CN113010509A

CN113010509A - Method and device for counting use data in specific time period and electronic equipment

Info

Publication number: CN113010509A
Application number: CN202110369006.6A
Authority: CN
Inventors: 张润; 邹广宇; 刘�文
Original assignee: Xinao Shuneng Technology Co Ltd
Current assignee: Xinao Shuneng Technology Co Ltd
Priority date: 2021-04-06
Filing date: 2021-04-06
Publication date: 2021-06-22

Abstract

The disclosure is applicable to the technical field of data statistics, and provides a method, a device and electronic equipment for counting use data in a specific time period, wherein a specific implementation mode of the method comprises the following steps: acquiring a data index of a preset unit time; acquiring summarized data of preset unit time based on the data index of the preset unit time; calculating to obtain use data of the preset unit time based on the summarized data of the preset unit time; acquiring use data in a preset time period to obtain a use data set; target data is calculated from the usage data set. This is disclosed through the summary data who obtains predetermineeing the unit interval, can obtain the data of multiple sources in predetermineeing the unit interval for the result of statistics is more accurate. By acquiring the use data in a preset time period, a plurality of items of data in a certain time period can be freely selected to obtain a use data set which accords with a target, so that target data are obtained through statistics.

Description

Method and device for counting use data in specific time period and electronic equipment

Technical Field

The present disclosure relates to the field of data statistics, and in particular, to a method and an apparatus for counting usage data in a specific time period, and an electronic device.

Background

At present, the comprehensive value of an enterprise is judged, data such as annual power consumption are important judgment standards, the whole annual power data cannot be directly acquired, the enterprise has a large number of electric equipment and corresponds to an electric meter for recording the power consumption of the electric equipment, the power consumption of each equipment in different time periods is different due to the fact that the number of the electric equipment counted by the electric meter in different lines is different, and therefore the data such as the annual power consumption of the enterprise cannot be accurately counted.

Disclosure of Invention

In view of this, the embodiments of the present disclosure provide a method, an apparatus, and an electronic device for counting usage data in a specific time period, so as to solve the technical problem that annual power consumption of an enterprise cannot be accurately counted because the number of electric devices counted by electric meters in different lines is different and the power consumption used by each device in different time periods is also different.

In a first aspect, some embodiments of the present disclosure provide a method of counting usage data over a particular period of time, the method comprising: acquiring a data index of a preset unit time; acquiring summarized data of preset unit time based on the data index of the preset unit time; calculating to obtain use data of the preset unit time based on the summarized data of the preset unit time; acquiring use data in a preset time period to obtain a use data set; target data is calculated from the usage data set.

In a second aspect, some embodiments of the present disclosure provide an apparatus for counting usage data in a specific time period, comprising: an index unit: acquiring a data index of a preset unit time; an acquisition unit: acquiring summarized data of preset unit time based on the data index of the preset unit time; using the data unit: calculating to obtain use data of the preset unit time according to the summarized data of the preset unit time; a summary unit: acquiring all use data of preset unit time in a specific time period to obtain a use data set; target data unit: target data is calculated from the usage data set.

In a third aspect, some embodiments of the present disclosure provide an electronic device, comprising: one or more processors; a storage device having one or more programs stored thereon; when executed by the one or more processors, cause the one or more processors to implement a method as described in the first aspect.

In a fourth aspect, some embodiments of the disclosure provide a computer readable storage medium storing a computer program which, when executed by a processor, implements a method as described in the first aspect.

Compared with the prior art, the embodiment of the disclosure has the advantages that at least:

(1) by acquiring the summarized data of the preset unit time, the data of various sources in the preset unit time can be acquired, so that the statistical result is more accurate.

(2) By acquiring the use data in a preset time period, a plurality of items of data in a certain time period can be freely selected to obtain a use data set which accords with a target, so that target data are obtained through statistics.

Drawings

To more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and other drawings can be obtained by those skilled in the art without inventive efforts.

FIG. 1 is a schematic diagram of one application scenario of a method of counting usage data over a particular time period according to an embodiment of the present disclosure;

FIG. 2 is a flow diagram of some embodiments of a method of counting usage data in a particular time period according to an embodiment of the present disclosure;

FIG. 3 is a flow diagram of further embodiments of methods of counting usage data for a particular period of time according to embodiments of the present disclosure;

FIG. 4 is a flow diagram of further embodiments of methods of counting usage data for a particular period of time according to embodiments of the present disclosure;

FIG. 5 is a block diagram of some embodiments of a data device used during a statistical specified time period in accordance with embodiments of the present disclosure;

FIG. 6 is a schematic structural diagram of an electronic device suitable for use in implementing some embodiments of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it is to be understood that the disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the disclosure are for illustration purposes only and are not intended to limit the scope of the disclosure.

