# cxli233/friendsdontletfriends

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6,994 stars · 284 forks · R · mit

## Links

- GitHub: https://github.com/cxli233/FriendsDontLetFriends
- awesome-repositories: https://awesome-repositories.com/repository/cxli233-friendsdontletfriends.md

## Topics

`data-visualization` `r`

## Description

FriendsDontLetFriends 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 interpretability of relationship data in network graphs.

The framework covers a broad range of visualization capabilities, including data distribution analysis, proportional data representation, and multifactorial experiment analysis. It focuses on applying best practices such as using faceting and grouping for complex results and employing colorblind-friendly palettes for numerical data.

## Tags

### Data & Databases

- [Data Visualization](https://awesome-repositories.com/f/data-databases/data-analysis-visualization/visualization-frameworks-libraries/data-visualization.md) — Provides a comprehensive framework of scripts and guidelines for creating accurate scientific data visualizations. ([source](https://github.com/cxli233/FriendsDontLetFriends/blob/main/README.md))
- [Visualization Pitfall Analysis](https://awesome-repositories.com/f/data-databases/data-analysis-visualization/visualization-frameworks-libraries/data-visualization/visualization-pitfall-analysis.md) — Identifies common pitfalls in data visualization through a curated collection of examples and scripts. ([source](https://github.com/cxli233/FriendsDontLetFriends#readme))
- [Automated Layout Algorithms](https://awesome-repositories.com/f/data-databases/automated-graph-layouts/automated-layout-algorithms.md) — Utilizes automated layout algorithms to arrange network nodes and optimize the interpretability of relationship data.
- [Distribution Analysis Plots](https://awesome-repositories.com/f/data-databases/box-plots/distribution-analysis-plots.md) — Offers guidelines and scripts for selecting the most accurate distribution plots based on sample size and modality.
- [Distribution Plot Selection](https://awesome-repositories.com/f/data-databases/box-plots/distribution-plot-selection.md) — Provides a framework for choosing between violin plots, histograms, or box plots based on sample size and data modality.
- [Data Analysis & Visualization](https://awesome-repositories.com/f/data-databases/data-analysis-visualization.md) — Represents complex experimental results using grouping and faceting to avoid ineffective aggregated bar charts. ([source](https://github.com/cxli233/FriendsDontLetFriends#readme))
- [Stacked](https://awesome-repositories.com/f/data-databases/data-analysis-visualization/analytical-platforms-engines/data-analysis-tools/bar-charts/stacked.md) — Provides proportional stacked bar representations to facilitate more accurate fractional data comparisons than circular charts.
- [Proportional Data Plots](https://awesome-repositories.com/f/data-databases/data-analysis-visualization/visualization-frameworks-libraries/data-visualization/proportional-data-plots.md) — Provides stacked bar plots for accurate comparison of fractional data as an alternative to pie charts. ([source](https://github.com/cxli233/FriendsDontLetFriends#readme))
- [Visualization Best Practices](https://awesome-repositories.com/f/data-databases/data-analysis-visualization/visualization-frameworks-libraries/data-visualization/visualization-best-practices.md) — Implements effective visual encoding for various data types using scripts that avoid common graphing errors. ([source](https://github.com/cxli233/FriendsDontLetFriends/tree/main/Scripts))
- [Faceted Plotting Systems](https://awesome-repositories.com/f/data-databases/data-analysis-visualization/visualization-frameworks-libraries/statistical-plotting-libraries/faceted-plotting-systems.md) — Utilizes faceting systems to organize complex multifactorial experimental results into multi-panel layouts. ([source](https://github.com/cxli233/FriendsDontLetFriends/blob/main/README.md))
- [Automated Graph Layouts](https://awesome-repositories.com/f/data-databases/automated-graph-layouts.md) — Implements various spatial layout algorithms to improve the interpretability of relationship data in network graphs.

