Data Science Desktop Survival Guide by Graham Williams
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Dataset Setup

20200320 Packages used in this chapter include dplyr, janitor, magrittr, randomForest, 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(dplyr)        # Wrangling: select() sample_frac().
library(janitor)      # Cleanup: clean_names().
library(magrittr)     # Data pipelines: %>% %<>% %T>% equals().
library(randomForest) # Model: randomForest() na.roughfix() for missing data.
library(rattle)       # normVarNames(). Dataset: weather.

After loading the required packages into the library we access the rattle::weatherAUS dataset and save it into the template dataset named ds, as per the template based approach introduced in Williams (2017). The dataset is reasonably large ( rows or observations by columns or variables) and is used extensively in this book to illustrate the capabilities of R for the Data Scientist.

# Initialise the dataset as per the template.
dsname <- "weatherAUS"
ds     <- get(dsname)

ds %>% sample_frac()

## # A tibble: 3,984 x 24
##    Date                Location MinTemp MaxTemp Rainfall Evaporation Sun...
##    <dttm>              <chr>      <dbl>   <dbl>    <dbl>       <dbl>    ...
##  1 2015-01-28 00:00:00 Sydney      17.3    20.5     57           7.2    ...
##  2 2019-12-21 00:00:00 Sydney      21.1    28.7      0           8.6    ...
##  3 2014-04-06 00:00:00 Sydney      17.2    21.7      3.4         4.6    ...
##  4 2015-09-23 00:00:00 Sydney      10      16.2      0.2         8.8    ...
##  5 2011-01-19 00:00:00 Sydney      19.3    25.4      7.2         5.6    ...
##  6 2015-05-09 00:00:00 Sydney      11.4    21        0           2.8    ...
##  7 2009-12-18 00:00:00 Sydney      20.2    21.4      5.4        13.6    ...
##  8 2015-11-10 00:00:00 Sydney      15.2    25.6      0           6      ...
##  9 2011-05-10 00:00:00 Sydney      10.1    18        4.4         3.4    ...
## 10 2008-06-21 00:00:00 Sydney      11.6    18.5      2.2         1.8    ...
## # ... with 3,974 more rows, and 17 more variables: WindGustDir <chr>,
## #   WindGustSpeed <dbl>, WindDir9am <chr>, WindDir3pm <chr>,
## #   WindSpeed9am <dbl>, WindSpeed3pm <dbl>, Humidity9am <dbl>,
## #   Humidity3pm <dbl>, Pressure9am <dbl>, Pressure3pm <dbl>, Cloud9am <d...
## #   Cloud3pm <dbl>, Temp9am <dbl>, Temp3pm <dbl>, RainToday <chr>,
## #   RISK_MM <dbl>, RainTomorrow <chr>