It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings. The embodiments and features of the embodiments in the present disclosure may be combined with each other without conflict.

It should be noted that the terms "first", "second", and the like in the present disclosure are only used for distinguishing different devices, modules or units, and are not used for limiting the order or interdependence relationship of the functions performed by the devices, modules or units.

It is noted that references to "a", "an", and "the" modifications in this disclosure are intended to be illustrative rather than limiting, and that those skilled in the art will recognize that "one or more" may be used unless the context clearly dictates otherwise.

The names of messages or information exchanged between devices in the embodiments of the present disclosure are for illustrative purposes only, and are not intended to limit the scope of the messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

FIG. 1 is a schematic diagram of one application scenario of a method of counting usage data over a particular time period, according to some embodiments of the present disclosure.

In the application scenario of fig. 1, first, the computing device 101 may obtain a data index 102 of a preset unit time. The computing device 101 may then obtain summary data 103 for a preset unit of time based on the data indicator 102 for the preset unit of time. Thereafter, the computing device 101 may calculate usage data 104 for a preset unit time based on the summarized data 103 for the preset unit time. Thereafter, the computing device 101 may obtain usage data for a preset period of time, resulting in a usage data set 105. Finally, the computing device 101 may calculate the target data 106 from the usage data set 105.

The computing device 101 may be hardware or software. When the computing device is hardware, it may be implemented as a distributed cluster composed of multiple servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices enumerated above. It may be implemented, for example, as multiple software or software modules to provide distributed services, or as a single software or software module. And is not particularly limited herein.

It should be understood that the number of computing devices in FIG. 1 is merely illustrative. There may be any number of computing devices, as implementation needs dictate.

With continued reference to fig. 2, a flow 200 of some embodiments of a method of counting usage data for a particular period of time according to the present disclosure is shown. The method may be performed by the computing device 101 of fig. 1. The method for counting the use data in the specific time period comprises the following steps:

step 201, acquiring a data index of a preset unit time.

In some embodiments, the subject to be counted may be a business, an organization, a government agency, or the like. The data to be counted can be daily average power consumption, water consumption and the like. The preset unit time may be per minute, per hour, per quarter, per year, or the like. The type of the data can be four integer types (byte, short, int, long), two floating point types (float, double), a character type (char) or a boolean type (boolean), etc.; the data index comprises detailed data to be collected and a calculation formula. The detailed data to be collected may include the number of data types to be collected, the number of data of each data type, the numerical value of each data, and the like. The data indexes further comprise index calculation formulas used for calculation, and the index calculation formulas are manually formulated according to the conditions of the statistical purposes, individuals to be counted and the like.

Step 202, acquiring summarized data of a preset unit time based on the data index of the preset unit time.

In some embodiments, an executing entity (such as the computing device 101 shown in fig. 1) of the statistical method may obtain summarized data of a preset unit time based on a data index of the preset unit time. The data type of the single data in the summarized data may be four integer types (byte, short, int, long), two floating point types (float, double), a character type (char), a boolean type (boolean), or the like. The summarized data may be the same type of data, such as integer type data, or different types of data, such as integer type data plus floating point type data.

And 203, calculating to obtain the use data of the preset unit time based on the summarized data of the preset unit time.

In some embodiments, the execution subject may calculate usage data of a preset unit time based on the summarized data of the preset unit time. The calculation formula is the index calculation formula obtained in step 201, and the usage data of the preset time can be obtained by substituting the summarized data into the calculation formula.

And 204, acquiring the use data in a preset time period to obtain a use data set.

In some embodiments, the execution subject may obtain the usage data within a preset time period to obtain the usage data set. The preset time period consists of at least 2 preset unit times; the usage data set is composed of at least 2 usage data of a preset unit time.

Step 205, calculating target data according to the use data set.

In some embodiments, the executing entity obtains the target data by calculating: firstly, acquiring a target calculation formula which is manually formulated; substituting the data of the use data set into a target calculation formula; and thirdly, obtaining target data.

