scaler Perform standard scaler on numerical features.

scaler Perform standard scaler on numerical features.

scaler(X_train, X_validation, X_test, colnames)

Arguments

colnames	vector Vector of column names for numeric features
x_train	data.frame Dataframe of train set containing columns to be scaled.
x_valid	data.frame Dataframe of validation set containing columns to be scaled.
x_test	data.frame Dataframe of test set containing columns to be scaled.

Value

list of data.frame Stores the x_train, x_valid and x_test separately as three dataframes in one list. The first element in the list will contain x_train, second will be x_valid and the third will contain x_test.

Examples

x_train <- data.frame(colors = c('Blue', 'Red', 'Green'), counts = c(34, 35, 56), usage = c(4, 6, 9))

x_validation <- data.frame(colors = c('Blue', 'Red', 'Green'), counts = c(29, 65, 13), usage = c(5, 27, 10))

x_test <- data.frame(colors = c('Blue', 'Red', 'Green'), counts = c(20, 35, 18), usage = c(9, 6, 0))

colnames <- c('counts', 'usage')

X_train = scaler(x_train, x_validation, x_test, colnames)$X_train
#> ── Attaching packages ──────────────────────────────────────────────────────────────────────── tidyverse 1.2.1 ──
#> ✓ ggplot2 3.2.1     ✓ purrr   0.3.3
#> ✓ tibble  2.1.3     ✓ dplyr   0.8.3
#> ✓ tidyr   1.0.0     ✓ stringr 1.4.0
#> ✓ readr   1.3.1     ✓ forcats 0.4.0
#> ── Conflicts ─────────────────────────────────────────────────────────────────────────── tidyverse_conflicts() ──
#> x dplyr::filter() masks stats::filter()
#> x dplyr::lag()    masks stats::lag()
#> 
#> Attaching package: ‘testthat’
#> The following object is masked from ‘package:dplyr’:
#> 
#>     matches
#> The following object is masked from ‘package:purrr’:
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#>     is_null
#> The following object is masked from ‘package:tidyr’:
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X_test = scaler(x_train, x_validation, x_test, colnames)$X_test
X_validation = scaler(x_train, x_validation, x_test, colnames)$X_validation