A data statistics method, device, electronic device, storage medium, and system

Abstract

The application provides a data statistical method, device, electronic equipment, storage medium and system, receives a data management instruction input by a user; adjusts a state of data according to the data management instruction, the state of the data at least including being selected; when the data is selected, generates a plurality of keys and key values corresponding to the plurality of keys according to a plurality of category information of each selected data; adds the plurality of keys and the plurality of key values to a first key-value pair data set with a plurality of key-value pairs constructed in advance, each key-value pair corresponding to the plurality of category information; and statistically counts each category information of all selected data according to the first key-value pair data set. The method is applicable to the statistics of various types of data without modifying the original data, can statistically count information according to different statistical requirements of the user, has powerful statistical functions, good scalability, and effectively improves the efficiency of data statistics.

Description

Technical Field

[0001] This invention relates to the field of data management technology, specifically to a data statistics method, apparatus, electronic device, storage medium, and system. Background Technology

[0002] As internet technology expands in depth and breadth in real life, mobile device applications are becoming increasingly integrated with work and life, often requiring the selection of multiple data points for batch statistical operations on mobile devices.

[0003] Currently, the following methods are commonly used to select data:

[0004] 1. In the data adapter, the tagged data is stored in a data set;

[0005] 2. Add a new field attribute to the data to mark the data as selected.

[0006] The above method has the following drawbacks:

[0007] 1. The added attributes used to mark data status will affect subsequent security verification and other operations;

[0008] 2. The logic is overlapping and unclear;

[0009] 3. Data types are limited and not universally applicable;

[0010] 4. Limited functionality, lacking statistical capabilities. Summary of the Invention

[0011] The data statistics method provided by this invention is applicable to the statistics of various types of data without modifying the original data, effectively improving the efficiency of data statistics.

[0012] In a first aspect, one embodiment provides a data statistics method, comprising: receiving a data management instruction input by a user; adjusting the state of data according to the data management instruction, wherein the state of the data includes at least being selected; if the state of the data is adjusted to be selected, generating multiple keys and key values ​​corresponding to the multiple keys according to multiple category information of each selected data; adding the multiple keys and multiple key values ​​to multiple pre-constructed first key-value pair datasets, wherein each first key-value pair dataset corresponds to each category information; and statistically analyzing the category information of all selected data according to the first key-value pair datasets.

[0013] In some embodiments, the state of the data also includes being deselected. When the state of the data is adjusted to be deselected, multiple keys of the data and the key values ​​corresponding to each key are removed from the corresponding first key-value pair dataset.

[0014] In some embodiments, the key of each selected data includes at least a unique data key, which is defined according to a preset identification marker of the selected data. The first key-value pair dataset includes at least a second key-value pair dataset and a third key-value pair dataset. The key of the second key-value pair dataset is a unique data key, and the key value is the selection state of the selected data, used to store the selection state of each selected data. The key of the third key-value pair dataset is a unique data key, and the key value is the byte size of the selected data, used to store the byte size of each selected data.

[0015] In some embodiments, the step of calculating various types of information for all selected data based on all the first key-value pair datasets includes: calculating the total number of all selected data based on the second key-value pair dataset; and calculating the total byte size of all selected data based on the third key-value pair dataset.

[0016] In some embodiments, the key of the selected data further includes a type-unique key, which is defined according to the data type of the selected file. The first key-value pair dataset includes at least a fourth key-value pair dataset and a fifth key-value pair dataset. The key of the fourth key-value pair dataset is the type-unique key, and the key value is the data type of the selected data, used to store the data type of each selected data. The key of the fifth key-value pair dataset is the type-unique key, and the key value is the byte size of the selected data, used to store the byte size of each selected data.

[0017] In some embodiments, the step of calculating various types of information for all selected data based on all the first key-value pair datasets further includes: calculating the total number of each data type in all selected data based on the fourth key-value pair dataset; and calculating the total byte size of the selected data for each data type based on the fifth key-value pair dataset.