To better understand the present embodiment, the following describes the present embodiment with a specific application scenario:

the execution subject may be the computing device 101 in fig. 1, the subject to be counted is enterprise a, and the data to be counted is the annual daily average power consumption of enterprise a, which is expressed in kilowatt-hour (kWh); the computing device 101 may obtain daily data for enterprise a. Presetting unit time as daily, and the data to be counted is the daily average power consumption of the enterprise A; the enterprise A has 3 power consumption devices, namely a1, a2 and a3 respectively, and 3 electric meters, namely e1, e2 and e3 respectively, for recording power consumption data; wherein E1 records the sum of daily power consumption data of a device a1 and a2, E2 records the sum of daily power consumption data of a2 and a3, E3 records the sum of daily power consumption data of a1 and a3, and if the average daily power consumption data of the enterprise A is E, the index calculation formula is as follows: e ═ E1+ E2+ E3)/2.

The computing device 101 may obtain power consumption data e1, e2, e3 of 3 meters a day before enterprise a as (128.05,39.10,412.39), respectively; substituting E1, E2 and E3 into a calculation formula to obtain the electricity consumption E of the enterprise A on the day before the day of statistics, namely (128.05+39.10+412.39)/2, namely 579.54 (kWh); according to the steps, all day power consumption data of the enterprise A in the previous year from the statistical day are obtained to form a usage data set {457.01, 345.23, 676.13, 503.22, 687.57, 362.15.. once.. so, 456.87, 398.69, 579.54 }. Since the target data of the statistics is annual daily average power consumption of the enterprise a, averaging the data in the data set, and if the target data is Z, the target calculation formula is:

z ═ (sum of all values in the set)/(number of values in the set).

The annual daily average power consumption of enterprise a was 518.88(kWh) by adding all the data in the usage data set and dividing by the number of values in the set.

The beneficial effects of the disclosed embodiment include the following:

In addition, the application scenarios provided in the present embodiment are only used to explain some embodiments of the present disclosure, and do not limit the scope of the present disclosure.

With continuing reference to FIG. 3 and with continuing reference to FIG. 3, a flow 300 of further embodiments of methods of counting usage data for a particular time period according to the present disclosure is shown. The method may be performed by the computing device 101 of fig. 1. The method for counting the data used in the specific time period comprises the following steps:

step 301, acquiring a data index of a preset unit time.

Step 302, acquiring summarized data of a preset unit time based on the data index of the preset unit time.

Step 303, calculating to obtain the usage data of the preset unit time based on the summarized data of the preset unit time.

And 304, acquiring the use data in a preset time period to obtain a use data set.

In some embodiments, the specific implementation and technical effects of

steps

301 and 304 may refer to

steps

201 and 204 in the embodiments corresponding to fig. 2, which are not described herein again.

Step 305, clearing error data in the usage data set.

Due to storage and calculation of large quantities of data, error data are occasionally generated in the data set; in some embodiments, the usage data set includes some error data, and the error data may be data with a null value, data with a negative value, data with an error in data type, or the like; after the error data is located, the error data is deleted from the usage data set. The data with a null numerical value refers to data with a null numerical value, and is different from the data with a 0 numerical value; when the default data is a positive value, the generated data with the negative numerical value is error data; data with wrong data type means that the data is different from the default stored data type, and sometimes an error code is indicated, such as NAN in a numerical data set.

And step 306, calculating to obtain target data.

In some embodiments, this step may refer to step 205 in those embodiments corresponding to fig. 2, which is not described herein again.

The embodiment of the disclosure can reduce the interference of invalid data in the statistical data to the final result and increase the accuracy of the statistical data by clearing the error data.

With further reference to fig. 4, a flow 400 of further embodiments of methods of counting usage data for a particular time period according to the present disclosure is shown. The method may be performed by the computing device 101 of fig. 1.

The method for counting the use data in the specific time period comprises the following steps:

step 401, acquiring a data index of a preset unit time.

And 402, acquiring summarized data of a preset unit time based on the data index of the preset unit time.

And step 403, calculating to obtain the use data of the preset unit time based on the summarized data of the preset unit time.

Step 404, obtaining the usage data in a preset time period to obtain a usage data set.

In some embodiments, the specific implementation and technical effects of

steps

401 and 404 may refer to

steps

Step 405, calculating initial target data according to the use data set.

