Decomposes a data frame into several relations, based on the given database schema. It's intended that the data frame satisfies all the functional dependencies implied by the schema, such as if the schema was constructed from the same data frame. If this is not the case, the function will returns an error.
decompose(
df,
schema,
keep_rownames = FALSE,
digits = getOption("digits"),
check = TRUE
)A database object, containing the data in df
within the database schema given in schema.
a data.frame, containing the data to be normalised.
a database schema with foreign key references, such as given by
autoref.
a logical or a string, indicating whether to include the row names as a column. If a string is given, it is used as the name for the column, otherwise the column is named "row". Set to FALSE by default.
a positive integer, indicating how many significant digits are
to be used for numeric and complex variables. A value of NA results
in no rounding. By default, this uses getOption("digits"), similarly
to format. See the "Floating-point variables" section for
discover for why this rounding is necessary for consistent
results across different machines. See the note in
print.default about digits >= 16.
a logical, indicating whether to check that df satisfies
the functional dependencies enforced by schema before creating the
result. This can find key violations without spending time creating the
result first, but is redundant if df was used to create
schema in the first place.
If the schema was constructed using approximate dependencies for the same
data frame, decompose returns an error, to prevent either duplicate records
or lossy decompositions. This is temporary: for the next update, we plan to
add an option to allow this, or to add "approximate" equivalents of databases
and database schemas.