README.Rmd

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output: github_document
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knitr::opts_chunk$set(
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# dumblump

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Lump a numeric variable into categorical groups using 'dumblump' algorithm

# The **dumblump** algorithm:

 1. Sort numbers in ascending order
 2. For each number, check its distance from the previous number (the closest, lower number in dataset).
 3. If distance >= threshold, define a new group. If distance < threshold, 'lump' with the group of the previous number

Disadvantages of this method
 1. You can get numbers of substantially different scales in a single group. E.g. If you have a set of numbers 1, 2, 3,4, 5, 6, 7 ... 100000.


These will all be classified as a single group unless theres a 'break' of > threshold somewhere along. If this is not what you want,
explore clustering methods


## Installation

You can install the development version of dumblump like so:

``` r
#install.packages('remotes')
remotes::install_github('selkamand/dumblump')
```

## Usage

This is a basic example which shows you how to solve a common problem:

```{r example}
library(dumblump)

unlumped <- c(1, 1, 2, 5,5 , 6, 1, 12, 12)


lumped <- dumblump(unlumped, threshold = 1)
data.frame(lumped, unlumped)
```