Data visualization method and device and electronic equipment

Abstract

The invention discloses a data visualization method and device and electronic equipment, and relates to the technical field of data processing. The method comprises the steps of generating a two-dimensional scatter diagram corresponding to to-be-visualized data in response to an operation that a user selects to pay attention to first attribute information of the to-be-visualized data; the data points in the two-dimensional scatter diagram form different data point clusters according to the first attribute information; and in response to an operation that a user selects to pay attention to second attribute information of the to-be-visualized data, taking the second attribute information as Z-axis representation of a three-dimensional space coordinate system, and generating and displaying a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter diagram.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and in particular, to a data visualization method, apparatus, and electronic device. Background Art

[0002] In the context of the big data era, especially during the training process of large models, in the face of massive and multi-dimensional training data, data viewing, data matching, and data analysis have become key challenges. Current data visualization means are limited to separately displaying information of each dimension in the form of a list or statistical chart, thus restricting users from deeply understanding and gaining insights into the data from the overall distribution level of each dimension. Summary of the Invention

[0003] In view of the above technical problems, embodiments of this application provide a data visualization method, apparatus, and electronic device.

[0004] The technical solution of the embodiments of this application is implemented as follows:

[0005] In a first aspect, embodiments of this application provide a data visualization method, including:

[0006] In response to an operation where a user selects to focus on first attribute information of data to be visualized, generating a two-dimensional scatter plot corresponding to the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information;

[0007] In response to an operation where a user selects to focus on second attribute information of the data to be visualized, using the second attribute information as the Z-axis representation in a three-dimensional space coordinate system, and generating and displaying a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0008] In some embodiments, the step of in response to an operation where a user selects to focus on second attribute information of the data to be visualized, using the second attribute information as the Z-axis representation in a three-dimensional space coordinate system, and generating and displaying a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot includes:

[0009] In response to an operation where a user selects to focus on second attribute information of the data to be visualized, sampling the target data based on the joint distribution of the first attribute information and the second attribute information in the target data to obtain sampled data; the target data is the data to be visualized corresponding to each data point in the two-dimensional scatter plot;

[0010] Using the second attribute information as the Z-axis representation in the three-dimensional space coordinate system, and generating and displaying a three-dimensional view corresponding to the sampled data in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0011] In some embodiments, generating the two-dimensional scatter plot corresponding to the data to be visualized in response to an operation of a user selecting to focus on first attribute information of the data to be visualized includes:

[0012] In response to an operation of a user selecting to focus on first attribute information of the data to be visualized, fusing the data to be visualized with the first attribute information to obtain fused data;

[0013] After reducing the dimensionality of the fused data to two-dimensional data, generating the two-dimensional scatter plot based on the two-dimensional data;

[0014] Wherein, the two-dimensional coordinates of each data point in the two-dimensional scatter plot can reflect the distribution characteristics of the first attribute information.

[0015] In some embodiments, the data visualization method further includes:

[0016] Determining the density center points of each data point cluster in the three-dimensional view;

[0017] Based on the density center points of each data point cluster, determining a target display perspective;

[0018] Based on the target display perspective, adjusting the display effect of the three-dimensional view to ensure that each data point cluster in the three-dimensional view is in a state where it can be observed at the target display perspective.

[0019] In some embodiments, the data visualization method further includes:

[0020] In response to an operation of a user selecting a Z-axis coordinate value range for the Z-axis of the three-dimensional space coordinate system, determining a target cross-sectional screenshot of the three-dimensional view based on the Z-axis coordinate value range; the target cross-sectional screenshot is parallel to the X-axis and the Y-axis of the three-dimensional space coordinate system and perpendicular to the Z-axis;

[0021] Generating and displaying a two-dimensional view corresponding to the target cross-sectional screenshot.

[0022] In some embodiments, the data visualization method further includes:

[0023] In response to an operation of a mouse hovering over any one first data point in the two-dimensional view, determining a second data point in the three-dimensional view; the second data point corresponds to the first data point;

[0024] Highlighting the second data point.

[0025] In some embodiments, the data visualization method further includes:

[0026] In response to an operation of hovering the mouse over any one of the third data points in the two-dimensional view, all the attribute information of the third data point is displayed in the two-dimensional view.

[0027] In some embodiments, before generating the two-dimensional scatter plot corresponding to the data to be visualized in response to an operation where the user selects to focus on the first attribute information of the data to be visualized, the method further includes:

[0028] Performing data analysis on the data to be visualized to obtain at least two attribute information of the data to be visualized; the at least two attribute information includes the first attribute information and the second attribute information;

[0029] Displaying the at least two attribute information through a user interaction interface for the user to select the attribute information that the user needs to focus on from the at least two attribute information.

[0030] In a second aspect, an embodiment of the present application provides a data visualization device, including:

[0031] A first response module, configured to generate a two-dimensional scatter plot corresponding to the data to be visualized in response to an operation where the user selects to focus on the first attribute information of the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information;

[0032] A second response module, configured to, in response to an operation where the user selects to focus on the second attribute information of the data to be visualized, use the second attribute information as the Z-axis representation of a three-dimensional space coordinate system, and generate and display a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0033] In a third aspect, an embodiment of the present application provides an electronic device, including a memory and a processor, where the memory is used to store executable data instructions; when the processor executes the executable data instructions stored in the memory, it implements the data visualization method as described in the first aspect. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required to be used in the embodiments. Obviously, the drawings described below are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0035] Figure 1 It is one of the flow diagrams of a data visualization method provided by an embodiment of the present application;

[0036] Figure 2A schematic diagram of a two-dimensional scatter plot provided by an embodiment of the present application;

[0037] Figure 3 One of the schematic diagrams of a three-dimensional view provided by an embodiment of the present application;

[0038] Figure 4 Another schematic diagram of a three-dimensional view provided by an embodiment of the present application;

[0039] Figure 5 Another schematic diagram of the flowchart of a data visualization method provided by an embodiment of the present application;

[0040] Figure 6 Another schematic diagram of the flowchart of a data visualization method provided by an embodiment of the present application;

[0041] Figure 7 One of the schematic diagrams of a target cross-sectional view of a three-dimensional view provided by an embodiment of the present application;