[0018] In some embodiments, each key of the selected data further includes a grouping unique key, which is defined according to a preset identifier that can group all selected data; the second key-value pair dataset includes a second key-value pair data subset, the key of the second key-value pair dataset is the grouping unique key, the key value is the second key-value pair data subset, the key of the second key-value pair data subset is the data unique key, and the key value is the selection state of the selected data; and / or the third key-value pair dataset includes a third key-value pair data subset, the key of the third key-value pair dataset is the grouping unique key, the key value is the third key-value pair data subset, and the key of the third key-value pair data subset is the type. A unique key, the key value being the set of all selected data's unique keys; and / or the fourth key-value pair dataset includes a fourth key-value pair data subset, the key of the fourth key-value pair dataset being the group unique key, the key value being the fourth key-value pair data subset, the key of the fourth key-value pair data subset being the data unique key, and the key value being the byte size of the selected data; and / or the fifth key-value pair dataset includes a fifth key-value pair data subset, the key of the fifth key-value pair dataset being the group unique key, the key value being the fifth key-value pair data subset, the key of the fifth key-value pair data subset being the type unique key, and the key value being the byte size of all selected data corresponding to that type unique key.

[0019] In some embodiments, the step of statistically analyzing various types of information of all the selected data based on all the first key-value pair datasets further includes: statistically analyzing various types of information of all the selected data by group based on the second key-value pair dataset, the third key-value pair dataset, the fourth key-value pair dataset, and the fifth key-value pair dataset.

[0020] In some embodiments, the method further includes displaying the category information of all the selected data that have been statistically analyzed.

[0021] In a second aspect, one embodiment provides a data statistics device, comprising: a display unit for displaying statistical category information; a processing unit for generating multiple keys and key values ​​corresponding to the multiple keys based on multiple category information of each selected data when the state of the data is adjusted to be selected; adding the multiple keys and multiple key values ​​to a pre-constructed first key-value pair dataset having multiple key-value pairs, each key-value pair corresponding to one category information of each selected data; and a statistics unit for statistically analyzing the category information of all selected data based on all the first key-value pair datasets, and outputting the statistically analyzed category information to the display unit for display.

[0022] Thirdly, in one embodiment, an electronic device is provided, characterized in that it includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method as described above.

[0023] Fourthly, in one embodiment, a computer storage medium is provided, wherein a computer program is stored on the storage medium, characterized in that the program, when executed by a processor, implements the method as described above.

[0024] Fifthly, in one embodiment, a data statistics system is provided, comprising: a network private cloud storage device for storing data from the aforementioned method; an electronic device including a processor, a memory, and an access port; the memory storing an application program executable on the processor; the processor being configured to respond to input from a user via the access port to obtain multiple categories of data stored on the network private cloud storage device, and to generate multiple keys and key values ​​corresponding to the multiple keys based on the multiple categories of information, and to implement the aforementioned method when executing the application program.

[0025] According to the method of the above embodiments, when data is selected, multiple keys and key values ​​corresponding to each key are generated for each selected data. The multiple keys and multiple key values ​​are added to a pre-constructed first key-value pair dataset with multiple key-value pairs, each key-value pair corresponding to multiple categories of information. Based on the first key-value pair dataset, the category information of all selected data is statistically analyzed. This method is applicable to the statistics of various types of data without modifying the original data. It can perform information statistics according to different statistical requirements of users, has powerful statistical functions, good scalability, and effectively improves the efficiency of data statistics. Attached Figure Description

[0026] Figure 1 A flowchart of the data statistics method provided by this invention;

[0027] Figure 2 This is a schematic diagram of a data statistics interface according to one embodiment;

[0028] Figure 3 A schematic diagram of the data statistics device provided by the present invention;

[0029] Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention;

[0030] Figure 5 A schematic diagram of the structure of the computer storage medium provided by the present invention;

