Examples: visualization, C++, networks, data cleaning, html widgets, ropensci.

Found 2489 packages in 0.12 seconds

plot.matrix — by Sigbert Klinke, 4 years ago

Visualizes a Matrix as Heatmap

Visualizes a matrix object plainly as heatmap. It provides S3 functions to plot simple matrices and loading matrices.

naniar — by Nicholas Tierney, 2 years ago

Data Structures, Summaries, and Visualisations for Missing Data

Missing values are ubiquitous in data and need to be explored and handled in the initial stages of analysis. 'naniar' provides data structures and functions that facilitate the plotting of missing values and examination of imputations. This allows missing data dependencies to be explored with minimal deviation from the common work patterns of 'ggplot2' and tidy data. The work is fully discussed at Tierney & Cook (2023) .

DendSer — by Catherine Hurley, 3 months ago

Dendrogram Seriation: Ordering for Visualisation

Re-arranges a dendrogram to optimize visualisation-based cost functions. The methods implemented here are described in "Advances in Dendrogram Seriation for Application to Visualization", Journal of Computational and Graphical Statistics (2015) D. Earle and C.B. Hurley .

bipartite — by Carsten F. Dormann, 2 months ago

Visualising Bipartite Networks and Calculating Some (Ecological) Indices

Functions to visualise webs and calculate a series of indices commonly used to describe pattern in (ecological) webs. It focuses on webs consisting of only two levels (bipartite), e.g. pollination webs or predator-prey-webs. Visualisation is important to get an idea of what we are actually looking at, while the indices summarise different aspects of the web's topology.

UpSetR — by Jake Conway, 7 years ago

A More Scalable Alternative to Venn and Euler Diagrams for Visualizing Intersecting Sets

Creates visualizations of intersecting sets using a novel matrix design, along with visualizations of several common set, element and attribute related tasks (Conway 2017) .

profvis — by Hadley Wickham, 2 years ago

Interactive Visualizations for Profiling R Code

Interactive visualizations for profiling R code.

NeuralNetTools — by Marcus W. Beck, 4 years ago

Visualization and Analysis Tools for Neural Networks

Visualization and analysis tools to aid in the interpretation of neural network models. Functions are available for plotting, quantifying variable importance, conducting a sensitivity analysis, and obtaining a simple list of model weights.

move — by Bart Kranstauber, 4 months ago

Visualizing and Analyzing Animal Track Data

Contains functions to access movement data stored in 'movebank.org' as well as tools to visualize and statistically analyze animal movement data, among others functions to calculate dynamic Brownian Bridge Movement Models. Move helps addressing movement ecology questions.

mlr3viz — by Marc Becker, 3 months ago

Visualizations for 'mlr3'

Visualization package of the 'mlr3' ecosystem. It features plots for mlr3 objects such as tasks, learners, predictions, benchmark results, tuning instances and filters via the 'autoplot()' generic of 'ggplot2'. The package draws plots with the 'viridis' color palette and applies the minimal theme. Visualizations include barplots, boxplots, histograms, ROC curves, and Precision-Recall curves.

shapviz — by Michael Mayer, 7 months ago

SHAP Visualizations

Visualizations for SHAP (SHapley Additive exPlanations), such as waterfall plots, force plots, various types of importance plots, dependence plots, and interaction plots. These plots act on a 'shapviz' object created from a matrix of SHAP values and a corresponding feature dataset. Wrappers for the R packages 'xgboost', 'lightgbm', 'fastshap', 'shapr', 'h2o', 'treeshap', 'DALEX', and 'kernelshap' are added for convenience. By separating visualization and computation, it is possible to display factor variables in graphs, even if the SHAP values are calculated by a model that requires numerical features. The plots are inspired by those provided by the 'shap' package in Python, but there is no dependency on it.