[0042] Figure 8 Another schematic diagram of a target cross-sectional view of a three-dimensional view provided by an embodiment of the present application;

[0043] Figure 9 A schematic diagram of the corresponding two-dimensional view of the target cross-sectional view of a three-dimensional view provided by an embodiment of the present application;

[0044] Figure 10 Another schematic diagram of the flowchart of a data visualization method provided by an embodiment of the present application;

[0045] Figure 11 Another schematic diagram of the flowchart of a data visualization method provided by an embodiment of the present application;

[0046] Figure 12 Another schematic diagram of the flowchart of a data visualization method provided by an embodiment of the present application;

[0047] Figure 13 Another schematic diagram of the flowchart of a data visualization method provided by an embodiment of the present application;

[0048] Figure 14 Another schematic diagram of the flowchart of a data visualization method provided by an embodiment of the present application;

[0049] Figure 15 A schematic diagram of the structure of a data visualization device provided by an embodiment of the present application;

[0050] Figure 16 A schematic diagram of the physical structure of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0051] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this application. Apparently, the described embodiments are some but not all of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of this application without creative efforts shall fall within the scope of protection of the embodiments of this application.

[0052] It should be noted that in the description of the embodiments of this application, the terms "first", "second", etc. are used to distinguish similar objects and are not used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances so that the embodiments of this application can be implemented in an order other than those illustrated or described here, and the objects distinguished by "first", "second", etc. are usually of the same category, and the number of objects is not limited. For example, the first object can be one or multiple.

[0053] Next, with reference to the accompanying drawings in the embodiments of this application, a data visualization method, device, and electronic device provided by the embodiments of this application will be introduced exemplarily.

[0054] Figure 1 One of the flow diagrams of a data visualization method provided by the embodiments of this application is as Figure 1 shown, and the method includes:

[0055] S101. In response to an operation where a user selects to focus on first attribute information of data to be visualized, generate a two-dimensional scatter plot corresponding to the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information.

[0056] It should be noted that the data to be visualized in the embodiments of this application is high-dimensional data, that is, the data to be visualized has attributes or features in multiple dimensions (such as type, quality, and language, etc.). Among them, the first attribute information in the embodiments of this application is an attribute or feature of one dimension of the data to be visualized that the user wants to focus on.

[0057] In some embodiments, when it is determined that the user selects through the user interface to focus on the first attribute information of the data to be visualized, in response to this selection operation of the user, a two-dimensional scatter plot corresponding to the data to be visualized can be automatically generated, and each data point in the generated two-dimensional scatter plot forms different data point clusters according to the first attribute information.

[0058] In some embodiments, after generating the two-dimensional scatter plot corresponding to the data to be visualized, different data point clusters in the two-dimensional scatter plot can be distinguished and displayed through visual elements such as different colors, shapes, or sizes.

[0059] Exemplarily, Figure 2 FIG. 2 is a schematic diagram of a two-dimensional scatter plot provided by an embodiment of the present application. As Figure 2 shown, the two-dimensional scatter plot includes a plurality of different data point clusters.

[0060] S102. In response to an operation in which a user selects to focus on second attribute information of the data to be visualized, represent the second attribute information as the Z-axis of a three-dimensional space coordinate system, and generate and display a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0061] It should be noted that the second attribute information in the embodiments of the present application is an attribute or feature of one dimension of the data to be visualized that the user wants to focus on, and the second attribute information and the first attribute information represent attributes or features of two different dimensions of the data to be visualized.

[0062] In some embodiments, when it is determined that the user selects, through a user interface, to focus on second attribute information of the data to be visualized, in response to this selection operation of the user, represent the second attribute information as the Z-axis of a three-dimensional space coordinate system, and based on the previously generated two-dimensional scatter plot (which means that on the basis of the two-dimensional scatter plot, each data point now has a corresponding Z-axis value determined by the second attribute information), generate and display a three-dimensional view in the three-dimensional space coordinate system.

[0063] In some embodiments, the user can, according to actual needs, select the attribute information (including the first attribute information and the second attribute information) of the data to be visualized that the user needs to focus on by clicking a button, a drop-down menu, or other interaction methods on the user interface.

[0064] In some embodiments, the two-dimensional scatter plot and its corresponding three-dimensional view can be displayed on the same display interface so that the user can intuitively compare and analyze data features in different dimensions; or the two-dimensional scatter plot and its corresponding three-dimensional view can be displayed on different display interfaces, and the user can view different views by switching the display interfaces.

[0065] It can be understood that for each data point in the generated three-dimensional view, each data point in the two-dimensional scatter plot is given different height values according to the second attribute information. The three-dimensional view not only retains the data point cluster characteristics in the two-dimensional scatter plot, but also increases the three-dimensional sense and depth of the data by introducing the second attribute information of the Z-axis, enabling the user to deeply explore the distribution and association of the data in different dimensions from different perspectives.

[0066] Exemplarily, Figure 3 FIG. 3 is one of the schematic diagrams of a three-dimensional view provided by an embodiment of the present application. Figure 4This is the second schematic diagram of a three-dimensional view provided by the embodiments of the present application, where Figure 3 and Figure 4 are the same three-dimensional view presented from different perspectives.

[0067] It can be understood that the data visualization method provided by the embodiments of the present application generates a two-dimensional scatter plot corresponding to the data to be visualized by responding to an operation of the user selecting to focus on the first attribute information of the data to be visualized, and each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information. Then, in response to the operation of the user selecting to focus on the second attribute information of the data to be visualized, the second attribute information is used as the representation of the Z-axis of the three-dimensional space coordinate system, and based on the two-dimensional scatter plot, a three-dimensional view is generated and displayed in the three-dimensional space coordinate system. In this way, the generated two-dimensional scatter plot allows the user to intuitively observe the distribution of the data formed according to the first attribute information, and the generated three-dimensional view adds a third dimension information with a clear meaning of the second attribute information on the basis of the two-dimensional scatter plot, so that the generated three-dimensional view can provide the user with deeper data insights, enabling the user to understand the relationship between the data from multiple dimensions, and the user can dynamically select the attribute information to be focused on according to actual needs. This interactive design greatly enhances the flexibility and user-friendliness of the data visualization process.