[0031] Figure 6 A schematic diagram of the data statistics system provided by the present invention. Detailed Implementation

[0032] The present invention will now be described in further detail with reference to specific embodiments and accompanying drawings. Similar elements in different embodiments are referred to by associated similar element reference numerals. In the following embodiments, many details are described to facilitate a better understanding of this application. However, those skilled in the art will readily recognize that some features may be omitted in different situations, or may be replaced by other elements, materials, or methods. In some cases, certain operations related to this application are not shown or described in the specification. This is to avoid obscuring the core parts of this application with excessive description. For those skilled in the art, detailed description of these related operations is not necessary; they can fully understand the related operations based on the description in the specification and general technical knowledge in the art.

[0033] Furthermore, the features, operations, or characteristics described in the specification can be combined in any suitable manner to form various embodiments. At the same time, the steps or actions in the method description can be rearranged or adjusted in a manner obvious to those skilled in the art. Therefore, the various orders in the specification and drawings are only for the clear description of a particular embodiment and do not imply a necessary order, unless otherwise stated that a particular order must be followed.

[0034] The serial numbers assigned to components in this article, such as "first" and "second", are used only to distinguish the objects being described and have no sequential or technical meaning.

[0035] When managing data on electronic devices, the common practice is to first select at least one piece of data and then proceed with the next step as needed. For example, when freeing up storage space on a private cloud, different types of data, such as audio / video, photos, documents, and programs, need to be selected first. A comprehensive assessment of information about these selected data (such as size in bytes, storage location, and whether they are associated with other data) is then used to determine whether to delete them. However, this process has several drawbacks. First, existing methods modify the original data, affecting subsequent operations. Second, for software developers, existing methods are not applicable to multiple data types, requiring adaptive modifications each time based on the data type, resulting in significant time costs. Furthermore, the lack of data statistics functionality leaves users without reference information for making comprehensive judgments.

[0036] Based on this, the present invention provides a data statistics method applicable to the statistics of various types of data. Without modifying the original data, it can quickly and accurately locate the corresponding data for subsequent operations. It has powerful statistical functions, good scalability, and effectively improves the efficiency of data statistics.

[0037] Please refer to Figure 1 The data statistics method provided by this invention includes:

[0038] S10: Receive data management instructions input by the user, and adjust the state of the data according to the data management instructions. The state of the data includes at least being selected.

[0039] In some embodiments, the electronic device responds to user input by displaying a data management interface that includes at least one piece of data, and sets the status of the displayed data to an adjustable state, whereby the data can be adjusted to be selected or deselected, and the user inputs data management commands through the data management interface.

[0040] Optionally, users can input data management commands via touch, voice, buttons, or any other possible means, which can be determined according to actual needs during application.

[0041] S20: If the state of the data is adjusted to be selected, generate multiple keys and key values ​​corresponding to the multiple keys based on the multiple category information of each selected data.

[0042] In some embodiments, the key for each selected data includes: a data unique key, a type unique key, and a group unique key. The data unique key is defined according to a preset identification marker of the selected data. The selected identification marker can be the storage path of the data, such as: the objectKey of an image = / album / sun(1).png, where one image path corresponds to one image. Alternatively, a combination of multiple attributes can be defined as the data unique key as needed, such as: defining the image size and storage path as the data unique key. Compared with the existing technology of finding data based solely on the storage path, the method of defining multiple data combinations as the data unique key is more accurate and efficient in locating data. The unique key is defined based on the data type of the selected file, such as text files, document files, video files, and audio files. This means that both existing and future data types are supported. The unique key for grouping is defined based on a preset identifier that can group all selected data, such as text file types, document file types, video file types, and audio file types. Using the unique key for grouping data allows the same data to be in different groups, enabling better data management. The method provided by this invention can quickly and accurately locate the corresponding data using the key and key-value pair of the selected data without modifying the original data, facilitating subsequent operations.

