fastDummies (version 0.1.2)

dummy_rows: Fast creation of dummy rows

Description

Fast creation of dummy rows

Usage

dummy_rows(dataset, select_columns = NULL, add_columns = NULL,
  ignore_columns = NULL, dummy_value = 0, year = FALSE,
  return_type = "data.table", dummy_indicator = FALSE)

Arguments

dataset

data.table or data.frame

select_columns

If NULL, uses character, factor, and Date columns to produce categories to make the dummy rows by. If not NULL, you manually enter a string or vector of columns name(s).

add_columns

String or vector of column name(s) to add to the selected coumns. This is only if you want to use all character, factor, and Date columns (selected by default) and are adding additional columns of different data types.

ignore_columns

String or vector of column name(s) to exclude from the selected columns. These excluded columns will get the same dummy value of all non-selected columns

dummy_value

Value of the row for columns that are not selected. Default is a value of 0.

year

TRUE to include a column called year (capitalization is ignored) as one of the selected columns.

return_type

Type of data you want back_ Default is data.table (better for use with large data)_ Other option is data.frame.

dummy_indicator

Adds binary column to say if row is dummy or not (i.e. included in original data or not)

Value

data.table or data.frame depending on input for return_type. data.table is default.

Examples

# NOT RUN {
data(dummy_rows_example)

# Makes dummy rows using default column selection and year
# to make categories
example <- dummy_rows(dummy_rows_example, year = TRUE)

# Same as above but adds binary column indicating if the row
# is dummy or not
example <- dummy_rows(dummy_rows_example, year = TRUE, dummy_indicator = TRUE)
# }