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rPandas - Translating from R to Python's Pandas Package

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.

Last updated

4.78 score 296 downloads

DBmaps - An R Tool for Streamlining Database Joins

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.

Last updated

4.48 score 3 stars 332 downloads

grepreaper - Efficient Data Filtering and Aggregation Using Grep

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.

Last updated

4.04 score 11 scripts 333 downloads

awkreader - File Reading with Pre-Filtering, Pattern Searching, and Distributed Files

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.

Last updated

2.00 score 346 downloads