[0043] S30: Add multiple keys and multiple key-value pairs to multiple pre-built first key-value pair datasets, each first key-value pair dataset corresponding to each category information.

[0044] In some embodiments, the first key-value pair dataset includes at least: a second key-value pair dataset and a third key-value pair dataset. The key of each selected data includes at least: a unique data key, which is defined according to a preset identification marker of the selected data. The second key-value pair dataset is based on the unique data key, and the key value is the selection state of the selected data, used to store the selection state of each selected data. The third key-value pair dataset is generated based on the unique data key and the byte size of the selected data, used to store the byte size of each selected data.

[0045] In some embodiments, the first key-value pair dataset further includes: a fourth key-value pair dataset and a fifth key-value pair dataset; the key of each selected data also includes a type-unique key, the key of the fourth key-value pair dataset is a type-unique key, the key value is the data type of the selected data, and it is used to store the data type of each selected data; the key of the fifth key-value pair dataset is a type-unique key, the key value is the byte size of the selected data, and it is used to store the byte size of each selected data.

[0046] In some embodiments, the second key-value pair dataset further includes a second key-value pair data subset, wherein the key of the second key-value pair dataset is a group-unique key, the key value is the second key-value pair data subset, the key of the second key-value pair data subset is a data-unique key, and the key value is the selection state of the selected data; and / or, the third key-value pair dataset includes a third key-value pair data subset, wherein the key of the third key-value pair dataset is a group-unique key, the key value is the third key-value pair data subset, the key of the third key-value pair data subset is a type-unique key, and the key value is the set of data-unique keys of all selected data; and / Or, the fourth key-value pair dataset includes a subset of fourth key-value pair data, where the key of the fourth key-value pair dataset is a group-unique key, the key value is the subset of fourth key-value pair data, the key of the subset of fourth key-value pair data is a data-unique key, and the key value is the byte size of the selected data; and / or, the fifth key-value pair dataset includes a subset of fifth key-value pair data, where the key of the fifth key-value pair dataset is a group-unique key, the key value is the subset of fifth key-value pair data, the key of the subset of fifth key-value pair data is a type-unique key, and the key value is the total byte size of all selected data corresponding to that type-unique key.

[0047] S40: Based on the first key-value pair dataset, calculate the category information for all selected data.

[0048] In some embodiments, the process of statistically analyzing various types of information for all selected data based on the first key-value pair dataset further includes: statistically analyzing various types of information for all selected data by group based on the second key-value pair dataset, the third key-value pair dataset, the fourth key-value pair dataset, and the fifth key-value pair dataset.

[0049] In some embodiments, if the state of selected data is changed to be deselected, multiple keys of the data and the key value corresponding to each key are removed from the corresponding first key-value pair dataset.

[0050] When applied, the electronic device responds to the user's input by changing the state of the data from selected to deselected. At this point, it is only necessary to remove the multiple keys of the data and the key values ​​corresponding to each key from the corresponding first key-value pair dataset.

[0051] In some embodiments, the method provided by the present invention further includes: displaying the category information of all selected data that have been statistically analyzed.

[0052] The following example illustrates the data statistics method of this invention, such as... Figure 2 As shown, in this example, the data management interface 100 includes a first data group 200, a second data group 300, and an information display box 400. Both data groups include 5 images. Various statistical information can be displayed in the information display box 400. The key, key value, byte size, and key-value pairs of each image are defined as follows:

[0053] The objectKey of the first image in the first group is / album / sun(1).png;

[0054] The objectKey of the second image in the first group is / album / sun(2).png;

[0055] The objectKey of the third image in the first group is / album / sun(3).jpeg;

[0056] The objectKey of the fourth image in the first group is / album / sun(4).jpeg;

[0057] The objectKey of the first image in the second group is / album / star(1).png;

[0058] The objectKey of the first image in the second group is / album / star(2).jpeg;

[0059] The size of the first image in the first group is 101;

[0060] The size of the second image in the first group is 102.

