Multi-dimensional visual analysis method for data report

Abstract

The invention relates to the technical field of data visualization, in particular to a multi-dimensional visual analysis method for a data report. Comprising the following steps: acquiring original report data, preprocessing an original report, and outputting a multi-dimensional data set; establishing a visual two-dimensional coordinate system, positioning feature dimensions, and obtaining a positioning data point coordinate system; dynamically adjusting the coordinate system range of the positioning data points, sequentially connecting a plurality of positioning data points, outputting a dimension coordinate system, and performing visual display; through the above mode, the feature dimensions are positioned in the multi-dimensional data set, and then the dimension coordinate system is established and visualized display is carried out, so that the establishment time is shortened, the establishment process is reduced, and visualized analysis of the multi-dimensional data is facilitated.

Description

Technical Field

[0001] The present invention relates to the technical field of data visualization, and in particular to a multi-dimensional visualization analysis method for data reports. Background Art

[0002] In data analysis, coordinate systems are often used for visual analysis. First, you need to select the appropriate coordinate system type, including scatter plots, line charts, bar charts, and histograms, then prepare the data and draw the coordinate system.

[0003] The above method can only be applied to single-dimensional data visualization. In multi-dimensional data analysis, it is necessary to repeatedly establish a coordinate system based on multiple analysis features. This takes a long time to establish and involves many processes, which is not conducive to visual analysis of multi-dimensional data. Summary of the invention

[0004] The purpose of the present invention is to provide a multi-dimensional visualization analysis method for data reports, aiming to solve the technical problem in the prior art that in multi-dimensional data analysis, a coordinate system needs to be repeatedly established according to multiple analysis features, which takes a long time to establish and involves many processes, and is not conducive to visualization analysis of multi-dimensional data.

[0005] To achieve the above purpose, the present invention adopts a multi-dimensional visualization analysis method for data reports, comprising the following steps:

[0006] Obtain original report data, pre-process the original report, and output a multi-dimensional data set;

[0007] Establish a visual two-dimensional coordinate system, locate the feature dimension, and obtain the coordinate system of the positioning data point;

[0008] Dynamically adjust the coordinate system range of the positioning data points, connect multiple positioning data points in sequence, output the dimensional coordinate system, and perform visual display.

[0009] Among them, in the steps of obtaining original report data, preprocessing the original report, and outputting a multi-dimensional data set:

[0010] Obtain original report data, identify and process missing values, abnormal values, and duplicate values ​​in the data;

[0011] Normalize the data and extract features.

[0012] Among them, after normalizing the data and extracting features:

[0013] Determine dimensions and measures, build multidimensional data sets, and output.

[0014] Among them, in the steps of establishing a visual two-dimensional coordinate system, locating the feature dimension, and obtaining the coordinate system of the positioning data point:

[0015] Establish a two-dimensional coordinate system to obtain feature dimension data from multi-dimensional data sets;

[0016] Verify the comparison between the verification hash value and the initial hash value of the feature dimension data and output the verification result.

[0017] Among them, in the step of comparing the verification hash value and the initial hash value of the verification feature dimension data and outputting the verification result:

[0018] If the verification hash value is the same as the initial hash value, the feature dimension data is located in the two-dimensional coordinate system to obtain the coordinates of the located data point.

[0019] Among them, in the step of comparing the verification hash value and the initial hash value of the verification feature dimension data and outputting the verification result:

[0020] If the verification hash value is not the same as the initial hash value, the alarm prompt data is output.

[0021] Among them, in the steps of dynamically adjusting the coordinate system range of the positioning data point, sequentially connecting multiple positioning data points, outputting the dimensional coordinate system, and performing visual display:

[0022] Determine the coordinate axis range according to the maximum value of the positioning data point;

[0023] Divide the coordinate area and determine the range of the coordinate area according to the range of the positioning data points;

[0024] Connect multiple positioning data points and form a dimensional polyline;

[0025] Integrate multiple coordinate areas, output dimensional coordinate system, and perform visual display.

