A practical guide to loading multiple CSV files into R and assembling them into a single data frame, demonstrated using three approaches: base R, tidyverse (readr + dplyr + purrr), and data.table. The author recommends base R for most cases unless data is very large. The post covers several real-world scenarios including selecting specific columns, handling non-unique filenames across subdirectories, and extracting experimental metadata from file paths or filenames. Practice exercises with solutions are included, targeting cell biologists learning R for microscopy data analysis.
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