[0061] The size of the third image in the first group is 103.

[0062] The size of the fourth image in the first group is 104.

[0063] The size of the first image in the second group is 201;

[0064] The size of the second image in the second group is 202.

[0065] Wherein, Key is the key, Value is the key-value pair, size is the image size in bytes, objectKey is the data unique key, key-value pairs include a one-to-one correspondence between Key and Value, the data unique key is the image storage path, the data type unique key is the image type (.png or .jpeg), the group unique key for the first group is 1, the group unique key for the second group is 2, the key-value pair dataset is represented by [], and the key-value pair is represented by {}. For ease of calculation, the following size values ​​are only hypothetical data and do not correspond to the actual data size.

[0066] It is important to note that if you need to select images across data groups, the objectKey of each image will be its MD5 hash value. MD5 is a hash function widely used in computer security to provide message integrity protection.

[0067] Add all the keys of the selected data and the key-value pairs corresponding to each key to multiple pre-built first key-value pair datasets. The first key-value pair datasets include second, third, fourth, and fifth key-value pair datasets, where:

[0068] The key of the second key-value pair dataset is the unique key for grouping, and the value is a subset of the second key-value pair data. The key of the subset of the second key-value pair data is the unique key of the data, and the value of the subset of the second key-value pair data indicates whether the data is selected (true for selected, false for not selected). The second key-value pair dataset is represented as follows:

[0069]

[0070]

[0071] The key of the third key-value pair dataset is a grouping unique key, and the value is a subset of the third key-value pair data. The key of the subset of the third key-value pair data is a type-unique key, and the value is the set of data-unique keys of all selected data. The third key-value pair dataset is represented as follows:

[0072]

[0073] The key of the fourth key-value pair dataset is a unique grouping key, and the value is a subset of the fourth key-value pair data. The key of the subset of the fourth key-value pair data is a unique data key, and the value is the size of the selected data in bytes. The fourth key-value pair dataset is represented as follows:

[0074]

[0075]

[0076] The key of the fifth key-value pair dataset is a group-unique key, and the value is a subset of the fifth key-value pair data. The key of the subset of the fifth key-value pair data is a type-unique key, and the value is the total size in bytes of all selected data corresponding to that type-unique key. The fifth key-value pair dataset is represented as follows:

[0077]

[0078] Based on the user's statistical requirements, the second key-value pair dataset, the third key-value pair dataset, the fourth key-value pair dataset, and the fifth key-value pair dataset, the following statistics are performed:

[0079] 1. Based on the second key-value pair dataset, count the total number of selected data.

[0080] The total number of selected data = 4 images selected in the first group + 2 images selected in the second group = 6.

[0081] 2. Based on the third key-value pair dataset, count the number of selected groups among all selected data.

[0082] The first group has 4 selected images, so the first group is marked as selected; the second group has 2 selected images, so the second group is marked as selected. Therefore, out of a total of 6 selected images, there are 2 groups with selected images; the number of selected groups = the first group + the second group = 2.

[0083] 3. Based on the fourth key-value pair dataset, calculate the total size in bytes of the selected data.

[0084] The first group has 4 images selected, so the total size of the selected data in the first group = 101 + 102 + 103 + 104 = 410. The second group has 2 images selected, so the total size of the selected data in the second group = 201 + 202 = 403; the total size of the selected data in bytes = 410 + 403 = 813.

[0085] 4. Based on the fifth key-value pair dataset, calculate the total byte size of the selected data of each data type in each group. The specific calculation process will not be elaborated here. When selected data is deselected by the user, remove the multiple keys of that data and the key-value pairs corresponding to each key from the corresponding first key-value pair dataset. For example, if the first image in the first group is deselected, then the key-value pairs of that image are deleted from the second, third, fourth, and fifth key-value pair datasets. When calculating the information of all selected images, perform a subtraction operation on the original statistical data.

