README.md

labelmachine

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labelmachine is an R package that helps assigning meaningful labels to data sets. Furthermore, you can manage your labels in so called lama-dictionary files, which are yaml files. This makes it very easy using the same label translations in multiple projects which share similar data structure.

Labeling your data can be easy!

Installation

# Install release version from CRAN
install.packages("labelmachine")

# Install development version from GitHub
devtools::install_github('a-maldet/labelmachine', build_vignettes = TRUE)

Concept

The label assignments are given in so called translations (named character vectors), which are like a recipes, telling which original value will be mapped onto which new label. The translations are collected in so called lama_dictionary objects. This lama_dictionary objects will be used to translate your data frame variables.

Usage

Let df be a data frame with marks and subjects, which should be translated

df <- data.frame(
  pupil_id = c(1, 1, 2, 2, 3),
  subject = c("en", "ma", "ma", "en", "en"),
  result = c(2, 1, 3, 2, NA),
  stringsAsFactors = FALSE
)
df
##   pupil_id subject result
## 1        1      en      2
## 2        1      ma      1
## 3        2      ma      3
## 4        2      en      2
## 5        3      en     NA

Create a lama_dictionary object holding the translations:

library(labelmachine)
dict <- new_lama_dictionary(
  subjects = c(en = "English", ma = "Mathematics", NA_ = "other subjects"),
  results = c("1" = "Excellent", "2" = "Satisfying", "3" = "Failed", NA_ = "Missed")
)
dict
## 
## --- lama_dictionary ---
## Variable 'subjects':
##               en               ma              NA_ 
##        "English"    "Mathematics" "other subjects" 
## 
## Variable 'results':
##            1            2            3          NA_ 
##  "Excellent" "Satisfying"     "Failed"     "Missed"

Translate the data frame variables:

df_new <- lama_translate(
  df,
  dict,
  subject_new = subjects(subject),
  result_new = results(result)
)
str(df_new)
## 'data.frame':    5 obs. of  5 variables:
##  $ pupil_id   : num  1 1 2 2 3
##  $ subject    : chr  "en" "ma" "ma" "en" ...
##  $ result     : num  2 1 3 2 NA
##  $ subject_new: Factor w/ 3 levels "English","Mathematics",..: 1 2 2 1 1
##  $ result_new : Factor w/ 4 levels "Excellent","Satisfying",..: 2 1 3 2 4

Highlights

labelmachine offers the following features:

Further reading

A short introduction can be found here: Get started



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labelmachine documentation built on Oct. 11, 2019, 9:05 a.m.