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README.md
simple_access_to_values.R
simple_access_to_values.ipynb
typology_visualisation.R
visualisation_helper.R
wals_ids_comparison.R
wals_ids_comparison.ipynb

README.md

Working with CLDF data in R

These scripts illustrate how to use basic R (i.e. without any external dependencies, packages, etc.) to work with CLDF data sets. merge() and the df[filter$condition %in% filter2$condition,] construct are used to combine the different data sources and perform basic queries and filtering tasks.

Note: While accessing CLDF data using standard data analysis tools as shown here is easy, this approach should be combined with consultation of the JSON metadata supplied with a CLDF dataset, to verify assumptions regarding syntax (e.g. the CSV dialect) and semantics (e.g. the mapping of column names to CLDF properties) of the data files.

  • simple_access_to_values.R (or its notebook version) illustrates a very basic analysis on the basis of the WALS CLDF dump.

  • wals_ids_comparison.R (or its notebook version) illustrates, in a more involved fashion, how to filter and analyse different CLDF dumps together (WALS and IDS, in this case).

  • typology_visualisation.R, a more involved example, outlining how to access, merge, filter, and post-process data for visualisation purposes. See also the associated helper file with all the functions that are being used in the example. This is based on coded provided by @bambooforest, here.

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