[0086] When new data is selected, the multiple keys of that data and the key-value pairs corresponding to each key are added to the corresponding first key-value pair dataset. When calculating the information of all selected images, an addition operation is performed on the original statistical data.

[0087] The method provided by this invention can mark the selection of any type of data and data group without modifying the original data. It can perform information statistics according to the user's statistical requirements, such as: counting the size of the selected data, counting the number of bytes of the selected data, counting the group of the selected data, and counting the total number of bytes of the selected data under each group. The statistical function is powerful, the scalability is good, and it effectively improves the efficiency of data management.

[0088] Another embodiment of the present invention provides a data statistics device, such as... Figure 3 As shown, it includes: a display unit 10 for displaying statistical information on various categories; a processing unit 20 for generating multiple keys and corresponding key values ​​based on multiple category information of each selected data when the data state is adjusted to be selected, adding the multiple keys and multiple key values ​​to a pre-constructed first key-value pair dataset with multiple key-value pairs, each key-value pair corresponding to multiple categories of information; and a statistics unit 30 for statistically analyzing various types of information of all selected data based on the first key-value pair dataset, and outputting the statistically analyzed information to the display unit 10 for display.

[0089] The data statistics device of this invention is used to execute the data statistics method in the above embodiments. Its specific processing procedure is the same as that of the data statistics method in the above embodiments, and will not be described in detail here.

[0090] Another embodiment of the present invention provides an electronic device, such as... Figure 4 As shown, it includes: a memory 40, a processor 50, and a computer program stored in the memory 40 and executable on the processor 50, characterized in that the processor 50 implements the method as described above when executing the computer program.

[0091] Another embodiment of the present invention provides a computer storage medium, such as Figure 5 As shown, a computer program is stored on the storage medium 60, which, when executed by the processor 50, implements the method described above.

[0092] Another embodiment of the present invention provides a data statistics system, such as Figure 6As shown, it includes: a network private cloud storage device 70 for storing data from the aforementioned method; an electronic device 80 including a processor 81, a memory 82, and an access port 83; the memory 82 stores an application program that can run on the processor 81; the processor 81 is used to respond to user input through the access port 83 to obtain multiple categories of information about the data stored on the network private cloud storage device 70, and to generate multiple keys and key values ​​corresponding to the multiple keys based on the multiple types of information, and to implement the aforementioned method when executing the application program.

[0093] The above examples illustrate the present invention only to aid in understanding it and are not intended to limit the scope of the invention. Those skilled in the art can make various simple deductions, modifications, or substitutions based on the principles of this invention.

Claims

1. A data statistics method, characterized in that, include: Receive data management instructions input by the user, and adjust the state of the data according to the data management instructions, wherein the state of the data includes at least being selected; If the state of the data is adjusted to be selected, multiple keys and key values ​​corresponding to the multiple keys are generated based on multiple category information of each selected data. The multiple keys and multiple key values ​​are added to multiple pre-constructed first key-value pair datasets, each of which corresponds to each of the category information. Based on the first key-value pair dataset, statistically analyze the category information of all selected data. Each selected data key includes at least: a unique data key, which is defined according to a preset identification identifier of the selected data; the first key-value pair dataset includes at least: a second key-value pair dataset and a third key-value pair dataset. The key of the second key-value pair dataset is a unique key, and the key value is the selection status of the selected data, which is used to store the selection status of each selected data. The key of the third key-value pair dataset is a unique key, and the key value is the size of the selected data in bytes, used to store the size of each selected data in bytes; The state of the data also includes being deselected. When the state of the data is adjusted to be deselected, multiple keys of the data and the key values ​​corresponding to the multiple keys are removed from the corresponding first key-value pair dataset. The step of statistically analyzing various types of information for all selected data based on all the first key-value pair datasets includes: Based on the second key-value pair dataset, count the total number of all selected data; Based on the third key-value pair dataset, calculate the total byte size of all selected data.

