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Arc Diagram
Visualizes connections between nodes placed along a single axis using semicircular arcs.
Explore 22+ scientific visualization types. Each chart includes Python code examples, usage tips, and interactive demos powered by Matplotlib, Plotly, Seaborn, and more.
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Visualizes connections between nodes placed along a single axis using semicircular arcs.
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Displays quantitative data over time, emphasizing the magnitude of change with filled regions.
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Compares categorical data using rectangular bars with heights proportional to values.
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Displays data distribution using quartiles, median, and outliers in a standardized format.
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A scatter plot where bubble size represents a third dimension of data.
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A map displaying circles sized proportionally to values over geographic regions.
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Compares a primary measure against targets with qualitative performance ranges.
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Visualizes daily data organized by calendar format with color-coded intensity.
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Displays OHLC (Open, High, Low, Close) price movements for financial analysis.

A thematic map where regions are shaded in proportion to statistical values.
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Displays hierarchical data as nested circles with size proportional to values.

Shows connections and routes between geographic points on a map.
Illustrates a project schedule with tasks shown as horizontal bars over time.
Represents data values as colors in a two-dimensional matrix format.
Displays the distribution of numerical data by grouping values into bins.
Displays data points connected by straight line segments to show trends over time.
Displays multivariate data on axes starting from a central point.
Flow diagram where arrow widths are proportional to flow quantities.
Displays values for two variables as points on a Cartesian coordinate system.
Displays hierarchical data as nested rectangles sized by value.
Combines box plots with kernel density to show distribution shape across groups.
Visualizes text data with word size proportional to frequency or importance.
This comprehensive chart gallery showcases over 22 visualization types commonly used in data science, scientific research, and business intelligence. Each chart type includes detailed descriptions, Python code examples, and practical use cases.
Whether you need to create bar charts, scatter plots, heatmaps, geographic maps, or advanced visualizations like Sankey diagrams and treemaps, Plotivy supports them all with AI-powered code generation.
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