[0068] In some embodiments, the operation of responding to the user selecting to focus on the second attribute information of the data to be visualized, using the second attribute information as the representation of the Z-axis of the three-dimensional space coordinate system, and generating and displaying a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot includes:

[0069] Responding to the operation of the user selecting to focus on the second attribute information of the data to be visualized, sampling the target data based on the joint distribution of the first attribute information and the second attribute information in the target data to obtain sampled data; the target data is the data to be visualized corresponding to each data point in the two-dimensional scatter plot;

[0070] Using the second attribute information as the representation of the Z-axis of the three-dimensional space coordinate system, and generating and displaying a three-dimensional view corresponding to the sampled data in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0071] In an embodiment of the present application, after determining that the user selects to focus on the second attribute information of the data to be visualized, the data to be visualized corresponding to each data point in the two-dimensional scatter plot, that is, the target data, can be first identified. Then, based on the joint distribution of the first attribute information and the second attribute information in the target data, the target data is sampled to obtain sampled data. Furthermore, the second attribute information is used as the representation of the Z-axis of the three-dimensional space coordinate system, and based on the previously generated two-dimensional scatter plot, a three-dimensional view corresponding to the sampled data is generated in the three-dimensional space coordinate system.

[0072] It should be noted that the sampling strategy for the target data in the embodiment of the present application is not specifically limited. For example, uniform sampling or stratified sampling strategies can be used to sample the target data, as long as it can ensure that the obtained sampled data can fully reflect the distribution characteristics of the original data to be visualized.

[0073] Exemplarily, Figure 5 FIG. 2 is a second flowchart of a data visualization method provided by an embodiment of the present application. As Figure 5 shown, the method includes:

[0074] S501. In response to an operation in which the user selects to focus on the first attribute information of the data to be visualized, generate a two-dimensional scatter plot corresponding to the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information.

[0075] S502. In response to an operation in which the user selects to focus on the second attribute information of the data to be visualized, sample the target data based on the joint distribution of the first attribute information and the second attribute information in the target data to obtain sampled data; the target data is the data to be visualized corresponding to each data point in the two-dimensional scatter plot.

[0076] S503. Use the second attribute information as the representation of the Z-axis of the three-dimensional space coordinate system, and generate and display a three-dimensional view corresponding to the sampled data in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0077] It should be noted that the descriptions of the same steps and the same content in this embodiment and other embodiments can be referred to the descriptions in other embodiments, and will not be repeated here.

[0078] It can be understood that in the embodiments of the present application, by sampling the to-be-visualized data (i.e., target data) corresponding to each data point in the two-dimensional scatter plot, a three-dimensional view corresponding to the sampled data is finally generated, which can ensure that each data point in the generated three-dimensional view can be clearly displayed. Moreover, considering the influence of the sampling process on the visualization result, by sampling based on the joint distribution of the first attribute information and the second attribute information in the target data, it can be ensured that the generated three-dimensional view can fully reflect the distribution characteristics of the original to-be-visualized data, thereby ensuring the accuracy and credibility of data visualization.

[0079] In some embodiments, generating the two-dimensional scatter plot corresponding to the to-be-visualized data in response to an operation of the user selecting to focus on the first attribute information of the to-be-visualized data includes:

[0080] In response to an operation of the user selecting to focus on the first attribute information of the to-be-visualized data, fusing the to-be-visualized data with the first attribute information to obtain fused data;

[0081] After reducing the dimensionality of the fused data to two-dimensional data, generating the two-dimensional scatter plot based on the two-dimensional data;

[0082] Wherein, the two-dimensional coordinates of each data point in the two-dimensional scatter plot can reflect the distribution characteristics of the first attribute information.

[0083] In the embodiments of the present application, after determining that the user selects to focus on the first attribute information of the to-be-visualized data, the to-be-visualized data can be first fused with the first attribute information selected by the user (the fusion process may involve operations such as data screening, sorting, or conversion to ensure data consistency and accuracy) to obtain fused data. Since the fused data is high-dimensional data, an appropriate dimensionality reduction algorithm (such as principal component analysis, linear discriminant analysis, etc.) can be further used to reduce the dimensionality of the fused data to two-dimensional data. The two-dimensional data after dimensionality reduction retains the main information in the original data, and then a two-dimensional scatter plot is generated based on the two-dimensional data, that is, each two-dimensional data point is plotted in a two-dimensional coordinate system to obtain a two-dimensional scatter plot. The abscissa and ordinate of each data point in the two-dimensional scatter plot respectively correspond to the two dimensions of the two-dimensional data after dimensionality reduction, and the two-dimensional coordinates of each data point in the two-dimensional scatter plot can reflect the distribution characteristics of the first attribute information.

[0084] Exemplarily, Figure 6 is the third schematic flowchart of a data visualization method provided by the embodiments of the present application. As Figure 6 shown, the method includes:

[0085] S601. In response to an operation of the user selecting to focus on the first attribute information of the to-be-visualized data, fusing the to-be-visualized data with the first attribute information to obtain fused data.

[0086] S602. After reducing the dimensionality of the fusion data to two-dimensional data, generate a two-dimensional scatter plot corresponding to the data to be visualized based on the two-dimensional data; the two-dimensional coordinates of each data point in the two-dimensional scatter plot can reflect the distribution characteristics of the first attribute information.

[0087] S603. In response to an operation where the user selects to focus on the second attribute information of the data to be visualized, sample the target data based on the joint distribution of the first attribute information and the second attribute information in the target data to obtain sampled data; the target data is the data to be visualized corresponding to each data point in the two-dimensional scatter plot.

[0088] S604. Use the second attribute information as the Z-axis representation of the three-dimensional space coordinate system, and generate and display a three-dimensional view corresponding to the sampled data in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0089] It should be noted that the descriptions of the same steps and the same content in this embodiment and other embodiments can be referred to the descriptions in other embodiments, and will not be repeated here.

[0090] It can be understood that by adopting data fusion and data dimensionality reduction techniques in the embodiments of the present application, the generated two-dimensional scatter plot can accurately reflect the distribution characteristics of the first attribute information in the data to be visualized, providing strong support for data analysis and decision-making.

