These need to be moved to their own package with the raw datasets which are available through two routes:
As .rda files through data(blabla, package = "appliedepidata"), and through interactive point and click to save the original raw data on desktop (then import as conventionally).

The second requires functions and tests.

This should act as a single source of truth for all the datasets used in handbooks, tutorials, exercises and case studies.

Need a good way to include metadata (both in terms of description of dataset source and data dictionaries).

Ideally need a future way for this to be programming and human language interchangable.

https://stat.ethz.ch/R-manual/R-devel/library/datasets/html/00Index.html

https://github.com/rfordatascience/tidytuesday/blob/master/.github/pr_instructions.md

cross-referencing appliedepi/epiRhandbook_eng#129
and appliedepi/epiRhandbook_eng#198

This has now been implemented in https://github.com/appliedepi/appliedepidata

This means that the following files can be deleted - and then {appliedepidata} needs to be added as a dependency.

R folder:

• AJS_linelist_internal.R
• AJS_pop_internal.R
• download_datasets.R
• shape_block_internal.R
• shape_quartier_internal.R

data folder:

• AJS_linelist_internal.rda
• AJS_pop_internal.rda
• shape_block_internal.rda
• shape_quartier_internal.rda

inst>extdata folder:

• AJS_AmTiman.xlsx
• AJS_AmTiman_population.xlsx
• Blocksshape.xxx
• Quartiersshape.xxx
• mortality_survey_data.xlsx
• mortality_survey_dict.xlsx