Explore 26 AI-friendly chart types with comprehensive knowledge base and live examples
A line chart is a statistical chart composed of points and lines in a Cartesian coordinate system, commonly used to represent changes in values over continuous time intervals or ordered categories. In a line chart, the x-axis is typically used for continuous time intervals or ordered categories, while the y-axis is used for quantitative data — negative values are plotted below the x-axis. Lines connect adjacent data points. Line charts are used to analyze trends of things changing over time or ordered categories. Data-wise, a line chart requires a continuous time field or a categorical field and at least one continuous data field.
A column chart is a statistical chart that uses vertical bars to compare numerical values across different categories. The most basic column chart requires one categorical variable and one numerical variable. In a column chart, each entity of the categorical variable is represented as a rectangle (commonly called a "bar"), and the numerical value determines the height of the bar.
A pie chart is a circular statistical chart divided into several sectors. In a pie chart, the arc length (as well as the central angle and area) of each sector represents the proportion of that category to the whole, and these sectors together form a complete circle. The most prominent function of a pie chart is to show proportions. Conventionally, people also use pie charts to compare the sizes of sectors to gain an understanding of the data. However, since humans are less perceptive of angles than lengths, pie charts are often inadequate when exact values need to be expressed (especially when values are close or numerous); bar charts are recommended instead. In terms of data, a pie chart generally requires one categorical data field and one continuous data field. It is worth noting that the data in the categorical field should, in the context of the chart, constitute a whole (e.g., Product A, Product B, and Product C make up the entire product line), rather than being independent and unrelated.
An area chart is a statistical chart that reflects numerical changes as an ordered variable changes, similar in principle to a line chart. The distinctive feature of an area chart is that the area between the line and the independent variable axis is filled with color.
A bar chart is a statistical chart that uses horizontal rectangular bars to compare numerical values across different categories. Unlike column charts, bar chart bars are arranged from left to right rather than from bottom to top. A bar chart also requires a categorical variable and a numerical variable. In a bar chart, each entity of the categorical variable is represented as a horizontal rectangular bar, and the numerical value determines the length of the bar.
A histogram is a chart that displays data distribution, using bars to represent the frequency of data points within a certain range. The height (or length) of each bar represents the number of data points falling within a specific interval, the X-axis represents the range of data values, and the Y-axis represents the frequency or count. Histograms are primarily used to represent the distribution of continuous variables and help analyze the central tendency, dispersion, and shape of data. The difference between a histogram and a bar chart: a histogram reflects data distribution, while a bar chart only compares values. In terms of data structure, a bar chart requires a categorical variable that is discrete (e.g., Class 1, Class 2, Class 3), so there are gaps between bars. But histogram data consists of continuous numerical variables (e.g., scores), so there are no gaps between bars.
A scatter chart is a chart that displays the relationship between two variables. By representing each data point as a point on the chart, a scatter chart can show the correlation or distribution trend between two variables (typically numeric variables). The horizontal and vertical position of each point is determined by the two numeric variables of the data point, with the X-axis and Y-axis representing the two variables respectively.
A word cloud is a visualization method that displays the frequency or weight of words in text data, using different text sizes to represent word frequency. Word clouds help quickly identify the most commonly used or most important words in text data. The size of each word is typically proportional to its frequency — larger fonts represent more frequent or more important words, allowing users to intuitively see how often a word appears in the text. This visual approach enables users to quickly grasp the main content and core themes of the text.
A treemap is a chart used to display hierarchical data structures. It visualizes hierarchical relationships by nesting data in rectangular areas. Each rectangle represents a category, and its size corresponds to the category's value. Treemaps are excellent for visualizing proportions across multiple categories, especially with large datasets, helping to quickly analyze the importance or weight of data.
A dual-axes chart is a combination chart that combines two different chart types, typically displaying a column chart and a line chart together. By using two vertical Y-axes (left and right) in one chart, it corresponds to different numerical dimensions. The column chart shows the magnitude or quantity of one set of data, while the line chart shows the trend of another set of data. Dual-axes charts are ideal for simultaneously displaying trends of different types of data.
