reorganise: Reorganise a table

In tabshiftr: Reshape Disorganised Messy Data

Reorganise a table

Description

This function takes a disorganised messy table and rearranges columns and rows into a tidy table based on a schema description.

Usage

reorganise(input = NULL, schema = NULL)

Arguments

input	[data.frame(1)] table to reorganise.
schema	[symbol(1)] the schema description of input.

Value

A (tidy) table which is the result of reorganising input based on schema.

Examples

# a rather disorganised table with messy clusters and a distinct variable
(input <- tabs2shift$clusters_messy)

# put together schema description by ...
# ... identifying cluster positions
schema <- setCluster(id = "territories", left = c(1, 1, 4), top = c(1, 8, 8))

# ... specifying the cluster ID as id variable (obligatory)
schema <- schema %>%
    setIDVar(name = "territories", columns = c(1, 1, 4), rows = c(2, 9, 9))

# ... specifying the distinct variable (explicit position)
schema <- schema %>%
    setIDVar(name = "year", columns = 4, rows = c(3:6), distinct = TRUE)

# ... specifying a tidy variable (by giving the column values)
schema <- schema %>%
    setIDVar(name = "commodities", columns = c(1, 1, 4))

# ... identifying the (tidy) observed variables
schema <- schema %>%
    setObsVar(name = "harvested", columns = c(2, 2, 5)) %>%
    setObsVar(name = "production", columns = c(3, 3, 6))

# get the tidy output
reorganise(input, schema)

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