2. The method as described in claim 1, characterized in that, The key of the selected data also includes a type-unique key, which is defined according to the data type of the selected data. The first key-value pair dataset includes at least a fourth key-value pair dataset and a fifth key-value pair dataset. The key of the fourth key-value pair dataset is a unique key of the type, and the key value is the data type of the selected data, used to store the data type of each selected data. The key of the fifth key-value pair dataset is a unique key of the type, and the key value is the byte size of the selected data, used to store the byte size of each selected data.

3. The method as described in claim 2, characterized in that, The step of calculating various types of information for all selected data based on all the first key-value pair datasets further includes: Based on the fourth key-value pair dataset, count the total number of each data type in all the selected data; Based on the fifth key-value pair dataset, calculate the total byte size of the selected data for each data type.

4. The method as described in claim 3, characterized in that, Each key of the selected data also includes a grouping unique key, which is defined according to a preset identifier that can group all the selected data; The second key-value pair dataset includes a second key-value pair data subset, where the key of the second key-value pair dataset is the group unique key, the key value is the second key-value pair data subset, the key of the second key-value pair data subset is the data unique key, and the key value is the selection status of the selected data; And / or, the third key-value pair dataset includes a third key-value pair data subset, wherein the key of the third key-value pair dataset is the grouping unique key, the key value is the third key-value pair data subset, the key of the third key-value pair data subset is the type unique key, and the key value is the set of the data unique keys of all selected data; And / or, the fourth key-value pair dataset includes a fourth key-value pair data subset, the key of the fourth key-value pair dataset is the group unique key, the key value is the fourth key-value pair data subset, the key of the fourth key-value pair data subset is the data unique key, and the key value is the byte size of the selected data; And / or, the fifth key-value pair dataset includes a fifth key-value pair data subset, wherein the key of the fifth key-value pair dataset is the group unique key, the key value is the fifth key-value pair data subset, the key of the fifth key-value pair data subset is the type unique key, and the key value is the byte size of all the selected data corresponding to the type unique key.

5. The method as described in claim 4, characterized in that, The step of calculating various types of information for all selected data based on all the first key-value pair datasets further includes: Based on the second key-value pair dataset, the third key-value pair dataset, the fourth key-value pair dataset, and the fifth key-value pair dataset, statistically analyze various types of information for all selected data according to their respective groups.

6. The method according to any one of claims 1-5, characterized in that, Also includes: Display the category information of all the selected data that have been statistically analyzed.

7. A data statistics device, characterized in that, For use in applying the method as described in any one of claims 1 to 6, the data statistics device comprises: The display unit is used to display statistical information for each category. The processing unit is configured to, when the state of the data is adjusted to be selected, generate multiple keys and key values ​​corresponding to the multiple keys based on multiple category information of each selected data; and add the multiple keys and multiple key values ​​to a pre-constructed first key-value pair dataset with multiple key-value pairs, wherein each key-value pair corresponds to one category information of each selected data. The statistics unit is used to count the category information of all selected data based on all the first key-value pair datasets, and output the counted category information to the display unit for display.

8. An electronic device, characterized in that, include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the computer program, implements the method as claimed in any one of claims 1 to 6.

9. A computer storage medium storing a computer program, characterized in that, When the program is executed by the processor, it implements the method as described in any one of claims 1 to 6.

10. A data statistics system, characterized in that, include: A private cloud storage device for storing data according to any one of claims 1 to 6; Electronic devices, including processors, memory, and access ports; The memory stores an application program that can run on the processor; the processor is configured to respond to user input through the access port to obtain multiple categories of data stored on the network private cloud storage device, generate multiple keys and key values ​​corresponding to the multiple categories of data, and implement the method as described in any one of claims 1 to 6 when executing the application program.

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