CN112612923A - Statistical analysis graph construction method, system, electronic device and storage medium - Google Patents
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Abstract
The application discloses a statistical analysis graph construction method, a statistical analysis graph construction system, electronic equipment and a storage medium, and relates to the technical field of statistics. The statistical analysis chart construction method comprises the following steps: acquiring a pre-configured first data source, and configuring the first data source to generate a second data source; acquiring preset chart types, configuration indexes and configuration dimensions, and acquiring corresponding configuration indexes and configuration dimensions based on a second data source and the chart types; and generating a statistical analysis graph according to the graph type, the configuration index, the configuration dimension and the second data source. The data required by the statistical analysis chart can be flexibly selected by configuring the first data source and the second data source; the mapping and connection relation of the data of the statistical analysis graph is designed through the graph type, the configuration index and the configuration dimension, and different forms of statistical analysis graphs can be generated according to actual requirements.
Description
Technical Field
The present application relates to the field of statistical techniques, and in particular, to a method and a system for constructing a statistical analysis graph, an electronic device, and a storage medium.
Background
For a traditional statistical analysis method, the method generally depends on customized chart, excel and other modes, and if the customized chart is adopted to count data, a chart cannot be freely configured; if the excel is adopted to carry out statistics on the data, the data cannot be communicated with the existing database.
Disclosure of Invention
The present application is directed to solving at least one of the problems in the prior art. Therefore, the application provides a statistical analysis chart construction method, a system, an electronic device and a storage medium, which can be communicated with the existing database according to actual requirements and can be integrated in the existing system for use.
The statistical analysis graph construction method according to the embodiment of the first aspect of the application comprises the following steps:
acquiring a pre-configured first data source;
configuring the first data source to generate a second data source;
acquiring preset chart types, configuration indexes and configuration dimensions;
acquiring a corresponding configuration index and a corresponding configuration dimension based on the second data source and the chart type;
and generating a statistical analysis graph according to the chart type, the configuration index, the configuration dimension and the second data source.
The statistical analysis graph construction method according to the embodiment of the application has at least the following beneficial effects:
acquiring a pre-configured first data source, and configuring the first data source to generate a second data source; acquiring preset chart types, configuration indexes and configuration dimensions, and acquiring corresponding configuration indexes and configuration dimensions based on a second data source and the chart types; and generating a statistical analysis graph according to the graph type, the configuration index, the configuration dimension and the second data source. The data required by the statistical analysis chart can be flexibly selected by connecting the first data source and the second data source; the mapping and connection relation of the data of the statistical analysis graph is designed through the graph type, the configuration index and the configuration dimension, and different forms of statistical analysis graphs can be generated according to actual requirements.
According to some embodiments of the present application, the configuring the first data source to generate a second data source includes:
configuring the first data source according to a preset data relation;
and generating a second data source according to the configured first data source.
According to some embodiments of the application, the method further comprises:
acquiring a preset query relation;
configuring the first data source according to the query relation;
and generating a query field of the first data source according to the configured query relation.
According to some embodiments of the application, the method further comprises:
acquiring the configuration index and the configuration dimension;
and generating corresponding summary parameters according to the configuration indexes and the configuration dimensions.
According to some embodiments of the present application, the obtaining the configuration index and the configuration dimension includes:
and acquiring the configuration index and the configuration dimension corresponding to the chart type according to the chart type of the statistical analysis chart.
According to some embodiments of the application, the method further comprises:
acquiring at least one statistical analysis chart and corresponding screening parameters;
and screening the statistical analysis chart according to the screening parameters, and updating the screened statistical analysis chart.
According to some embodiments of the application, the method further comprises:
comparing whether the second data sources of at least two of the statistical analysis graphs are equal;
and if so, generating a correlation analysis graph according to a preset configuration dimension and at least two statistical analysis graphs.