[0026] A multi-dimensional visualization analysis method for data reports of the present invention obtains original report data, pre-processes the original report, and outputs a multi-dimensional data set; establishes a visualization two-dimensional coordinate system, locates the characteristic dimension, and obtains the coordinate system of the positioning data point; dynamically adjusts the range of the positioning data point coordinate system, connects multiple positioning data points in sequence, outputs the dimensional coordinate system, and performs visualization display; locates the characteristic dimension in the multi-dimensional data set, and then establishes the dimensional coordinate system and performs visualization display, thereby shortening the establishment time and reducing the establishment process, which is conducive to visualization analysis of multi-dimensional data. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 It is a flowchart of the steps of the multi-dimensional visualization analysis method of data reports of the present invention.

[0029] Figure 2 It is a step flow chart of S100 of the present invention.

[0030] Figure 3 It is a step flow chart of S200 of the present invention.

[0031] Figure 4 It is a step flow chart of S300 of the present invention.

[0032] Figure 5 It is a structural principle diagram of the data report multi-dimensional visualization analysis system of the present invention.

[0033] Figure 6 It is a structural principle diagram of the electronic equipment of the present invention.

[0034] 401-dataset processing module, 402-feature dimension positioning module, 403-dimensional coordinate system output module. DETAILED DESCRIPTION

[0035] Here, exemplary embodiments are described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0036] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0037] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0038] See also Figure 1 to Figure 4 The present invention provides a method for multi-dimensional visualization analysis of data reports, comprising the following steps:

[0039] S100: Acquire original report data, pre-process the original report, and output a multi-dimensional data set;

[0040] S200: Establish a visualized two-dimensional coordinate system, locate the feature dimension, and obtain a coordinate system of the positioning data point;

[0041] S300: Dynamically adjust the coordinate system range of the positioning data point, connect multiple positioning data points in sequence, output the dimensional coordinate system, and perform visual display.

[0042] In this embodiment, the original report data is first obtained, the original report is preprocessed, and a multi-dimensional data set is output; then a visual two-dimensional coordinate system is established, the characteristic dimension is located, and the coordinate system of the positioning data point is obtained; then the range of the positioning data point coordinate system is dynamically adjusted, and multiple positioning data points are connected in sequence, and the dimensional coordinate system is output and visualized; the characteristic dimension is located in the multi-dimensional data set, and then the dimensional coordinate system is established and visualized, so as to shorten the establishment time and reduce the establishment process, which is conducive to the visualization analysis of multi-dimensional data.

[0043] Furthermore, in the steps of obtaining original report data, preprocessing the original report, and outputting a multi-dimensional data set, the specific process is as follows:

[0044] S101: Obtain original report data, identify and process missing values, abnormal values, and duplicate values ​​in the data;

[0045] S102: normalize the data and extract features;

[0046] S103: Determine dimensions and measures, construct a multidimensional data set, and output it.

[0047] In this implementation, the original report data is first obtained, and missing values, abnormal values, and duplicate values ​​in the data are identified and processed; the processing methods include deletion, filling, and replacement, wherein the filling method includes using the mean, median, and mode to fill missing values, and the replacement method includes using the mean to replace abnormal values. Then the data is normalized and features are extracted; wherein the features can be: sales, time, date, location, category, etc. Then the dimensions and measures are determined, a multidimensional data set is constructed, and output.

[0048] Furthermore, in the steps of establishing a visual two-dimensional coordinate system, locating the feature dimension, and obtaining the coordinate system of the positioning data point, the specific process is as follows:

[0049] S201: Establish a two-dimensional coordinate system and obtain feature dimension data from a multi-dimensional data set;

[0050] S202: Verify the comparison between the verification hash value and the initial hash value of the feature dimension data, and output the verification result.

