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: 176,747 x 7
## date location wind_dir_9am rainfall min_temp wind_speed_3pm temp_9am
## <date> <chr> <ord> <dbl> <dbl> <dbl> <dbl>
## 1 2018-01-29 NorahHead NNE 0.2 21.7 17 24.5
## 2 2017-11-22 Dartmoor NNE 0 14.9 11 26.4
## 3 2020-02-16 MelbourneA… SW 3.4 15.2 11 17.1
## 4 2015-11-03 Penrith SW 0.2 17.7 11 18.2
## 5 2019-07-26 Canberra NNE 0 -1.8 9 2
## 6 2010-09-26 Watsonia NE 0 6.9 19 11.8
## 7 2010-09-21 BadgerysCr… NNW 0.2 6.3 24 16.6
## 8 2010-08-24 Brisbane W 10.2 14 20 17.9
## 9 2019-07-10 Penrith NE 0 3.1 11 9.7
## 10 2012-11-07 PerthAirpo… SW 0.2 9.5 26 18.2
## # … with 176,737 more rowsReferences
Williams, Graham J. 2017. The Essentials of Data Science: Knowledge Discovery Using r. The r Series. CRC Press.
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