A fast and friendly R package for reading rectangular data from delimited files like CSV and TSV.
readr is an R package that provides fast and user-friendly functions to read rectangular data from flat files like CSV, TSV, and fixed-width formats. It solves the problem of efficiently importing and parsing real-world data with informative feedback, making data import more reliable and consistent within the tidyverse ecosystem.
R users, data analysts, and data scientists who need to import and clean structured data from text files as part of their data analysis workflows, especially those working within the tidyverse.
Developers choose readr for its speed improvements over base R, consistent and intuitive API, informative error reporting, and seamless integration with the tidyverse, offering a modern and efficient alternative for data import tasks.
Read flat files (csv, tsv, fwf) into R
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Uses the vroom engine by default in the second edition for significantly quicker data loading compared to base R functions, as highlighted in the performance comparisons.
Provides detailed problem reports when parsing issues arise, helping users debug real-world data inconsistencies efficiently.
Features a uniform naming scheme (e.g., col_names, col_types) and outputs tibbles, ensuring seamless integration with other tidyverse packages like dplyr.
Allows explicit column type specification via col_types, with intelligent guessing as a convenient starting point, reducing manual setup time.
Acknowledged to be sometimes slower than data.table's fread(), particularly on numeric-heavy datasets, which can impact efficiency in big data scenarios.
Tight integration with the tidyverse adds dependency overhead if not already using that ecosystem, and may not align with workflows based on other R paradigms.
Automatic column type guessing, while convenient, can lead to incorrect parsing in messy data, requiring manual intervention for accuracy and reproducibility.