[0091] In some embodiments, the data visualization method further includes:

[0092] Determine the density center points of each data point cluster in the three-dimensional view;

[0093] Determine a target display perspective based on the density center points of each data point cluster;

[0094] Adjust the display effect of the three-dimensional view based on the target display perspective to ensure that each data point cluster in the three-dimensional view is in a state where it can be observed from the target display perspective.

[0095] It should be noted that for a data point cluster, the density center point refers to the area or point where the data points in the data point cluster are most densely distributed. Intuitively, the density center point can be regarded as the "center of gravity" or "core" of the cluster, which represents the main characteristics and trends of the data point cluster. The density center point can be determined by calculating the average value or median of all data points within the data point cluster, or by using more complex density estimation methods (such as the Density-Based Spatial Clustering of Applications with Noise (DBSCAN)).

[0096] In the embodiments of the present application, in order to optimize the display effect of the 3D view, the density center points of each data point cluster in the 3D view can be first determined, and then based on the density center points of each data point cluster, an optimal viewing angle (i.e., the target display angle) can be calculated. This viewing angle should be able to maximize the display of the differences and interrelationships between each data point cluster, while ensuring that all data point clusters are in a state where they can be observed. Finally, the display effect of the 3D view is adjusted based on the target display angle, which can include rotating the view, zooming the view, adjusting the lighting and shadow effects, etc., to ensure that each data point cluster in the 3D view is in a state where it can be observed by the user at the target display angle.

[0097] In some embodiments, the target display angle can be determined based on the density center points of each data point cluster, combined with factors such as the spatial distribution, size, shape, and mutual occlusion between each data point cluster.

[0098] In some embodiments, the target display angle can be determined based on the length of the contour line and / or the covered area that each data point cluster can be observed. When the length of the contour line and / or the covered area that each data point cluster can be observed is larger, the viewing angle at this time is the optimal viewing angle, that is, the target display angle.

[0099] It can be understood that by automatically determining the target display angle and automatically adjusting the display effect of the 3D view based on the target display angle in the embodiments of the present application, it can ensure that each data point cluster in the 3D view presents the best visual effect at the target display angle, making the data visualization result more easily acceptable and understandable to the user, and improving the user experience.

[0100] In some embodiments, the data visualization method further includes:

[0101] In response to a target operation triggered by the user for the 3D view, the 3D view is dynamically adjusted based on the target operation;

[0102] Among them, the target operations include zooming, roaming, and rotating operations.

[0103] It should be noted that the zooming operation allows the user to adjust the size and level of detail of the 3D view according to needs. When the user hopes to observe a certain data point cluster in more detail or hopes to include multiple data point clusters in the view at the same time, the zooming operation can be used to achieve this. The user can trigger the zooming operation by scrolling the mouse wheel, clicking the zoom button, or using keyboard shortcuts. The system can adjust the scale of the 3D view according to the user's operation instructions, thereby changing the size and level of detail of the view. During the zooming process, the data point clusters in the 3D view will be enlarged or reduced accordingly, but their relative positions and shapes remain unchanged. In this way, the user can more flexibly observe and analyze the data without changing the data distribution.

[0104] It should be noted that the roaming operation allows the user to freely move the view in the 3D space, so as to be able to more comprehensively observe the distribution and relationship of the data point clusters. The user can trigger the roaming operation by dragging the mouse, using the arrow keys, or clicking the roaming button. The system can adjust the perspective and position of the 3D view according to the user's operation instructions, so that the 3D view can move freely in the 3D space.

[0105] It should be noted that the rotating operation allows the user to rotate the 3D view in order to observe the data point clusters from multiple angles. This is very helpful for understanding the three-dimensional structure and mutual relationship of the data point clusters. The user can trigger the rotating operation by dragging the mouse or using the rotation button. The system can adjust the rotation angle of the 3D view according to the user's operation instructions, so that the user can observe the data points in the 3D view from different angles. During the rotation process, the data point clusters in the 3D view will rotate accordingly, presenting different three-dimensional effects and perspectives. This helps the user to more comprehensively understand the three-dimensional structure and characteristics of the data.

[0106] It can be understood that by providing dynamic adjustment functions such as zooming, roaming, and rotating in the embodiments of the present application, the interactivity between the user and the 3D view is greatly enhanced. The user can flexibly adjust the display effect and angle of the 3D view according to needs, so as to better understand and analyze the data.

[0107] In some embodiments, the data visualization method further includes:

[0108] In response to the user's operation of selecting a Z-axis coordinate value range for the Z-axis of the 3D space coordinate system, based on the Z-axis coordinate value range, determine the target cross-sectional screenshot of the 3D view; the target cross-sectional screenshot is parallel to the X-axis and Y-axis of the 3D space coordinate system and perpendicular to the Z-axis;

[0109] Generate and display the 2D view corresponding to the target cross-sectional screenshot.

[0110] In the embodiments of the present application, the user can select the Z-axis coordinate value range through a slider, an input box or other interactive elements on the user interaction interface. This range defines which data points in the three-dimensional view will be included in the target cross-sectional screenshot. Once the user determines the Z-axis coordinate value range, the system can determine the target cross-sectional screenshot in the three-dimensional view based on this range, and then project the data points in the target cross-sectional screenshot onto a two-dimensional plane to generate a corresponding two-dimensional view. This two-dimensional view can retain the position information of the data points on the X-axis and Y-axis, and at the same time reflect their distribution within the Z-axis coordinate value range.

[0111] In some embodiments, during the process of the user selecting the Z-axis coordinate value range, the currently selected range can be displayed in real time on the interface, and the highlighted area or preview line in the three-dimensional view can be updated to help the user more accurately select the position of the target cross-sectional screenshot.

[0112] In some embodiments, the generated two-dimensional view can be displayed in a separate window next to the three-dimensional view, or displayed as an overlay of the three-dimensional view. The user can switch, zoom or move the two-dimensional view through the control elements on the interface to observe and analyze the data in more detail.