### Scientific & Mathematical Computing

- [Scientific Visualizations](https://awesome-repositories.com/f/scientific-mathematical-computing/scientific-visualizations.md) — Provides a comprehensive framework for creating accurate scientific charts that avoid common representation mistakes.
- [Color Palette Selection](https://awesome-repositories.com/f/scientific-mathematical-computing/color-palette-selection.md) — Provides guidelines and scripts for implementing colorblind-friendly palettes and unidirectional gradients in scientific plots.
- [Experimental Data Visualizers](https://awesome-repositories.com/f/scientific-mathematical-computing/experimental-data-visualizers.md) — Represent complex experimental results using grouping and faceting to avoid misleading aggregated bar charts.
- [Group Comparison Visualizations](https://awesome-repositories.com/f/scientific-mathematical-computing/group-comparison-visualizations.md) — Provides visual methods for comparing means and dispersion across groups while avoiding the use of misleading bar plots. ([source](https://github.com/cxli233/FriendsDontLetFriends#readme))
- [Heatmap Dimension Reordering](https://awesome-repositories.com/f/scientific-mathematical-computing/heatmap-dimension-reordering.md) — Implements mechanisms to rearrange heatmap rows and columns based on statistical properties to reveal hidden data patterns.
- [Multifactorial Data Faceting](https://awesome-repositories.com/f/scientific-mathematical-computing/multifactorial-data-faceting.md) — Organizes multifactorial experimental results into grids of subplots to avoid the use of misleading aggregated bar charts.
- [Multifactorial Experimental Visualizations](https://awesome-repositories.com/f/scientific-mathematical-computing/multifactorial-experimental-visualizations.md) — Uses grouping and faceting to represent complex experimental results without using misleading aggregated bar charts.
- [Network Graph Layouts](https://awesome-repositories.com/f/scientific-mathematical-computing/network-graph-layouts.md) — Optimizes the interpretability of relationship data in network graphs by testing different spatial layout algorithms. ([source](https://github.com/cxli233/FriendsDontLetFriends#readme))
- [Plotting Scripts](https://awesome-repositories.com/f/scientific-mathematical-computing/plotting-scripts.md) — Generates scientific charts by applying a set of predefined coding rules to avoid common data representation errors.
- [Proportional Data Plots](https://awesome-repositories.com/f/scientific-mathematical-computing/proportional-data-plots.md) — Implements stacked bar plots for fractional data to facilitate more accurate comparisons than circular charts. ([source](https://github.com/cxli233/FriendsDontLetFriends/tree/main))
- [Statistical Dimension Reordering](https://awesome-repositories.com/f/scientific-mathematical-computing/statistical-dimension-reordering.md) — Rearranges heatmap rows and columns based on statistical properties to expose hidden patterns in large datasets.
- [Visual Encoding Guidelines](https://awesome-repositories.com/f/scientific-mathematical-computing/visual-encoding-guidelines.md) — Translates numerical data into visual elements using predefined coding guidelines to prevent common representation mistakes.
- [Factor-Level Analysis](https://awesome-repositories.com/f/scientific-mathematical-computing/factor-level-analysis.md) — Analyzes response variable ranges across factor levels to prevent the omission of significant effects in multifactorial data.
- [Factor-Level Range Analysis](https://awesome-repositories.com/f/scientific-mathematical-computing/factor-level-range-analysis.md) — Analyzes data ranges at each factor level to prevent missing significant effects in multifactorial experiments. ([source](https://github.com/cxli233/FriendsDontLetFriends/tree/main))
- [Response Variable Scaling](https://awesome-repositories.com/f/scientific-mathematical-computing/matrix-factorization-toolkits/scale-factor-calculators/response-variable-scaling.md) — Scales response variables by checking ranges at each factor level to prevent missing significant effects. ([source](https://github.com/cxli233/FriendsDontLetFriends/blob/main/README.md))
- [Response Variable Analysis](https://awesome-repositories.com/f/scientific-mathematical-computing/response-variable-analysis.md) — Analyzes response variables at each factor level to ensure significant effects remain visible during evaluation. ([source](https://github.com/cxli233/FriendsDontLetFriends#readme))

### Artificial Intelligence & ML

- [Data Representation](https://awesome-repositories.com/f/artificial-intelligence-ml/data-representation.md) — Provides best practices for representing fractional population data using stacked bars for higher accuracy.
- [Heuristic Selection Logic](https://awesome-repositories.com/f/artificial-intelligence-ml/model-architecture-selection/heuristic-selection-logic.md) — Employs heuristic selection logic to determine the best distribution plot based on dataset statistics and sample size.
- [Graph-Based Optimization](https://awesome-repositories.com/f/artificial-intelligence-ml/portfolio-optimization-algorithms/graph-based-optimization.md) — Optimizes the visual arrangement of network nodes and connections to make relationship data easier to interpret.

