14.2 ML Data and Variables

20210104

The rattle::weatherAUS dataset is loaded into the template variable ds and further template variables are setup as introduced by Graham J. Williams (2017). See Chapter 8 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()

It is always useful to remind ourselves of the dataset with a random sample:

ds  %>% sample_frac() %>% select(date, location, sample(3:length(vars), 5))

## # A tibble: 217,049 × 7
##    date       location      humidity_3pm wind_speed_3pm rainfall press…¹ wind_…²
##    <date>     <chr>                <int>          <dbl>    <dbl>   <dbl>   <dbl>
##  1 2017-06-07 BadgerysCreek           90             19     17.4   1021.      43
##  2 2008-12-05 Penrith                 48             15      0       NA       28
##  3 2022-04-28 Albany                  NA             NA     19.8   1013.      NA
##  4 2017-10-08 Mildura                 33             17      0.2   1008.      39
##  5 2011-06-02 WaggaWagga              46             15      0     1023.      28
##  6 2013-08-06 Penrith                 33             24      0       NA       50
##  7 2015-11-28 Canberra                30             17      0     1013.      52
##  8 2011-01-08 CoffsHarbour            87             28      5.6   1009.      33
....

References

Williams, Graham J. 2017. The Essentials of Data Science: Knowledge Discovery Using r. The r Series. CRC Press.

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