[0113] Exemplarily, Figure 7 is one of the schematic diagrams of the target cross-sectional screenshot of a three-dimensional view provided by the embodiments of the present application. As Figure 7 shown, this target cross-sectional screenshot is a plane, which means that the Z-axis coordinate value range selected by the user is a Z-axis coordinate value point. Figure 8 is another schematic diagram of the target cross-sectional screenshot of a three-dimensional view provided by the embodiments of the present application. As Figure 8 shown, this target cross-sectional screenshot is a three-dimensional diagram.

[0114] Exemplarily, Figure 9 is a schematic diagram of the two-dimensional view corresponding to the target cross-sectional screenshot of a three-dimensional view provided by the embodiments of the present application. As Figure 9 shown, this two-dimensional view is Figure 8 the two-dimensional view corresponding to the target cross-sectional screenshot shown.

[0115] Exemplarily, Figure 10 is the fourth schematic diagram of the process flow of a data visualization method provided by the embodiments of the present application. As Figure 10 shown, this method includes:

[0116] S1001. In response to an operation by the user to select to focus on the first attribute information of the data to be visualized, generate a two-dimensional scatter plot corresponding to the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information.

[0117] S1002. In response to an operation where the user selects to pay attention to the second attribute information of the data to be visualized, use the second attribute information as the representation of the Z-axis in a three-dimensional space coordinate system, and generate and display a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0118] S1003. In response to an operation where the user selects a Z-axis coordinate value range for the Z-axis of the three-dimensional space coordinate system, determine a target cross-sectional screenshot of the three-dimensional view based on the Z-axis coordinate value range; the target cross-sectional screenshot is parallel to the X-axis and Y-axis of the three-dimensional space coordinate system and perpendicular to the Z-axis.

[0119] S1004. Generate and display a two-dimensional view corresponding to the target cross-sectional screenshot.

[0120] It should be noted that for the descriptions of the same steps and the same content in this embodiment and other embodiments, reference can be made to the descriptions in other embodiments, and details will not be repeated here.

[0121] It can be understood that by allowing the user to select a Z-axis coordinate value range to generate a target cross-sectional screenshot and the corresponding two-dimensional view, the present application embodiment greatly enhances the user's control and interaction capabilities with the three-dimensional view. The user can flexibly select and analyze data as needed, thereby having a deeper understanding and insight into the data.

[0122] In some embodiments, the data visualization method further includes:

[0123] In response to an operation where the mouse hovers over any one of the first data points in the two-dimensional view, determine a second data point in the three-dimensional view; the second data point corresponds to the first data point;

[0124] Highlight the second data point.

[0125] In the embodiment of the present application, in the display area of the two-dimensional view, it is possible to detect whether the mouse hovers over a certain data point by listening for mouse events. When it is determined that the mouse hovers over a certain data point (i.e., the first data point), identify it through the coordinates or identifiers of this data point, and based on the correspondence between the data points in the two-dimensional view and the three-dimensional view, find the corresponding data point (i.e., the second data point) in the three-dimensional view. Once the second data point in the three-dimensional view is determined, the second data point is highlighted.

[0126] In some embodiments, the highlighting of the second data point can be achieved by changing the color, size, shape of the second data point or adding a border, etc.

[0127] Exemplarily, Figure 11FIG. 5 is a schematic flowchart of a data visualization method provided by an embodiment of the present application. As shown in Figure 11 , the method includes:

[0128] S1101. In response to an operation of a user selecting to focus on first attribute information of data to be visualized, generate a two-dimensional scatter plot corresponding to the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information.

[0129] S1102. In response to an operation of a user selecting to focus on second attribute information of the data to be visualized, use the second attribute information as the representation of the Z-axis of a three-dimensional space coordinate system, and based on the two-dimensional scatter plot, generate and display a three-dimensional view in the three-dimensional space coordinate system.

[0130] S1103. In response to an operation of a user selecting a Z-axis coordinate value range for the Z-axis of the three-dimensional space coordinate system, based on the Z-axis coordinate value range, determine a target cross-sectional screenshot of the three-dimensional view; the target cross-sectional screenshot is parallel to the X-axis and Y-axis of the three-dimensional space coordinate system and perpendicular to the Z-axis.

[0131] S1104. Generate and display a two-dimensional view corresponding to the target cross-sectional screenshot.

[0132] S1105. In response to an operation of a mouse hovering over any one first data point in the two-dimensional view, determine a second data point in the three-dimensional view; the second data point corresponds to the first data point.

[0133] S1106. Emphasize and display the second data point.

[0134] It should be noted that for the descriptions of the same steps and the same content in this embodiment and other embodiments, reference may be made to the descriptions in other embodiments, and details are not described herein again.

[0135] It can be understood that the embodiment of the present application realizes the linkage between the two-dimensional view and the three-dimensional view, enabling the user to more intuitively understand the projection and corresponding relationship of the data in the three-dimensional view on the corresponding two-dimensional view, so as to better analyze and understand the data.

[0136] In some embodiments, the data visualization method further includes:

[0137] In response to an operation of a mouse hovering over any one third data point in the two-dimensional view, display all attribute information of the third data point in the two-dimensional view.

[0138] In the embodiments of the present application, in the display area of the two-dimensional view, it is possible to detect whether the mouse hovers over a certain data point by listening for mouse events. When it is determined that the mouse hovers over a certain data point (i.e., the third data point), it is identified by the coordinates or identifier of this data point. Once the data point is identified, all the attribute information of this data point can be obtained in a certain way (such as data binding, global variables, or application programming interface (API) calls). After obtaining the attribute information of this data point, the attribute information of this data point can be displayed by showing a tooltip, a pop-up window, or a floating panel next to this data point. As Figure 9 shown, the attribute information of the data point hovered by the mouse is displayed by means of a pop-up window (the rectangular box in the figure is the pop-up window).

[0139] Exemplarily, Figure 12 is the sixth schematic flowchart of a data visualization method provided by the embodiments of the present application. As Figure 12 shown, the method includes:

[0140] S1201. In response to an operation where the user selects to focus on the first attribute information of the data to be visualized, generate a two-dimensional scatter plot corresponding to the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information.