A radar chart is a chart that displays multivariate data. It typically has three or more axes radiating from the same center point at equal angular intervals, with each axis representing a quantitative variable, and the points on each axis connected in sequence to form lines or geometric shapes. Radar charts can be used to compare variables or to check for outliers. Additionally, overall numerical comparisons can be made between multiple radar charts or between multiple data layers within a radar chart.
A liquid chart is a visualization that uses a liquid fill effect to represent a numerical proportion. Typically using a circular container as the carrier, it intuitively displays the current progress or proportion of a metric through the liquid level height and wave animation. The liquid height represents the percentage value, and the wave effect enhances visual appeal. It is well-suited for displaying the completion or status of a single metric.
A funnel chart is used to display the progressive loss or conversion of data across multiple stages. It typically uses a funnel shape to represent the data volume at each stage, wide at the top and narrow at the bottom, intuitively reflecting the quantity changes and conversion rates at each step. It is suitable for analyzing bottlenecks and optimization opportunities in processes.
A Sankey diagram is a chart used to visualize the flow of resources such as energy, money, or materials between different nodes. It uses bandwidth to represent flow magnitude, with nodes and flow lines intuitively showing the direction and distribution of each part. It is commonly used in energy flow, fund flow, user path analysis, and other scenarios.
A Venn diagram is a chart that uses overlapping circles to represent set relationships. Each circle represents a set, and the overlapping areas between circles represent the intersection of sets, while non-overlapping parts represent unique elements. Venn diagrams intuitively show intersections, unions, and complements between sets, and are commonly used in set operations, classification analysis, and similar scenarios.
A boxplot is a statistical chart used to display data distribution, central tendency, and outliers. The box represents the interquartile range, the whiskers represent the range of data extremes, and outliers are marked individually. It is well-suited for visually comparing the distribution characteristics of different groups of data.
A violin chart is a statistical chart used to display data distribution and probability density. It uses symmetric density curves to show the distribution shape of data, and can combine boxplot elements to display median and quartiles. It is suitable for intuitively comparing the distribution and density characteristics of different groups of data.
A waterfall chart visualizes the incremental changes from a starting value to an ending result, clearly breaking down positive and negative contributions. By showing an initial value, multiple increases and decreases, and a final total, it helps analyze the impact of each step on the overall result. It is commonly used in financial statements, budget comparisons, and phased metric breakdowns.
A flow diagram visually represents the steps and decision points of a process or system. It shows the entire flow from start to finish. Each node represents a specific step or decision point, while edges represent the sequence and relationships between steps. Edges only need to be named when they represent branching conditions.
A network graph is a diagram that displays relationships (edges) between entities (nodes). Through the connections of nodes and edges, it intuitively represents complex network structures. Each node represents an entity, and each edge represents a relationship or connection between two nodes.
An organization chart visually displays the hierarchical structure and departmental relationships within an organization. It uses nodes and edges to represent different positions, departments, and their reporting relationships. Each node represents a position or department, while edges represent reporting or peer relationships. Presented in a tree structure, the top level is the highest management, expanding downward level by level to individual departments and positions.
An indented tree represents hierarchical relationships through horizontal indentation. Each element occupies one line, with child nodes indented below their parent, and the progressive indentation visually shows node depth and subordination. It is commonly used for file directory structures, knowledge classification systems, organizational hierarchies, and other scenarios that require a clear display of hierarchical relationships.
A mind map uses a central theme as its core, organizing and presenting information through hierarchical branches. It distributes content on both sides of the center point, making efficient use of space while clearly showing the hierarchical relationship between main branches and sub-branches. When text content is complex, mind maps help extract and structure key information, clarifying the relationships between main topics and subtopics.
A table is a structured way to organize data using rows and columns. Each row represents a data entity, and each column represents an attribute or field. Tables can clearly display large amounts of data, making it easy for users to search, compare, and analyze. Tables are commonly used to present structured data such as financial reports, grade sheets, product lists, etc. The core advantage of tables is alignment and comparison. Users can quickly locate data in a specific row or column and make horizontal or vertical comparisons. Tables also support sorting, filtering, and other operations to enhance data usability and interactivity.
A narrative text visualization component built on AntV T8, used to present data insights in the form of natural language narratives, supporting data entities with semantic annotations and inline mini charts embedded in paragraph text.
