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Introduction

git2rdata supports extra metadata since version 0.4.1. Metadata is stored in a separate file with the same name as the data file, but with the extension .yml. The metadata file is a YAML file with a specific structure. The metadata file contains a generic section and a section for each field in the data file. The generic section contains information about the data file as a whole. The fields sections contain information about the fields in the data file. The metadata file is stored in the same directory as the data file.

The generic section contains the following mandatory properties, automatically created by git2rdata:

  • git2rdata: the version of git2rdata used to create the metadata.
  • datahash: the hash of the data file.
  • hash: the hash of the metadata file.
  • optimize: a logical indicating whether the data file is optimized for git2rdata.
  • sorting: a character vector with the names of the fields in the data file.
  • split_by: a character vector with the names of the fields used to split the data file.
  • NA string: the string used to represent missing values in the data file.

The generic section can contain the following optional properties:

  • table name: the name of the dataset.
  • title: the title of the dataset.
  • description: a description of the dataset.

The fields sections contain the following mandatory properties, automatically created by git2rdata:

  • type: the type of the field.
  • class: the class of the field.
  • levels: the levels of the field (for factors).
  • index: the index of the field (for factors).
  • NA string: the string used to represent missing values in the field.

The fields sections can contain the following optional properties:

  • description: a description of the field.

Adding metadata

write_vc() only stores the mandatory properties in the metadata file.

library(git2rdata)
root <- tempfile("git2rdata-metadata")
dir.create(root)
write_vc(iris, file = "iris", root = root, sorting = "Sepal.Length")
## Warning: Sorting on 'Sepal.Length' results in ties.
## Add extra sorting variables to ensure small diffs.
## 9282fad022c924c16a76bd8b3c174e71fc4515fe 
##                               "iris.tsv" 
## 0d434e56d22a710c99c5b912e8624d52abd41aaf 
##                               "iris.yml"

Reading metadata

read_vc() reads the metadata file and adds it as attributes to the data.frame. print() and summary() alert the user to the display_metadata() function. This function displays the metadata of a git2rdata object. Missing optional metadata results in an NA value in the output of display_metadata().

my_iris <- read_vc("iris", root = root)
str(my_iris)
## Classes 'git2rdata' and 'data.frame':    150 obs. of  5 variables:
##  $ Sepal.Length: num  4.3 4.4 4.4 4.4 4.5 4.6 4.6 4.6 4.6 4.7 ...
##  $ Sepal.Width : num  3 2.9 3 3.2 2.3 3.1 3.4 3.6 3.2 3.2 ...
##  $ Petal.Length: num  1.1 1.4 1.3 1.3 1.3 1.5 1.4 1 1.4 1.3 ...
##  $ Petal.Width : num  0.1 0.2 0.2 0.2 0.3 0.2 0.3 0.2 0.2 0.2 ...
##  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
##  - attr(*, "source")= Named chr [1:2] "/tmp/Rtmpk3umea/git2rdata-metadata170c5e01e260/iris.tsv" "/tmp/Rtmpk3umea/git2rdata-metadata170c5e01e260/iris.yml"
##   ..- attr(*, "names")= chr [1:2] "9282fad022c924c16a76bd8b3c174e71fc4515fe" "0d434e56d22a710c99c5b912e8624d52abd41aaf"
##  - attr(*, "optimize")= logi TRUE
##  - attr(*, "sorting")= chr "Sepal.Length"
print(head(my_iris))
##   Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1          4.3         3.0          1.1         0.1  setosa
## 2          4.4         2.9          1.4         0.2  setosa
## 3          4.4         3.0          1.3         0.2  setosa
## 4          4.4         3.2          1.3         0.2  setosa
## 5          4.5         2.3          1.3         0.3  setosa
## 6          4.6         3.1          1.5         0.2  setosa
## 
## Use `display_metadata()` to view the metadata.
summary(my_iris)
##   Sepal.Length    Sepal.Width     Petal.Length    Petal.Width   
##  Min.   :4.300   Min.   :2.000   Min.   :1.000   Min.   :0.100  
##  1st Qu.:5.100   1st Qu.:2.800   1st Qu.:1.600   1st Qu.:0.300  
##  Median :5.800   Median :3.000   Median :4.350   Median :1.300  
##  Mean   :5.843   Mean   :3.057   Mean   :3.758   Mean   :1.199  
##  3rd Qu.:6.400   3rd Qu.:3.300   3rd Qu.:5.100   3rd Qu.:1.800  
##  Max.   :7.900   Max.   :4.400   Max.   :6.900   Max.   :2.500  
##        Species  
##  setosa    :50  
##  versicolor:50  
##  virginica :50  
##                 
##                 
##                 
## 
## Use `display_metadata()` to view the metadata.
## Table name: NA
## Title: NA
## Description: NA
## Path: /tmp/Rtmpk3umea/git2rdata-metadata170c5e01e260/iris.tsv (9282fad022c924c16a76bd8b3c174e71fc4515fe), /tmp/Rtmpk3umea/git2rdata-metadata170c5e01e260/iris.yml (0d434e56d22a710c99c5b912e8624d52abd41aaf)
## Sorting order: Sepal.Length
## Optimized storage: TRUE
## Variables:
##   - Sepal.Length: NA
##   - Sepal.Width: NA
##   - Petal.Length: NA
##   - Petal.Width: NA
##   - Species: NA

