{introverse} quick docs

 as.numeric()
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Description

The as.numeric() function comes with R and is part of the Base R {base} package.

We use this function to coerce a value or variable to be a numeric, i.e. change the variable’s type into a numeric type.

Not all values can be changed to numeric, and this function will return NA if the value could not be coerced.

Conceptual Usage

as.numeric(value to coerce into numeric type)

Examples

# Convert the string "10" to the number 10
as.numeric("10")

## [1] 10

# This example will return NA since there is no natural way to coerce the argument into a numeric
# It will also reveal a warning message telling you the coercion wasn't possible
as.numeric("you can't make strings into numbers")

## Warning: NAs introduced by coercion

## [1] NA

# The logical `TRUE` turns into 1 when coerced to be a number. 
# This is consistent across all programming languages that allow coersion.
as.numeric(TRUE)

## [1] 1

# The logical `FALSE` turns into 0 when coerced to be a number. 
# This is consistent across all programming languages that allow coersion.
as.numeric(FALSE)

## [1] 0

# Example of coercing a column in a tibble to be numeric.
# This will only work if the column values are allowed to be numbers

# First, create and show a tibble to use for the example:
example_tib <- tibble::tibble(
  column1 = c("1", "2", "3", "4"),
  column2 = c("a", "b", "c", "d")
)
example_tib

## # A tibble: 4 × 2
##   column1 column2
##   <chr>   <chr>  
## 1 1       a      
## 2 2       b      
## 3 3       c      
## 4 4       d

# We can successfully coerce column1, but column2 will becomes NAs
example_tib$column1 <- as.numeric(example_tib$column1)
example_tib$column2 <- as.numeric(example_tib$column2)

## Warning: NAs introduced by coercion

# Show data after coersion:
example_tib

## # A tibble: 4 × 2
##   column1 column2
##     <dbl>   <dbl>
## 1       1      NA
## 2       2      NA
## 3       3      NA
## 4       4      NA

# Or, we can coerce (or attempt coercion) with dplyr::mutate()
example_tib %>%
  dplyr::mutate(column1 = as.numeric(column1),
                column2 = as.numeric(column2))

## # A tibble: 4 × 2
##   column1 column2
##     <dbl>   <dbl>
## 1       1      NA
## 2       2      NA
## 3       3      NA
## 4       4      NA