2 repository-uri
Awesome GitHub RepositoriesDistribution Plot Selection
Logic for choosing the most appropriate distribution visualization based on data modality and sample size.
Distinct from Box Plots: Focuses on the selection criteria between different plot types (violin, box, histogram) rather than a specific plot type.
Explore 2 awesome GitHub repositories matching data & databases · Distribution Plot Selection. Refine with filters or upvote what's useful.
Awesome Distribution Plot Selection GitHub Repositories
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- cxli233/friendsdontletfriends
cxli233/FriendsDontLetFriends
6,994Vezi pe GitHubFriendsDontLetFriends is a scientific data visualization guide and framework designed to help users create accurate plots while avoiding common data representation mistakes. It provides a collection of scripts and guidelines for selecting distribution plots, color scales, and layouts that accurately represent complex experimental data. The project distinguishes itself through specialized toolkits for revealing hidden patterns in large datasets. It includes systems for heatmap optimization via dimension reordering and outlier management, as well as spatial layout algorithms to improve the inte
Provides a framework for choosing between violin plots, histograms, or box plots based on sample size and data modality.
Rdata-visualizationr - mne-tools/mne-python
mne-tools/mne-python
3,243Vezi pe GitHubMNE-Python is an open-source Python library for processing, visualizing, and analyzing human neurophysiological data, including MEG, EEG, sEEG, ECoG, and NIRS recordings. It provides a comprehensive framework for loading data from over 30 proprietary file formats into a common hierarchical FIF data structure, and represents all time-series data as NumPy arrays for seamless integration with the scientific Python ecosystem. The library is built around object-oriented data containers that encapsulate raw, epoched, evoked, and source data with built-in preprocessing and visualization methods. The
Generates topographic maps of the scalp field distribution at specified time points, with configurable averaging durations.
Pythonecogeegelectrocorticography
