datadoc is an R package for automatically generating a datadoc - documentation for a dataset - as a bookdown project. A datadoc is a reproducible, rich and structured format for documenting data.
Much of the focus of data analysis and data science is building models for describing some phenomenon or predicting outcomes. However, model building accounts for a very small portion of an analyst's time. The majority of an analyst's time is spent on collecting, curating, correcting and combining datasets. Data analysis is an interactive exercise, so analysts often discover understand the characteristics of a dataset as they analyse it. Their subsequent knowledge about the characteristics of a dataset are rarely recorded or communicated in a structured format.
In regulated industries where statistical models are audited, a regulator will examine the suitability of the data first, not the model - as the saying goes "Garbage in, garbage out". Each variable and data source must be described and documented. This apparently straightforward task can be very complicated and time consuming. datadoc sets out to automate a lot of this process.
There are many ways of writing documentation for datasets. I've chosen three cases below that vary widely in their richness and detail.
The Quick Draw documentation. Amazing interacive website.
The UCI Machine Learning Repository provides a reference page for each dataset. The reference starts with a summary table and sections regarding the data's source, additional information, attribute information, relevant papers and papers that cite this dataset.
In some sense the
summary function is simple documentation for a dataset. I provides many of the key statistics of interest such as mean, minimum and maximum for numeric variables and simple counts for categorical variables.
summary(iris[c(1, 2, 5)]) #> Sepal.Length Sepal.Width Species #> Min. :4.300 Min. :2.000 setosa :50 #> 1st Qu.:5.100 1st Qu.:2.800 versicolor:50 #> Median :5.800 Median :3.000 virginica :50 #> Mean :5.843 Mean :3.057 #> 3rd Qu.:6.400 3rd Qu.:3.300 #> Max. :7.900 Max. :4.400
When designing a database each entity and its relationships are mapped to a table with primary and surrogate keys and (hopefully) each column is appropriately constrained. A well designed and documented database is fundamental for supporting any data analysis, however a database's primary function is effectively storing and retrieving data, rather than recording a datasets characteristics.
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