Updating the optional metadata

To add metadata to a git2rdata object, use the update_metadata() function. This function allows you to add or update the optional metadata of a git2rdata object. Setting an argument to NA or an empty string will remove the corresponding property from the metadata. The function only updates the metadata file, not the data file. To see the changes, read the object again before using display_metadata(). Note that all the metadata is available in the data.frame as attributes.

update_metadata(
  file = "iris", root = root, name = "iris", title = "Iris dataset",
  description =
"The Iris dataset is a multivariate dataset introduced by the British
statistician and biologist Ronald Fisher in his 1936 paper The use of multiple
measurements in taxonomic problems.",
  field_description = c(
    Sepal.Length = "The length of the sepal in cm",
    Sepal.Width = "The width of the sepal in cm",
    Petal.Length = "The length of the petal in cm",
    Petal.Width = "The width of the petal in cm",
    Species = "The species of the iris"
  )
)
my_iris <- read_vc("iris", root = root)
display_metadata(my_iris)
## Table name: iris
## Title: Iris dataset
## Description: The Iris dataset is a multivariate dataset introduced by the British
## statistician and biologist Ronald Fisher in his 1936 paper The use of multiple
## measurements in taxonomic problems.
## Path: /tmp/Rtmpk3umea/git2rdata-metadata170c5e01e260/iris.tsv (9282fad022c924c16a76bd8b3c174e71fc4515fe), /tmp/Rtmpk3umea/git2rdata-metadata170c5e01e260/iris.yml (1d7f38f89830a2b7996e759044d7dfd59e5da4f6)
## Sorting order: Sepal.Length
## Optimized storage: TRUE
## Variables:
##   - Sepal.Length: The length of the sepal in cm
##   - Sepal.Width: The width of the sepal in cm
##   - Petal.Length: The length of the petal in cm
##   - Petal.Width: The width of the petal in cm
##   - Species: The species of the iris
str(my_iris)
## Classes 'git2rdata' and 'data.frame':    150 obs. of  5 variables:
##  $ Sepal.Length: num  4.3 4.4 4.4 4.4 4.5 4.6 4.6 4.6 4.6 4.7 ...
##   ..- attr(*, "description")= chr "The length of the sepal in cm"
##  $ Sepal.Width : num  3 2.9 3 3.2 2.3 3.1 3.4 3.6 3.2 3.2 ...
##   ..- attr(*, "description")= chr "The width of the sepal in cm"
##  $ Petal.Length: num  1.1 1.4 1.3 1.3 1.3 1.5 1.4 1 1.4 1.3 ...
##   ..- attr(*, "description")= chr "The length of the petal in cm"
##  $ Petal.Width : num  0.1 0.2 0.2 0.2 0.3 0.2 0.3 0.2 0.2 0.2 ...
##   ..- attr(*, "description")= chr "The width of the petal in cm"
##  $ Species     : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...
##   ..- attr(*, "description")= chr "The species of the iris"
##  - attr(*, "source")= Named chr [1:2] "/tmp/Rtmpk3umea/git2rdata-metadata170c5e01e260/iris.tsv" "/tmp/Rtmpk3umea/git2rdata-metadata170c5e01e260/iris.yml"
##   ..- attr(*, "names")= chr [1:2] "9282fad022c924c16a76bd8b3c174e71fc4515fe" "1d7f38f89830a2b7996e759044d7dfd59e5da4f6"
##  - attr(*, "table name")= chr "iris"
##  - attr(*, "title")= chr "Iris dataset"
##  - attr(*, "description")= chr "The Iris dataset is a multivariate dataset introduced by the British\nstatistician and biologist Ronald Fisher "| __truncated__
##  - attr(*, "optimize")= logi TRUE
##  - attr(*, "sorting")= chr "Sepal.Length"