The statistical analysis graph construction system according to the embodiment of the second aspect of the present application includes:
a first obtaining module: the first acquisition module is used for acquiring a pre-configured first data source;
a configuration module: the first configuration module is used for configuring the first data source to generate a second data source;
a second obtaining module: acquiring preset chart types, configuration indexes and configuration dimensions; acquiring a corresponding configuration index and a corresponding configuration dimension based on the second data source and the chart type;
a generation module: and generating a statistical analysis graph according to the chart type, the configuration index, the configuration dimension and the second data source.
The statistical analysis graph construction system according to the embodiment of the application has at least the following beneficial effects:
the statistical analysis graph construction system comprises a first acquisition module, a configuration module, a second acquisition module and a generation module. The method comprises the steps that a first acquisition module acquires a pre-configured first data source; the configuration module configures the first data source to generate a second data source; the configuration module configures the first data source to generate a second data source; the second acquisition module acquires preset chart types, configuration indexes and configuration dimensions; acquiring corresponding configuration indexes and configuration dimensions based on a second data source and the chart type; the generation module generates a statistical analysis graph according to the graph type, the configuration index, the configuration dimension and the second data source. The data required by the statistical analysis chart can be flexibly selected by configuring the first data source and the second data source; the mapping and connection relation of the data of the statistical analysis graph is designed through the graph type, the configuration index and the configuration dimension, and different forms of statistical analysis graphs can be generated according to actual requirements.
An electronic device according to an embodiment of a third aspect of the present application includes:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions that are executed by the at least one processor, so that the at least one processor, when executing the instructions, implements the statistical analysis graph construction method according to any one of the embodiments of the first aspect of the present application.
According to the electronic equipment of the embodiment of the application, at least the following beneficial effects are achieved: the method for constructing the statistical analysis chart is implemented to obtain a pre-configured first data source, and configure the first data source to generate a second data source; acquiring preset chart types, configuration indexes and configuration dimensions, and acquiring corresponding configuration indexes and configuration dimensions based on a second data source and the chart types; and generating a statistical analysis graph according to the graph type, the configuration index, the configuration dimension and the second data source. The data required by the statistical analysis chart can be flexibly selected by configuring the first data source and the second data source; the mapping and connection relation of the data of the statistical analysis graph is designed through the graph type, the configuration index and the configuration dimension, and different forms of statistical analysis graphs can be generated according to actual requirements.
A computer-readable storage medium according to a fourth aspect embodiment of the present application, comprising:
the computer-readable storage medium stores computer-executable instructions for performing the statistical analysis graph construction method according to the embodiment of the first aspect of the present application.
The computer-readable storage instructions according to the embodiments of the present application have at least the following advantages: the method for constructing the statistical analysis chart is implemented to obtain a pre-configured first data source, and configure the first data source to generate a second data source; acquiring preset chart types, configuration indexes and configuration dimensions, and acquiring corresponding configuration indexes and configuration dimensions based on a second data source and the chart types; and generating a statistical analysis graph according to the graph type, the configuration index, the configuration dimension and the second data source. The data required by the statistical analysis chart can be flexibly selected by configuring the first data source and the second data source; the mapping and connection relation of the data of the statistical analysis graph is designed through the graph type, the configuration index and the configuration dimension, and different forms of statistical analysis graphs can be generated according to actual requirements.
Additional aspects and advantages of the present application will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the present application.
Drawings
The present application is further described with reference to the following figures and examples, in which:
FIG. 1 is a flow chart of a statistical analysis graph construction method provided by some embodiments of the present application;
FIG. 2 is a flow chart of a statistical analysis graph construction method according to further embodiments of the present application;
FIG. 3 is a flow chart of a statistical analysis graph construction method according to further embodiments of the present application;
FIG. 4 is a flow chart of a method for constructing a statistical analysis graph according to further embodiments of the present application;
FIG. 5 is a flow chart of a statistical analysis graph construction method according to further embodiments of the present application;
FIG. 6 is a flow chart of a method for constructing a statistical analysis graph according to further embodiments of the present application;
fig. 7 is a block diagram of a module structure of a statistical analysis graph construction system according to some embodiments of the present application.