### Part of an Awesome List

- [Heatmap Visualization](https://awesome-repositories.com/f/awesome-lists/data/heatmap-visualization.md) — Optimizes heatmap interpretability by reordering rows and columns and adjusting color scales for outliers. ([source](https://github.com/cxli233/FriendsDontLetFriends/blob/main/README.md))
- [Dimension Reordering](https://awesome-repositories.com/f/awesome-lists/data/heatmap-visualization/dimension-reordering.md) — Implements dimension reordering and color scale configuration to expose hidden patterns in large datasets.
- [Heatmap Layout Optimization](https://awesome-repositories.com/f/awesome-lists/data/heatmap-visualization/heatmap-layout-optimization.md) — Optimizes heatmaps by strategically reordering rows and columns and managing data outliers to reveal hidden patterns. ([source](https://github.com/cxli233/FriendsDontLetFriends#readme))
- [Color Palettes](https://awesome-repositories.com/f/awesome-lists/devtools/color-palettes.md) — Configures unidirectional gradients and colorblind-safe palettes to ensure numerical data is interpreted accurately. ([source](https://github.com/cxli233/FriendsDontLetFriends#readme))
- [Scientific Color Scales](https://awesome-repositories.com/f/awesome-lists/devtools/color-palettes/scientific-color-scales.md) — Provides guidelines and scripts for configuring colorblind-safe palettes and unidirectional gradients to ensure accurate numerical data interpretation. ([source](https://github.com/cxli233/FriendsDontLetFriends/blob/main/README.md))
- [Dispersion Plots](https://awesome-repositories.com/f/awesome-lists/devtools/plotting-and-visualization/dispersion-plots.md) — Provides means and data dispersion visualizations that avoid the use of misleading bar plots. ([source](https://github.com/cxli233/FriendsDontLetFriends/tree/main))
- [Visualization Guides](https://awesome-repositories.com/f/awesome-lists/devtools/visualization-guides.md) — Provides instructional guides and curated examples to identify and avoid common data visualization mistakes. ([source](https://github.com/cxli233/FriendsDontLetFriends/tree/main))
- [Layout Optimization Tools](https://awesome-repositories.com/f/awesome-lists/data/heatmap-visualization/layout-optimization-tools.md) — Provides tools for revealing hidden patterns via dimension reordering and outlier management in heatmaps.
- [Plotting and Visualization](https://awesome-repositories.com/f/awesome-lists/devtools/plotting-and-visualization.md) — Organizes population or community structure visualizations by optimizing the grouping and ordering of samples. ([source](https://github.com/cxli233/FriendsDontLetFriends/blob/main/README.md))
- [Stacked Bar Plot Optimization](https://awesome-repositories.com/f/awesome-lists/devtools/plotting-and-visualization/stacked-bar-plot-optimization.md) — Optimizes proportional data visualizations by grouping and reordering samples by abundance or class. ([source](https://github.com/cxli233/FriendsDontLetFriends/blob/main/Scripts/stacked_bars_optimization.Rmd))
- [Data Visualization](https://awesome-repositories.com/f/awesome-lists/data/data-visualization.md) — Collection of bad visualization practices and alternatives.

### Graphics & Multimedia

- [Data Plotting Workflows](https://awesome-repositories.com/f/graphics-multimedia/data-plotting-workflows.md) — Implements a methodology for selecting appropriate distribution plots and color scales for complex scientific data.
- [Layout Algorithms](https://awesome-repositories.com/f/graphics-multimedia/visualization-mapping/layout-algorithms.md) — Implements multiple spatial layout algorithms to optimize the interpretability of relationship data in network graphs.

### User Interface & Experience

- [Statistical Distribution Visualizers](https://awesome-repositories.com/f/user-interface-experience/data-visualization-tools/data-visualization/charting-frameworks/immediate-mode-plotting-libraries/statistical-distribution-visualizers.md) — Selects appropriate violin plots, histograms, or raw data points based on sample size and distribution shape. ([source](https://github.com/cxli233/FriendsDontLetFriends/tree/main))
- [Statistical Grid Reordering](https://awesome-repositories.com/f/user-interface-experience/multi-item-drag-operations/swap-based-reordering/grid-based-reordering/statistical-grid-reordering.md) — Reorders heatmap rows and columns based on practical meanings or statistics to make hidden data patterns more discernible. ([source](https://github.com/cxli233/FriendsDontLetFriends/blob/main/Heatmap_tutorial.md))
- [Faceting Layout Grids](https://awesome-repositories.com/f/user-interface-experience/grid-layouts/faceting-layout-grids.md) — Implements layout grids that partition complex experimental results into subplots to prevent data aggregation errors.