[0051] In this embodiment, a two-dimensional coordinate system is first established, and the feature dimension data is obtained from a multidimensional data set. Then, the comparison between the verification hash value of the feature dimension data and the initial hash value is verified, and the verification result is output. Among them, the initial hash value is calculated after the data is normalized, and the data is used as input, and its hash value is calculated using the selected hash algorithm. The hash algorithm can be SHA-256, MD5, etc., and the calculated hash value is stored together with the data; the verification hash value is calculated when preparing to establish a visual two-dimensional coordinate system, and the feature dimension data is re-read, and its hash value is calculated using the same hash algorithm. If the two hash values ​​are the same, it means that the data has not changed during storage or transmission, and the data is complete. At this time, the feature dimension data is located in the two-dimensional coordinate system to obtain the coordinates of the positioning data point; if the two hash values ​​are different, it means that the data may have been tampered with or damaged, and the alarm prompt data is output at this time.

[0052] Furthermore, in the steps of dynamically adjusting the coordinate system range of the positioning data point, sequentially connecting multiple positioning data points, outputting the dimensional coordinate system, and performing visual display, the specific process is as follows:

[0053] S301: Determine the coordinate axis range according to the maximum value of the positioning data point;

[0054] S302: Divide the coordinate area and determine the range of the coordinate area according to the range of the positioning data points;

[0055] S303: Connect multiple positioning data points to form a dimensional polyline;

[0056] S304: Integrate multiple coordinate areas, output a dimensional coordinate system, and perform visual display.

[0057] In this embodiment, the coordinate axis range is first determined based on the maximum value of the positioning data point. For example, the range is set to a multiple of the maximum value, such as 1.1 times, 1.2 times, etc., to ensure that the data point is not too close to the edge of the coordinate axis. Then the coordinate area is divided, and the coordinate area range is determined based on the positioning data point range. In each coordinate area, it is determined whether the positioning data points are dense or sparse; the determination method is:

[0058]

[0059] in is the density estimate, that is, the probability estimate at point x; n is the data point; h is the bandwidth, and K is the kernel function.

[0060] in a certain area A higher value indicates that the data points in the region are more concentrated, that is, the data points are dense in the region.

[0061] On the contrary, if A lower value indicates that the data points in the region are more dispersed, that is, the data points are sparse in the region.

[0062] According to the judgment structure, determine the range of the coordinate area. If the data points in a certain area are relatively concentrated, you can expand the range of the area to prevent some data from being unclear; if the data points in a certain area are relatively scattered, you can reduce the range of the area to prevent wasting the screen. Connect multiple positioning data points and form a dimensional polyline; then integrate multiple coordinate areas, output the dimensional coordinate system, and perform visual display.

[0063] Corresponding to the aforementioned embodiment of the method for multi-dimensional visualization analysis of data reports, the present application also provides an embodiment of a system for multi-dimensional visualization analysis of data reports.

[0064] Figure 5 is a block diagram of a data report multi-dimensional visualization analysis system according to an exemplary embodiment. Figure 5 The system may include: a data set processing module 401, a feature dimension positioning module 402 and a dimension coordinate system output module 403; wherein:

[0065] The data set processing module 401 is used to obtain original report data, pre-process the original report, and output a multi-dimensional data set;

[0066] The feature dimension positioning module 402 is used to establish a visual two-dimensional coordinate system, locate the feature dimension, and obtain a positioning data point coordinate system;

[0067] The dimensional coordinate system output module 403 is used to dynamically adjust the coordinate system range of the positioning data point, sequentially connect multiple positioning data points, output the dimensional coordinate system, and perform visual display.

[0068] In this embodiment, the data set processing module 401 obtains the original report data, pre-processes the original report, and outputs a multi-dimensional data set; the feature dimension positioning module 402 establishes a visual two-dimensional coordinate system, locates the feature dimension, and obtains the positioning data point coordinate system; the dimension coordinate system output module 403 dynamically adjusts the positioning data point coordinate system range, connects multiple positioning data points in sequence, outputs the dimension coordinate system, and performs a visual display; locates the feature dimension in the multi-dimensional data set, and then establishes the dimension coordinate system and performs a visual display, thereby shortening the establishment time and reducing the establishment process, which is conducive to the visual analysis of multi-dimensional data.