[0141] S1202. In response to an operation where the user selects to focus on the second attribute information of the data to be visualized, use the second attribute information as the representation of the Z-axis of the three-dimensional space coordinate system, and based on the two-dimensional scatter plot, generate and display a three-dimensional view in the three-dimensional space coordinate system.

[0142] S1203. In response to an operation where the user selects a Z-axis coordinate value range for the Z-axis of the three-dimensional space coordinate system, based on the Z-axis coordinate value range, determine the target cross-sectional screenshot of the three-dimensional view; the target cross-sectional screenshot is parallel to the X-axis and Y-axis of the three-dimensional space coordinate system and perpendicular to the Z-axis.

[0143] S1204. Generate and display a two-dimensional view corresponding to the target cross-sectional screenshot.

[0144] S1205. In response to an operation where the mouse hovers over any third data point in the two-dimensional view, display all the attribute information of the third data point in the two-dimensional view.

[0145] It should be noted that for the description of the same steps and the same content in this embodiment as in other embodiments, reference can be made to the descriptions in other embodiments, and details will not be repeated here.

[0146] It can be understood that the embodiments of the present application can provide users with a more intuitive and interactive data visualization experience. Users can hover the mouse to view the detailed attribute information of data points, so as to better understand and analyze the data.

[0147] In some embodiments, before generating the two-dimensional scatter plot corresponding to the data to be visualized in response to the operation of the user selecting to focus on the first attribute information of the data to be visualized, the method further includes:

[0148] Performing data analysis on the data to be visualized to obtain at least two attribute information of the data to be visualized; the at least two attribute information includes the first attribute information and the second attribute information;

[0149] Displaying the at least two attribute information through a user interface for the user to select the attribute information that the user needs to focus on from the at least two attribute information.

[0150] It should be noted that in the embodiments of the present application, in order to generate a two-dimensional scatter plot and a three-dimensional view that can reflect the user's focus points, it is first necessary to perform in-depth data analysis on the data to be visualized. This process aims to mine the key information in the data to be visualized, especially those attribute information that can reveal the internal laws and characteristics of the data to be visualized.

[0151] In some embodiments, the data to be visualized can be preprocessed first, including data cleaning, missing value processing, outlier detection and processing, etc., to ensure the quality and accuracy of the data to be visualized and provide a reliable basis for subsequent analysis. After the preprocessing of the data to be visualized is completed, statistical methods, machine learning algorithms or data mining techniques, etc., can be used to extract at least two attribute information from the preprocessed data to be visualized. These attribute information should be able to comprehensively reflect the characteristics and laws of the data to be visualized, and these attribute information include the first attribute information and the second attribute information that the user may focus on later. Then, the at least two extracted attribute information can be displayed through the user interface. It can be presented in the form of a list, a chart or a tree structure, etc., so that the user can intuitively understand the attribute information of the data to be visualized.

[0152] In some embodiments, options for the user to select the attribute information to be focused on are provided on the user interface. It can be implemented by means of check boxes, drop-down menus or drag-and-drop selections, etc., so that the user can select the first attribute information and the second attribute information to be focused on from the displayed attribute information according to their own needs and analysis purposes.

[0153] Exemplarily, Figure 13 This is the seventh flow chart diagram of a data visualization method provided by the embodiments of the present application, as Figure 13As shown, the method includes:

[0154] S1301. Perform data analysis on the data to be visualized to obtain at least two attribute information of the data to be visualized; the at least two attribute information includes first attribute information and second attribute information.

[0155] S1302. Display the at least two attribute information through a user interaction interface for the user to select the attribute information that the user needs to focus on from the at least two attribute information.

[0156] S1303. In response to the operation of the user selecting to focus on the first attribute information of the data to be visualized, generate a two-dimensional scatter plot corresponding to the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information.

[0157] S1304. In response to the operation of the user selecting to focus on the second attribute information of the data to be visualized, represent the second attribute information as the Z-axis of a three-dimensional space coordinate system, and generate and display a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0158] It should be noted that the descriptions of the same steps and the same content in this embodiment and other embodiments can be referred to the descriptions in other embodiments, and will not be repeated here.

[0159] It can be understood that the embodiment of the present application extracts attribute information by performing in-depth data analysis on the data to be visualized, and displays it through a user interaction interface so that the user can select the attribute information that they need to focus on to generate corresponding two-dimensional scatter plots and three-dimensional views. This interactive design greatly enhances the flexibility and user-friendliness of the data visualization process.

[0160] Exemplarily, Figure 14 is the eighth flowchart diagram of a data visualization method provided by an embodiment of the present application. As Figure 14 shown, the method includes:

[0161] S1401. Load a data set.

[0162] It can be understood that the data set loaded in the embodiment of the present application includes the data to be visualized.

[0163] S1402. Preprocess the data in the data set.

[0164] In some embodiments, the data in the data set can be subjected to data cleaning, missing value processing, outlier detection and processing, etc. according to actual needs.

[0165] S1403. Perform type analysis, quality analysis, complexity analysis, language analysis, feature analysis, etc. on the preprocessed data.

[0166] In some embodiments, statistical methods, machine learning algorithms, data mining techniques, etc. can be used to perform type analysis, quality analysis, complexity analysis, language analysis, feature analysis, etc. on the preprocessed data, with the aim of extracting attribute information that can comprehensively reflect the characteristics and laws of the data to be visualized.

[0167] S1404. Perform dimensionality reduction based on the first attribute information of the analyzed data and display it in a two-dimensional space in the form of a visual scatter plot.

[0168] In some embodiments, the preprocessed data can be fused with the first attribute information, and then the fused data can be reduced to two dimensions and further displayed in a two-dimensional space in the form of a visual scatter plot.

[0169] S1405. Determine the second attribute information of the analyzed data as the Z-axis feature, perform data sampling based on the joint distribution of the data of the Z-axis feature and the first attribute information, and generate and display a three-dimensional view of the sampled data.

[0170] It should be noted that in the embodiments of the present application, by setting the data feature to be displayed (i.e., the second attribute information) on the Z-axis, the data can "float" in the three-dimensional space from the perspective of the Z-axis. Users can view the data from various perspectives through methods such as zooming, roaming, and rotating, and can intuitively feel the hierarchy and correlation between the data. The introduction of the Z-axis perspective greatly enriches the depth and breadth of data insight, and users can clearly observe the data distribution in different dimensions.

