Summarize a data frame as binned interpolated percentiles

This function was deprecated in epidatatools 2.0.0. Use averaged_quantile(), EPI's preferred method for interpolating percentiles, with dplyr::reframe() instead. It uses a different method, so its results differ:

dplyr::reframe(mtcars, probs = c(0.25, 0.75),
  value = averaged_quantile(mpg, wt, probs), .by = cyl)

Usage

binipolate(data, x, probs = 0.5, bin_size, .by = NULL, w = NULL)

Arguments

data

data frame

x

column to compute

probs

numeric vector of percentiles with values [0,1]

bin_size

size of binning

.by

optional, a tidy-selection of columns for single-operation grouping

w

numeric vector of weights the same length as x giving the weights to use for elements of x

Value

a tibble or data frame

Examples

binipolate(mtcars, mpg, bin_size = 0.25)
#> Warning: `binipolate()` was deprecated in epidatatools 2.0.0.
#> ℹ Please use `averaged_quantile()` instead.
#> ℹ For example: `dplyr::reframe(data, probs = probs, value =
#>   averaged_quantile(x, w, probs), .by = group)`. averaged_quantile() uses a
#>   different method, so its results differ.
#> # A tibble: 1 × 2
#>   probs value
#>   <dbl> <dbl>
#> 1   0.5  19.1
binipolate(mtcars, mpg, probs = c(0.25, 0.5, 0.75), bin_size = 0.25)
#> # A tibble: 3 × 2
#>   probs value
#>   <dbl> <dbl>
#> 1  0.25  15.4
#> 2  0.5   19.1
#> 3  0.75  22.2
binipolate(mtcars, mpg, probs = c(0.25, 0.5, 0.75), bin_size = 0.25, .by = cyl, w = wt)
#> # A tibble: 9 × 3
#>     cyl probs value
#>   <dbl> <dbl> <dbl>
#> 1     4  0.25  21.9
#> 2     4  0.5   23.9
#> 3     4  0.75  28.3
#> 4     6  0.25  18.0
#> 5     6  0.5   19.5
#> 6     6  0.75  20.6
#> 7     8  0.25  13.0
#> 8     8  0.5   15.2
#> 9     8  0.75  16.1