Search Results for "mind-mapping"

...With ggplot2 you simply provide the data, tell ggplot2 how to map variables to aesthetics, what graphical primitives to use, and it will take care of the rest. ggplot2 is over 10 years old and is used by hundreds of thousands of people all over the world for plotting. In most cases using ggplot2 starts with supplying a dataset and aesthetic mapping (with aes()); adding on layers (like geom_point() or geom_histogram()), scales (like scale_colour_brewer()), and faceting specifications (like facet_wrap()); and finally, coordinating systems. ggplot2 has a rich ecosystem of community-maintained extensions for those looking for more innovation. ggplot2 is a part of the tidyverse, an ecosystem of R packages designed for data science.

purrr enhances R’s functional programming capabilities by providing a consistent set of tools for working with lists and vectors, enabling safer and more expressive iteration compared to base R’s loop functions.

This is an R package designed for producing beautiful and interactive 2D and 3D visualizations — especially maps and terrain renderings — using elevation/gridded data and ray-tracing / hill-shading methods. At its core, rayshader takes a matrix of elevations and applies shading, texture, ambient occlusion, overlays, and light modeling (ray shade, lambertian shading, etc.) to produce realistic relief maps. Users can rotate, zoom, and animate the scenes or script camera trajectories...

The future package in R provides a unified abstraction for asynchronous and/or parallel computation. It allows R expressions to be scheduled for future evaluation, with the result retrieved later, in a way decoupled from the specific backend used. This lets code be written in a way that works with sequential execution, multicore, multisession, cluster, or remote compute backends, without changing the high-level code. It handles automatic exporting of needed global variables/functions,...

This repository hosts the source for Geocomputation with R, an open-source book covering spatial data analysis, visualization, and modeling using R. It teaches how to work with vector and raster data, coordinate systems, mapping, and geocomputation techniques using packages like sf, terra, tmap, and more. Actively maintained and updated for real-world geospatial workflows.

Scala and polyglot Spark library (Scala, PySpark, SparkSQL, ... ) focused on reading OpenStreetMap Pbf files.

...It includes working pipelines for alignment, differential expression, alternative splicing, visualization, and interpretation. It is designed to run in the cloud or local environments, providing introductory material on file formats, reference genomes / annotation, QC, mapping, quantifying expression, visualizing results, etc. The version in that repo is deprecated, but still maintains content for those wishing to follow the original published workflow. Includes instruction on cloud computing basics and using cloud environments for large data processing.