dplyr vs jq

dplyr is a free R package for transforming data frames and tibbles through a set of code-based operations. Its main verbs add variables with mutate(), choose variables with select(), filter cases with filter(), summarize values with summarise(), and order rows with arrange(). Combine them with group_by() to apply operations to groups, or use two-table verbs to work with pairs of datasets. The across() helper repeats an operation over several columns, while rowwise() supports row-by-row work. The programming guide covers data masking, tidy selection, and use in functions or loops. For other data settings, dbplyr translates dplyr code into SQL for relational databases; the documentation also lists Arrow, dtplyr, duckplyr, and sparklyr as alternative backends for larger datasets. dplyr runs on Linux, macOS, and Windows and is licensed under MIT. The CRAN package requires R 4.1.0 or later, and installation instructions cover CRAN and a development version from GitHub. The project recommends dplyr to people learning data transformation in R for Data Science.

jq is a free command-line processor for selecting and transforming JSON data. A jq filter takes an input and produces output; filters can be combined to access nested attributes, construct objects, gather results into arrays, or make other transformations. It reads whitespace-separated JSON values and writes serialized results separated by whitespace. Each expression runs on each input value and may produce zero or more outputs. For very large inputs, the --stream option parses incrementally. Output options include compact, raw, ASCII, sorted-key, and colored forms. Written in portable C, jq has no runtime dependencies, and a standalone binary can be copied to another machine of the same type. Standalone executables are available for Linux, macOS, and Windows, with packages listed for Linux distributions and package managers including Homebrew, MacPorts, winget, Scoop, and Chocolatey. A Docker image is also available. Release binaries have SHA-256 checksums, and signed release artifacts use jq release keys. The code is licensed under MIT; the documentation uses CC-BY-3.0.