In some embodiments, the executing entity obtains the initial target data by calculating: firstly, acquiring an initial target calculation formula which is manually formulated; substituting the data of the use data set into an initial target calculation formula; and thirdly, obtaining initial target data.

Step 406, screening the data in the usage data set to obtain a screened data set.

In some embodiments, an executing agent of the statistical method (e.g., computing device 101 shown in fig. 1) may filter the data in the usage data set to obtain a filtered data set. The screening method may be to remove a single data, a certain piece of data, a plurality of data or a plurality of pieces of data in the data set, or may be to screen data of a certain data type, or may be to screen data within a certain range, or the like.

And step 407, calculating to obtain screening target data according to the screening data set.

In some embodiments, the execution subject obtains the screening target data by calculating: firstly, acquiring a manually formulated screening target calculation formula; substituting the data of the use data set into a screening target calculation formula; and step three, obtaining screening target data.

Step 408, comparing the initial target data with the screening target data, and selecting the optimal data.

In some embodiments, the execution subject compares the initial target data with the screening target data to select the optimal data. And the optimal data is obtained by manually selecting one of the optimal data and the optimal data as the optimal data according to the statistical purpose.

the execution subject may be the computing device 101 in fig. 1, the subject to be counted is enterprise B, and the data to be counted is the annual daily average power consumption of the enterprise B in 2020; referring to step 200, all the daily power consumption data of the last year of enterprise B may be obtained, and based on this data, a usage data set {257.23, 312.59, 566.13, 419.86, 699.19, 358.15......, 499.11, 519.49, 545.78} is formed, which has 366 data in total. Since the target data counted this time is the annual daily average power consumption of the enterprise B, the average number in the usage data set is obtained, the target data is set to Z, and the obtained initial target calculation formula is:

z ═ (sum of all values in the set)/(number of values in the set).

The initial objective of the annual daily average power consumption for business B was 518.88(kWh) by summing all the data in the usage data set divided by the number of values in the set (366). Due to the influence of epidemic situations, data of the enterprise B in 2-6 months in 2020 is obviously abnormal, so that the data needs to be screened and removed, and the annual daily average power consumption value is calculated. After removing the partial data, a screening data set is obtained, wherein the screening data set comprises 215 data in total, and the screening data set comprises {257.01, 345.23, 661.13, 345.22, 589.57, 362.15,........., 329.87, 425.69, 516.55 }. The obtained screening target data is the same as the calculation formula of the initial target data, so the data in the screening data set is substituted into the initial target calculation formula, and the screening target data is 616.06(kWh) by adding all the data in the use data set and dividing by the number of values in the set (366).

Compare target data 518.88 with screening target data 616.06. When the annual average daily power consumption of the enterprise a is obtained, the power consumption during the epidemic situation is abnormal data, and therefore the screened target data 616.06(kWh) is selected as the optimal data.

Some embodiments of the present disclosure may screen data that better meet statistical requirements from the acquired data by screening the data, and may also obtain different types of statistical data by screening the data, thereby increasing the flexibility and accuracy of the method for using data in a specific time period of the statistics.

With further reference to fig. 5, as an implementation of the above method for the above figures, the present disclosure provides some embodiments of a method for counting usage data in a specific time period, and these embodiments of the apparatus correspond to those of the method described above in fig. 2, and the apparatus can be applied to various electronic devices.

As shown in fig. 5, the method 500 of counting usage data in a specific time period of some embodiments includes: an index unit 501, an acquisition unit 502, a usage data unit 503, a summary unit 504, and a target data unit 505. Wherein, the index unit 501 is configured to obtain a data index of a preset unit time; the obtaining unit 502 is configured to obtain summarized data of a preset unit time based on the data index of the preset unit time; the usage data unit 503 is configured to calculate usage data of a preset unit time according to the summarized data of the preset unit time; the summarizing unit 504 is configured to obtain usage data of all preset unit times in a specific time period, resulting in a usage data set; the target data unit 505 is configured to calculate target data from the usage data set.

In some optional implementations of some embodiments, the target data unit 505 is further configured to: clearing error data in the usage data set.

In some optional implementations of some embodiments, the error data may include data with a null value, data with a negative value, data with an error in data type, and the like.

