reportabs

The reportabs package is designed to make reporting on ABS data easier. It is designed to work with (most of!) the data included in the aitidata package. reportabs contains functions to help with both visual and textual reporting of data.

Installation

reportabs can be installed from github with:

# install.packages("remotes")
remotes::install_github("f-fof/reportabs")

This package works with ABS Time Series data. A collection of pre-tidied ABS data is available through the aitidata package. This package is large and constantly updated, so you shouldn’t need to install it. Instead, you can access the data through this package.

labour_force <- read_absdata("labour_force")

It is also recommended that the tidyverse is installed and loaded.

# install.packages("tidyverse")
library(tidyverse)

What can this package do?

This package is designed to:

• report changes in labour market (or other data) indicators;
• plot labour market (or other data) indicators over time;
• generate the monthly labour force briefing

Reporting

The following functions can assist with reporting ABS time series data:

• current(): Report the current value of an indicator.
• growth(): Report the growth of an indicator over a specified period.
• change(): Report the change in the level of an indicator over a specified period.
• last_value(): Report the value of an indicator for the previous year or month.
• value_at(): Report the value of an indicator in a specific year and month.
• average_over(): Report the average value of an indicator between a specified period.
• release(): Report the most recent year or month of the data.

The key to each of these functions it the argument filter_with. This argument takes a list of parameters which must be specified to generate the correct data. filter_with requires you to specify at least an indicator by list(indicator = " "). The available indicators for each dataset can be viewed with distinct() from the dplyr package for example distinct(labour_force, indicator). filter_with can be used to also filter by gender, a state/territory (including Australia), an age group, an industry, and a series type.