https://akshat09867.r-universe.devRecent package updates in akshat09867R-universehttps://github.com/akshat09867.pnghttps://akshat09867.r-universe.devThu, 03 Sep 2026 12:20:11 GMTcodingmaster902@gmail.com (Akshat Maurya)Provides high-performance tools for out-of-core text processing and data ingestion by leveraging system 'AWK' utilities. Allows users to count records, filter rows, and compute streaming aggregations—such as group-by means, streaming medians, standard deviations, and correlations—directly on disk prior to reading data into R. By delegating line-by-line filtering and summarization to system-level 'AWK' commands and streaming results back through data.table::fread(), the package significantly reduces memory footprint and execution times when working with large individual files or multi-file directory structures.https://github.com/r-universe/akshat09867/actions/runs/37194384696Thu, 03 Sep 2026 12:20:11 GMTawkreader0.1.0successhttps://akshat09867.r-universe.devhttps://github.com/cran/awkreaderIntroduction_to_awk.RmdIntroduction_to_awk.htmlawkreader: Pre-Filtering and Pattern Searching for Combined File Reading2026-09-03 12:20:112026-09-03 12:20:11codingmaster902@gmail.com (Akshat Maurya)Simplifies and automates the process of exploring and merging data from relational databases. This package allows users to discover table relationships, create a map of all possible joins, and generate executable plans to merge data based on a structured metadata framework.https://github.com/r-universe/akshat09867/actions/runs/36693579748Mon, 31 Aug 2026 06:06:20 GMTDBmaps0.1.1successhttps://akshat09867.r-universe.devhttps://github.com/akshat09867/dbmapsdiscovering-join-paths.Rmddiscovering-join-paths.htmlAutomated Join Path Discovery2025-07-01 05:54:062025-07-14 05:54:25join-plan.Rmdjoin-plan.htmlCreating Execution Plans for Data Joins2025-07-31 05:28:402025-08-06 08:44:06defining-table-metadata.Rmddefining-table-metadata.htmlDefining Table Metadata with table_info()2025-06-09 05:59:302025-06-24 04:51:31generating-aggregation-code.Rmdgenerating-aggregation-code.htmlGenerating Aggregation Code from Metadata2025-06-17 05:59:492025-06-17 05:59:49DBmaps-introduction.RmdDBmaps-introduction.htmlIntroduction to DBmaps2025-05-31 05:36:142025-08-28 06:08:05codingmaster902@gmail.com (Akshat Maurya)Provides an R interface to Python's 'pandas' library using non-standard evaluation. Users can write R code (e.g., rp_filter(), rp_select(), rp_mutate()) that is translated into pandas commands and executed via 'reticulate'. Supports chaining, grouping, and 'summarisation', and includes a 'table_name' parameter to generate 'copy-pasteable' Python code. Ideal for leveraging pandas' speed and flexibility within the R ecosystem.https://github.com/r-universe/akshat09867/actions/runs/39008457333Wed, 29 Apr 2026 04:14:29 GMTrPandas0.1.4successhttps://akshat09867.r-universe.devhttps://github.com/akshat09867/rpandasintroduction-to-rPandas.Rmdintroduction-to-rPandas.htmlIntroduction-to-rPandas2025-11-11 09:26:542026-04-21 11:44:15codingmaster902@gmail.com (Akshat Maurya)Provides an interface to the system-level 'grep' utility for efficiently reading, filtering, and aggregating data from multiple flat files. By pre-filtering data at the command line before it enters the R environment, the package reduces memory overhead and improves ingestion speed. Includes functions for counting records across large file systems and supports recursive directory searching.https://github.com/r-universe/akshat09867/actions/runs/38066789244Sun, 29 Mar 2026 05:36:32 GMTgrepreaper0.1.1successhttps://akshat09867.r-universe.devhttps://github.com/akshat09867/grepreaperIntroduction-to-grepreaper.RmdIntroduction-to-grepreaper.htmlIntroduction to grepreaper2026-01-14 05:32:232026-01-15 13:43:58