richmond     17.5     29.9     33.6        NA       NA  
##  6 2014-01-18 Tuggera~     14.2     39.4      0          NA       NA  
##  7 2014-07-31 Launces~     11.5     14.7     29.2        NA       NA  
....