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Arc Diagram
Visualizes connections between nodes placed along a single axis using semicircular arcs.
Explore 57+ 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 diagram used to visually organize information showing relationships among concepts.
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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.

Displays inter-relationships between data in a matrix using ribbons connecting arcs.

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.
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Visualizes the distribution of data over a continuous interval using kernel density estimation.

A pie chart variant with a blank center for additional information.
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Uses dots to show the presence or density of features at geographic locations.

Shows data as a grid of dots where each dot represents a unit of data.

Graphical representations of the variability of data indicating error or uncertainty in measurements.

A diagram representing the sequence of steps in a process or workflow.

Shows movement of objects, people, or information between geographic areas.

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.

Custom diagrams using drawing primitives to illustrate specific concepts.

A financial chart for tracking price movements that filters out noise and highlights trend reversals.

Displays data points connected by straight line segments to show trends over time.

A variable-width bar chart where both width and height of segments are proportional to values.

A bar chart where multiple datasets are displayed side-by-side for direct comparison.

A graph showing how different entities are connected through relationships.

A polar area diagram combining properties of radar charts and bar charts.

A chord diagram where connections are shown as lines rather than ribbons.

Illustrates movements in the price of a financial instrument showing open, high, low, and close values.

Visualizes high-dimensional data by plotting each variable on a separate vertical axis.

A charting technique focusing on price movements without regard to time.

Shows the distribution of various age groups in a population, split by gender.

Uses shapes with areas proportional to values for visual comparison.

Displays multivariate data on axes starting from a central point.

A bar chart plotted on a polar coordinate system with bars radiating from the center.

Similar to a radial bar chart but with columns extending from the center outward.

Flow diagram where arrow widths are proportional to flow quantities.

Displays values for two variables as points on a Cartesian coordinate system.

Displays the range between minimum and maximum values as floating bars.

Plots time-series data along a spiral to highlight periodic patterns.

An area chart where multiple series are stacked on top of one another.

A bar chart where parts of the total are stacked on top of each other.
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A text-based display showing data distribution while preserving individual values.

A stacked area graph displaced around a central axis for an organic, flowing shape.

Displays hierarchical data in concentric rings radiating from a center.

A simple table used to count and display the frequency of occurrences.

A formatted table showing a schedule of events with times and details.

A display of events in chronological order along a time axis.

Represents hierarchical structures in a branching tree format.

Displays hierarchical data as nested rectangles sized by value.

Uses circles to show relationships and overlaps between sets of data.

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 57 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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