[0171] In some embodiments, an operation of the user selecting a certain point or a certain section of the area on the Z-axis can be responded to, a cross-sectional screenshot parallel to the X-axis and Y-axis and perpendicular to the Z-axis is generated, and a two-dimensional view corresponding to the cross-sectional screenshot is generated and displayed. This two-dimensional view can clearly present the data distribution within a specific Z-axis range, and the two-dimensional view and the three-dimensional view can be linked, that is, when a user selects a certain data point in the two-dimensional view, the corresponding data point in the three-dimensional view can be highlighted.

[0172] It can be understood that the data visualization method provided by the embodiments of the present application can at least bring the following beneficial effects: (1) Three-dimensional stereoscopic insight: By introducing the Z-axis feature with a clear meaning, multi-dimensional data is displayed in a three-dimensional space, enabling users to intuitively observe and analyze the relationships between different dimensions of data in the same view; (2) Flexible Z-axis feature switching and dynamic cross-sectional screenshot analysis: Users can flexibly select different Z-axis features, and can accurately select specific points or regions on the Z-axis for fine-grained cross-sectional screenshot analysis, as well as the data linkage function between different views, which helps users to more comprehensively understand the data features; (3) Automatic data sampling and joint distribution analysis: Automatically sample and visualize data according to the joint distribution of different features that users are concerned about, simplify the analysis process of complex data, and improve the accuracy and usability of data visualization.

[0173] The data visualization device provided by the embodiments of the present application will be described below. The data visualization device described below can be correspondingly referred to the data visualization method described above.

[0174] Figure 15 It is a schematic structural diagram of a data visualization device provided by an embodiment of the present application, as Figure 15 shown. The device includes: a first response module 1510 and a second response module 1520; where:

[0175] The first response module 1510 is configured to generate a two-dimensional scatter plot corresponding to the data to be visualized in response to an operation of a user selecting to pay attention to the first attribute information of the data to be visualized; each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information;

[0176] The second response module 1520 is configured to, in response to an operation of a user selecting to pay attention to the second attribute information of the data to be visualized, use the second attribute information as the Z-axis representation of a three-dimensional space coordinate system, and generate and display a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0177] The data visualization device provided by the embodiments of the present application generates a two-dimensional scatter plot corresponding to the data to be visualized by responding to the operation of the user selecting to focus on the first attribute information of the data to be visualized, and each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information. Then, in response to the operation of the user selecting to focus on the second attribute information of the data to be visualized, the second attribute information is used as the representation of the Z-axis of the three-dimensional space coordinate system, and based on the two-dimensional scatter plot, a three-dimensional view is generated and displayed in the three-dimensional space coordinate system. In this way, the generated two-dimensional scatter plot enables the user to intuitively observe the distribution of the data according to the first attribute information, and the generated three-dimensional view adds a third dimension information with a clear meaning of the second attribute information on the basis of the two-dimensional scatter plot, so that the generated three-dimensional view can provide the user with deeper data insights, enabling the user to understand the relationship between the data from multiple dimensions, and the user can dynamically select the attribute information to be focused on according to actual needs. This interactive design greatly enhances the flexibility and user-friendliness of the data visualization process.

[0178] In some embodiments, the second response module 1520 includes:

[0179] A sampling unit, configured to sample the target data based on the joint distribution of the first attribute information and the second attribute information in the target data in response to the operation of the user selecting to focus on the second attribute information of the data to be visualized, and obtain sampled data; the target data is the data to be visualized corresponding to each data point in the two-dimensional scatter plot;

[0180] A three-dimensional view generation unit, configured to use the second attribute information as the representation of the Z-axis of the three-dimensional space coordinate system, and generate and display a three-dimensional view corresponding to the sampled data in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

[0181] In some embodiments, the first response module 1510 includes:

[0182] A fusion unit, configured to fuse the data to be visualized with the first attribute information in response to the operation of the user selecting to focus on the first attribute information of the data to be visualized, and obtain fusion data;

[0183] A two-dimensional scatter plot generation unit, configured to reduce the fusion data to two-dimensional data, and generate the two-dimensional scatter plot based on the two-dimensional data;

[0184] Wherein, the two-dimensional coordinates of each data point in the two-dimensional scatter plot can reflect the distribution characteristics of the first attribute information.

[0185] In some embodiments, the device further includes:

[0186] A first determination module, configured to determine the density center points of each data point cluster in the three-dimensional view;

[0187] A second determination module, configured to determine a target display perspective based on the density center points of each data point cluster;

[0188] An adjustment module, configured to adjust the display effect of the three-dimensional view based on the target display perspective, so as to ensure that each data point cluster in the three-dimensional view is in a state where it can be observed from the target display perspective.

[0189] In some embodiments, the apparatus further includes:

[0190] A third response module, configured to respond to an operation in which a user selects a Z-axis coordinate value range for the Z-axis of the three-dimensional space coordinate system, and determine a target cross-sectional screenshot of the three-dimensional view based on the Z-axis coordinate value range; the target cross-sectional screenshot is parallel to the X-axis and Y-axis of the three-dimensional space coordinate system and perpendicular to the Z-axis;

[0191] A generation module, configured to generate and display a two-dimensional view corresponding to the target cross-sectional screenshot.

[0192] In some embodiments, the apparatus further includes:

[0193] A fourth response module, configured to respond to an operation in which a mouse hovers over any one of the first data points in the two-dimensional view, and determine a second data point in the three-dimensional view; the second data point corresponds to the first data point;

[0194] An emphasized display module, configured to perform an emphasized display on the second data point.

[0195] In some embodiments, the apparatus further includes:

[0196] A fifth response module, configured to respond to an operation in which a mouse hovers over any one of the third data points in the two-dimensional view, and display all attribute information of the third data point in the two-dimensional view.

