extract_numeric_columns: extract_numeric_columns
In ronybsulca/numericColumns:

Description Usage Arguments Value Errors Examples

View source: R/extract_numeric_columns.R

This function returns all of the columns of the given dataset whose values are numeric or have a meaningfull numerical equivalent. If isCSV is TRUE, then dataset is taken a string depicitng the name of a CSV file. with_bool specifies if booleans are taken as numeric as well.

1 2	extract_numeric_columns(dataset, isCSV = FALSE, columns = NULL, row_names = FALSE, with_bool = FALSE, header = TRUE)

`dataset`	A DataFrame of Data.Table object whose columns will be inspected for numeric values. If `isCSV` is `TRUE`, then dataset is the name of the CSV file to inspect.
`isCSV`	bool. If `TRUE`, the dataset will be read from the CSV file depicted in `dataset`.
`columns`	vector list of column names to coerce which columns the analysis will apply to. The given `columns` that do not pass the numeric test will be returned as NAs. If default `extract_numeric_columns` will apply the numeric test to all columns and return only the ones that pass it.
`row_names`	bool or integer. Only applied when `isCSV` is `TRUE`. If `TRUE`, the dataset will be read and returned with their row names. If `FALSE`, the dataset won't be read with row names. If `row_names` is an integer, then that index will be used consider the row names column.
`with_bool`	bool. Specifies whether we consider booleans as numeric values.
`header`	bool. Same Parameters as that in `read.csv`. Specifies if the CSV being read contains headers in the first row. `TRUE` by default.

This function returns a Data Frame object, with row names given based on the row_names argument. It includes all the columns of the given dataset whose elements are all numeric or have a meaningful numerical equivalent.

extract_numeric_columns won't be able to detect numeric values in columns of data type factor. If a numeric column is being read from a csv as factor by this function, then the dataset must be given as data table or data frame object (isCSV = FALSE).

## Not run: 
extract_numeric_columns(mtcars)
extract_numeric_columns(mtcars, columns = c("mpg", "cyl"))
extract_numeric_columns("test_data_1.csv", isCSV = TRUE)
extract_numeric_columns("test_data_2.csv", isCSV = TRUE, row_names = TRUE, with_bool = TRUE)

## End(Not run)