In some optional implementations of some embodiments, the target data unit 505 is further configured to: screening the data in the use data set to obtain a screened data set; calculating according to the screening data set to obtain screening target data; and comparing the target data with the screening target data, and selecting the optimal data.

It will be understood that the elements described in the apparatus 500 correspond to various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting advantages described above with respect to the method are also applicable to the apparatus 500 and the units included therein, and are not described herein again.

Referring now to FIG. 6, a block diagram of an electronic device (e.g., computing device 101 of FIG. 1)600 suitable for use in implementing some embodiments of the present disclosure is shown. The server shown in fig. 6 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 6, electronic device 600 may include a processing means (e.g., central processing unit, graphics processor, etc.) 601 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage means 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data necessary for the operation of the electronic apparatus 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

Generally, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touch pad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, etc.; output devices 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, tape, hard disk, etc.; and a communication device 609. The communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 illustrates an electronic device 600 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided. Each block shown in fig. 6 may represent one device or may represent multiple devices as desired.

In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flow diagrams may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In some such embodiments, the computer program may be downloaded and installed from a network through the communication device 609, or installed from the storage device 608, or installed from the ROM 602. The computer program, when executed by the processing device 601, performs the above-described functions defined in the methods of some embodiments of the present disclosure.

It should be noted that the computer readable medium described above in some embodiments of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In some embodiments of the disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.

In some embodiments, the clients, servers may communicate using any currently known or future developed network Protocol, such as HTTP (HyperText Transfer Protocol), and may interconnect with any form or medium of digital data communication (e.g., a communications network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the Internet (e.g., the Internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed network.

The computer readable medium may be embodied in the apparatus; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to: acquiring a data index of a preset unit time; acquiring summarized data of preset unit time based on the data index of the preset unit time; calculating to obtain use data of the preset unit time based on the summarized data of the preset unit time; acquiring use data in a preset time period to obtain a use data set; target data is calculated from the usage data set.

Computer program code for carrying out operations for embodiments of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in some embodiments of the present disclosure may be implemented by software, and may also be implemented by hardware. The described units may also be provided in a processor, and may be described as: a processor includes an index unit, an acquisition unit, a usage data unit, a summary unit, and a target data unit. For example, the index unit may also be described as a "unit that acquires a data index of a preset unit time".

The functions described herein above may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), systems on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), and the like.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is made without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features with similar functions disclosed in the embodiments of the present disclosure are mutually replaced to form the technical solution.

Claims

1. A method of counting usage data for a specified period of time, the method comprising:

acquiring a data index of a preset unit time;

acquiring summarized data of preset unit time based on the data index of the preset unit time;

calculating to obtain use data of the preset unit time based on the summarized data of the preset unit time;

acquiring use data in a preset time period to obtain a use data set;

and calculating to obtain target data according to the use data set.

2. The method for counting usage data in a specific time period according to claim 1, wherein after obtaining the usage data in a preset time period and obtaining the usage data set, the method further comprises:

clearing error data in the usage data set.

3. The method of claim 2, wherein the error data comprises at least one of: data with negative value, data with null value and data with wrong data type.

4. The method for counting usage data in a specific time period according to any one of claims 1 to 3, wherein the calculating target data according to the usage data set comprises:

and calculating to obtain initial target data according to the use data set.

Screening the data in the use data set to obtain a screened data set;

calculating to obtain screening target data according to the screening data set;

and comparing the initial target data with the screening target data, and selecting the optimal data.

5. An apparatus for counting usage data for a specified period of time, comprising:

an index unit configured to acquire a data index of a preset unit time;

an obtaining unit configured to obtain summarized data of a preset unit time based on the data index of the preset unit time;

the use data unit is configured to calculate use data of the preset unit time according to the summarized data of the preset unit time;

the summarizing unit is configured to acquire the use data of all preset unit times in a specific time period to obtain a use data set;

and the target data unit is configured to obtain target data through calculation according to the use data set.

6. The apparatus of claim 5, further comprising:

clearing error data in the usage data set.

7. The apparatus of claim 5, the error data comprising at least one of: data with negative value, data with null value and data with wrong data type.

8. The apparatus of any of claims 5 to 7, wherein the target data unit comprises:

and calculating to obtain initial target data according to the use data set.

Screening the data in the use data set to obtain a screened data set;

9. An electronic device, comprising:

one or more processors;

a storage device having one or more programs stored thereon;

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-4.

10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 4.