validateSchema: Check and update schema descriptions

In tabshiftr: Reshape Disorganised Messy Data

Check and update schema descriptions

Description

This function takes a raw schema description and updates values that were only given as wildcard or implied values. It is automatically called by reorganise, but can also be used in concert with the getters to debug a schema.

Usage

validateSchema(schema = NULL, input = NULL)

Arguments

schema	[symbol(1)] the schema description.
input	[data.frame(1)] an input for which to check a schema description.

Details

The core idea of a schema description is that it can be written in a very generic way, as long as it describes sufficiently where in a table what variable can be found. A very generic way can be via using the function .find to identify the initially unknown cell-locations of a variable on-the-fly, for example when it is merely known that a variable must be in the table, but not where it is.

validateSchema matches a schema with an input table and inserts the accordingly evaluated positions (of clusters, filters and variables), adapts some of the meta-data and ensures formal consistency of the schema.

Value

An updated schema description

Examples

# build a schema for an already tidy table
(tidyTab <- tabs2shift$tidy)

schema <-
  setIDVar(name = "territories", col = 1) %>%
  setIDVar(name = "year", col = .find(pattern = "period")) %>%
  setIDVar(name = "commodities", col = 3) %>%
  setObsVar(name = "harvested", col = 5) %>%
  setObsVar(name = "production", col = 6)

# before ...
schema

# ... after
validateSchema(schema = schema, input = tidyTab)

tabshiftr documentation built on Feb. 16, 2023, 10:24 p.m.