4 个仓库
Awesome GitHub RepositoriesMissing Value Visual Representations
Controls how null, NaN, and missing values are displayed in chart marks and scales.
Distinct from Null Handling Strategies: No existing candidate covers visual representation of missing data; candidates focus on data cleaning.
Explore 4 awesome GitHub repositories matching data & databases · Missing Value Visual Representations. Refine with filters or upvote what's useful.
Awesome Missing Value Visual Representations GitHub Repositories
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- leeoniya/uplot
leeoniya/uPlot
10,266在 GitHub 上查看uPlot 是一个高性能 Canvas 时间序列图表库，旨在以高帧率渲染数百万个数据点。它作为一个高频数据可视化工具和实时数据流绘图仪，利用 HTML5 Canvas API 在绘制大型时间数据集时保持响应性。 该项目的独特之处在于其基于插件的可视化框架，允许自定义渲染器创建专门的视觉效果，如热力图和箱线图。它还作为一个交互式金融图表工具，专门支持 OHLC 图表、柱状图和面积带。 该库涵盖了广泛的功能，包括具有线性、对数和均匀刻度的轴管理，以及通过缩放、平移和跨多个链接视图的同步光标进行的交互式导航。它提供了用于动态数据流式传输的滑动窗口缓冲系统，以及用于管理缺失数据和时区感知处理的工具。附加功能包括堆叠图表聚合以及将可视化导出为静态图像格式的能力。
Controls how null values and data gaps are visually represented using sparse alignment and timezone-aware processing.
JavaScript - vega/vega-lite
vega/vega-lite
5,216在 GitHub 上查看Vega-Lite is a high-level declarative language for specifying interactive, multi-view visualizations. It compiles a concise JSON specification into a full Vega visualization, automatically inferring scales, axes, and legends from encoding declarations. The grammar-of-graphics encoding maps data fields to visual channels such as position, color, size, and shape, while a multi-view composition grammar enables layered, faceted, concatenated, and repeated layouts. Reactive parameter binding links named parameters to input widgets, selections, and expressions for dynamic updates. The project suppo
Controls how null and NaN values are represented in marks and scales, with filtering or custom output.
TypeScriptchartsdeclarative-languageplot - residentmario/missingno
ResidentMario/missingno
4,209在 GitHub 上查看missingno 是一个用于缺失数据模式可视化和分析的 Python 库。它提供了一套工具来分析数据集的完整性、映射数据缺口并量化变量中空值的数量。 该库通过空值相关性分析器和分层数据聚类工具脱颖而出。这些组件允许通过测量一个变量的缺失如何与另一个变量的缺失相关联，来检测系统性依赖和趋势。 该工具集涵盖了更广泛的数据质量审计和探索性分析功能。它包括使用线性和对数刻度进行列空值汇总的功能，以及用于识别记录中系统性缺口的基于矩阵的映射。
Provides a visual summary of missing value volumes per column using linear and logarithmic scaling.
Pythondata-analysisdata-visualizationmissing-data - f5/unovis
f5/unovis
2,730在 GitHub 上查看Unovis is a modular SVG and Canvas data visualization library used to build interactive charts, maps, and network graphs. It provides a framework-agnostic set of primitives for creating data dashboards and specialized visualizations. The library is distinguished by its dedicated toolkits for different visualization domains, including an XY charting library for coordinated plots, a network graph framework for relational data, and a geospatial visualization toolkit for TopoJSON-based mapping. Its capability surface covers a wide range of data representations, including linear, area, and bar ch
Controls how missing or null data points are visually represented in charts using gaps or dashed lines.
TypeScriptangularchartsdata-visualization