[0069] Regarding the system in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0070] For the system embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application. A person of ordinary skill in the art can understand and implement it without creative work.

[0071] Accordingly, the present application also provides an electronic device, including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned multi-dimensional visualization analysis method for data reports. Figure 6 As shown, it is a hardware structure diagram of any device with data processing capability in which a data report multi-dimensional visual analysis system provided by an embodiment of the present invention is located. Figure 6 In addition to the processor, memory and network interface shown, any device with data processing capability in which the apparatus in the embodiment is located may also include other hardware, generally based on the actual functions of the device with data processing capability, which will not be described in detail.

[0072] Accordingly, the present application also provides a computer-readable storage medium on which computer instructions are stored, and when the instructions are executed by the processor, the multi-dimensional visualization analysis method of the data report as described above is implemented. The computer-readable storage medium can be an internal storage unit of any device with data processing capabilities described in any of the aforementioned embodiments, such as a hard disk or a memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), an SD card, a flash card (Flash Card), etc. equipped on the device. Further, the computer-readable storage medium can also include both an internal storage unit of any device with data processing capabilities and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capabilities, and can also be used to temporarily store data that has been output or is to be output.

[0073] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the contents disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0074] It should be understood that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A multi-dimensional visualization analysis method for data reports, characterized in that: The steps include: Obtain original report data, pre-process the original report, and output a multi-dimensional data set; Establish a visual two-dimensional coordinate system, locate the feature dimension, and obtain the coordinate system of the positioning data point; Dynamically adjust the coordinate system range of the positioning data points, connect multiple positioning data points in sequence, output the dimensional coordinate system, and perform visual display.

2. The multi-dimensional visualization analysis method for data reports according to claim 1, characterized in that: In the steps of obtaining original report data, preprocessing the original report, and outputting a multidimensional data set: Obtain original report data, identify and process missing values, abnormal values, and duplicate values ​​in the data; Normalize the data and extract features.

3. The multi-dimensional visualization analysis method for data reports according to claim 2, characterized in that: After normalizing the data and extracting features: Determine dimensions and measures, build multidimensional data sets, and output.

4. The multi-dimensional visualization analysis method for data reports according to claim 1, characterized in that: In the steps of establishing a visual two-dimensional coordinate system, locating feature dimensions, and obtaining the coordinate system of the positioning data points: Establish a two-dimensional coordinate system to obtain feature dimension data from multi-dimensional data sets; Verify the comparison between the verification hash value and the initial hash value of the feature dimension data and output the verification result.

5. The multi-dimensional visualization analysis method for data reports according to claim 4, characterized in that: When verifying the comparison between the verification hash value and the initial hash value of the feature dimension data and outputting the verification result: If the verification hash value is the same as the initial hash value, the feature dimension data is located in the two-dimensional coordinate system to obtain the coordinates of the located data point.

6. The multi-dimensional visualization analysis method for data reports according to claim 4, characterized in that: When verifying the comparison between the verification hash value and the initial hash value of the feature dimension data and outputting the verification result: If the verification hash value is not the same as the initial hash value, the alarm prompt data is output.

7. The multi-dimensional visualization analysis method for data reports according to claim 1, characterized in that: In the steps of dynamically adjusting the coordinate system range of the positioning data points, sequentially connecting multiple positioning data points, outputting the dimensional coordinate system, and performing visual display: Determine the coordinate axis range according to the maximum value of the positioning data point; Divide the coordinate area and determine the range of the coordinate area according to the range of the positioning data points; Connect multiple positioning data points and form a dimensional polyline; Integrate multiple coordinate areas, output dimensional coordinate system, and perform visual display.

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