[0197] In some embodiments, the apparatus further includes:

[0198] A data analysis module, configured to perform data analysis on the data to be visualized, and obtain at least two pieces of attribute information of the data to be visualized; the at least two pieces of attribute information include the first attribute information and the second attribute information;

[0199] An attribute information display module, configured to display the at least two pieces of attribute information through a user interaction interface for the user to select the attribute information that the user needs to pay attention to from the at least two pieces of attribute information.

[0200] It should be noted here that the above data visualization device provided by the embodiments of the present application can implement all the method steps implemented by the above data visualization method embodiments, and can achieve the same technical effects. Therefore, the same parts and beneficial effects as those in the method embodiments will not be specifically described herein.

[0201] Figure 16 The following is a schematic physical structure diagram of an electronic device provided by an embodiment of the present application. As Figure 16 shown, the electronic device may include: a processor 1610, a communications interface 1620, a memory 1630, and a communication bus 1640. Among them, the processor 1610, the communications interface 1620, and the memory 1630 communicate with each other through the communication bus 1640. The processor 1610 can call the executable data instructions stored in the memory 1630 to execute some or all of the steps of the data visualization methods provided in the above embodiments.

[0202] In addition, when the executable data instructions stored in the above-mentioned memory 1630 are implemented in the form of a software functional unit and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiments of the present application, in essence, or the part that contributes to the related technology, can be embodied in the form of a software product. The software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The foregoing storage medium includes: various media such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc that can store program codes.

[0203] The embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is run by a processor, some or all of the steps of the data visualization methods provided in the above embodiments are implemented.

[0204] The embodiments of the present application also provide a computer program product. The computer program product includes a computer program stored in a computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer can execute some or all of the steps of the data visualization methods provided in the above embodiments.

[0205] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0206] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the embodiments of the present application can take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware aspects. Moreover, the embodiments of the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0207] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0208] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0209] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0210] As described above, it is only an optional embodiment of the present application and is not intended to limit the protection scope of the present application.

Claims

1. A data visualization method, comprising: In response to a user selecting to focus on first attribute information of the data to be visualized, generating a two-dimensional scatter plot corresponding to the data to be visualized; Each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information; In response to the user selecting to focus on the second attribute information of the data to be visualized, the second attribute information is represented as the Z axis of the three-dimensional space coordinate system, and based on the two-dimensional scatter plot, a three-dimensional view is generated and displayed in the three-dimensional space coordinate system.

2. The data visualization method according to claim 1, wherein in response to the user selecting the operation of focusing on the second attribute information of the data to be visualized, the second attribute information is used as the Z-axis representation of the three-dimensional space coordinate system, and based on the two-dimensional scatter plot, a three-dimensional view is generated and displayed in the three-dimensional space coordinate system, comprising: In response to a user selecting to focus on the second attribute information of the data to be visualized, sampling the target data based on a joint distribution of the first attribute information and the second attribute information in the target data to obtain sampled data; The target data is the data to be visualized corresponding to each data point in the two-dimensional scatter plot; The second attribute information is represented as a Z axis of the three-dimensional space coordinate system, and based on the two-dimensional scatter plot, a three-dimensional view corresponding to the sampling data is generated and displayed in the three-dimensional space coordinate system.

3. The data visualization method according to claim 1, wherein in response to the user selecting the operation of focusing on the first attribute information of the data to be visualized, generating a two-dimensional scatter plot corresponding to the data to be visualized comprises: In response to a user selecting to focus on first attribute information of the data to be visualized, fusing the data to be visualized with the first attribute information to obtain fused data; After reducing the dimension of the fused data into two-dimensional data, generating the two-dimensional scatter plot based on the two-dimensional data; The two-dimensional coordinates of each data point in the two-dimensional scatter plot can reflect the distribution characteristics of the first attribute information.

4. The data visualization method according to any one of claims 1 to 3, further comprising: Determining a density center point of each data point cluster in the three-dimensional view; Determining a target display viewing angle based on a density center point of each of the data point clusters; Based on the target display viewing angle, the display effect of the three-dimensional view is adjusted to ensure that each of the data point clusters in the three-dimensional view is in an observable state under the target display viewing angle.

5. The data visualization method according to any one of claims 1 to 3, further comprising: In response to a user selecting a Z-axis coordinate value range for a Z-axis of the three-dimensional space coordinate system, determining a target cross-sectional screenshot of the three-dimensional view based on the Z-axis coordinate value range; The target cross-section image is parallel to the X-axis and the Y-axis of the three-dimensional space coordinate system, and perpendicular to the Z-axis; Generate and display a two-dimensional view corresponding to the target cross-sectional screenshot.

6. The data visualization method according to claim 5, further comprising: In response to an operation of hovering a mouse over any first data point in the two-dimensional view, determining a second data point in the three-dimensional view; The second data point corresponds to the first data point; The second data point is highlighted.

7. The data visualization method according to claim 5, further comprising: In response to an operation of hovering a mouse over any third data point in the two-dimensional view, all attribute information of the third data point is displayed in the two-dimensional view.

8. The data visualization method according to any one of claims 1 to 3, wherein in response to the user selecting the operation of focusing on the first attribute information of the data to be visualized, before generating the two-dimensional scatter plot corresponding to the data to be visualized, the method further comprises: Performing data analysis on the data to be visualized to obtain at least two attribute information of the data to be visualized; The at least two attribute information include the first attribute information and the second attribute information; The at least two pieces of attribute information are displayed through a user interaction interface, so that the user can select the attribute information that the user needs to pay attention to from the at least two pieces of attribute information.

9. A data visualization device, comprising: A first response module, configured to generate a two-dimensional scatter plot corresponding to the data to be visualized in response to a user selecting to focus on first attribute information of the data to be visualized; Each data point in the two-dimensional scatter plot forms different data point clusters according to the first attribute information; The second response module is used to respond to the user's operation of selecting to focus on the second attribute information of the data to be visualized, use the second attribute information as the Z-axis representation of the three-dimensional space coordinate system, and generate and display a three-dimensional view in the three-dimensional space coordinate system based on the two-dimensional scatter plot.

10. An electronic device, comprising: A memory for storing executable data instructions; A processor is used to implement the data visualization method described in any one of claims 1 to 8 when executing the executable data instructions stored in the memory.

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