Episode Details

Bringing tidy principles to a fundamental visualization for gene expressions, being on your best "behavior" for organizing your tests, and how data.table stacks up to DuckDB and polars for reshaping your data layouts.
Episode Links

• This week's curator: Jon Carroll - @jonocarroll@fosstodon.org (Mastodon) & @carroll_jono (X/Twitter)
• Exploring the tidyHeatmap R package
• Don't Expect That "Function Works Correctly", Do This Instead
• Comparing data.table reshape to duckdb and polars
• Entire issue available at rweekly.org/2024-W43

Supplement Resources

• tidyHeatmap: Draw heatmap simply using a tidy data frame https://stemangiola.github.io/tidyHeatmap/
• Novel App knock-in mouse model shows key features of amyloid pathology and reveals profound metabolic dysregulation of microglia https://molecularneurodegeneration.biomedcentral.com/articles/10.1186/s13024-022-00547-7
• Shiny App-Packages chapter on writing tests and specifications https://mjfrigaard.github.io/shiny-app-pkgs/test_specs.html
• WANT CLEANER UNIT TESTS? TRY ARRANGE, ACT, ASSERT COMMENTS https://jakubsob.github.io/blog/want-cleaner-test-try-arrange-act-assert/
• Super Data Science Podcast 827: Polars: Past, Present and Future, with Polars Creator Ritchie Vink https://www.superdatascience.com/podcast/827
• duckplyr: A DuckDB-backed version for dplyr https://duckplyr.tidyverse.org/

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Music credits powered by OCRemix

• Black Feathers in the Sky - Kid Icarus: Uprising - MkVaff - https://ocremix.org/remix/OCR04200
• Cross-Examination - Phoenix Wright: Ace At