Reference numerals:
the system comprises a first acquisition module 100, a configuration module 200, a second acquisition module 300 and a generation module 400.
Detailed Description
Reference will now be made in detail to the embodiments of the present application, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of explaining the present application and are not to be construed as limiting the present application.
In the description of the present application, reference to the description of the terms "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present application. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
For a traditional statistical analysis method, the method generally depends on customized chart, excel and other modes, and if the customized chart is adopted to count data, a chart cannot be freely configured; if the excel is adopted to carry out statistics on the data, the data cannot be communicated with the existing database.
Based on the above, the application provides a statistical analysis graph construction method, a statistical analysis graph construction system, an electronic device and a storage medium, which can acquire a pre-configured first data source, configure the first data source and generate a second data source; acquiring preset chart types, configuration indexes and configuration dimensions, and acquiring corresponding configuration indexes and configuration dimensions based on a second data source and the chart types; and generating a statistical analysis graph according to the graph type, the configuration index, the configuration dimension and the second data source. The data required by the statistical analysis chart can be flexibly selected by configuring the first data source and the second data source; the mapping and connection relation of the data of the statistical analysis graph is designed through the graph type, the configuration index and the configuration dimension, and different forms of statistical analysis graphs can be generated according to actual requirements.
In a first aspect, an embodiment of the present application provides a statistical analysis graph construction method.
In some embodiments of the present application, system access is required when constructing the statistical analysis graph, and the programming language and the compiling tool are not limited herein. If the java language is adopted to construct the statistical analysis graph, the system is divided into a reporter-webapi service, a reporter-datastore service and a reporter-adapt service, the database supports mysql, oracle and sql server, the sprint boot framework is adopted for development, and jar and war packets are provided for use. The user needs to configure the reporter-webapi, the reporter-database, the reporter-adapt service and the database in tomcat/nginx. It should be noted that if the jar package is run, the built-in tomcat is actually used, specifically, the java-jar command start is executed on the server, and the war needs to be put under webapps of the external tomcat. And then, modifying the config file in the config folder under the service, and configuring the address of the database and the account password. Since the system adopts a front-end and back-end separated form, the front-end page needs to be separately deployed in the tomcat server. Starting a configured web server, accessing a management background, successfully opening an initialization page, logging in by using an initial administrator account, and supporting to modify an initial password, wherein the initialization page is a construction interface of a statistical analysis chart in the embodiment of the application.
Referring to fig. 1, fig. 1 is a flowchart of a statistical analysis graph construction method provided in some embodiments of the present application, which specifically includes the steps of:
s100, acquiring a pre-configured first data source;
s200, configuring the first data source to generate a second data source;
s300, acquiring preset chart types, configuration indexes and configuration dimensions;
s400, acquiring corresponding configuration indexes and configuration dimensions based on a second data source and the chart type;
and S500, generating a statistical analysis graph according to the graph type, the configuration index, the configuration dimension and the second data source.
In step S100, a plurality of first data sources are accessed through entering a construction interface of a statistical analysis chart, where the plurality of first data sources are data pre-stored in a database, and specifically, the front-end interface is connected to the database to obtain data stored in the plurality of databases, that is, the first data sources.
In step S200, the first data source is configured to obtain a second data source.
In some embodiments, as shown in fig. 2, step S200 specifically includes the steps of:
s210, configuring a first data source according to a preset data relation;
and S220, generating a second data source according to the configured first data source.
In step S210, the preset data relationship includes a mapping relationship, an authority relationship, and an association relationship, and the first data source is configured according to the mapping relationship, the authority relationship, and the association relationship, where the mapping relationship refers to matching of fields of entity classes in the code with fields in a table in the database; the authority relationship refers to setting an authority table in a database, and recording various authorities in the authority table, for example, setting some authorities for a certain preset user role, for example, the administrator role in the embodiment can configure a public chart, but the common user role cannot configure the public chart, and can only view a personal chart, so that different functions can be distinguished according to the role; the association relation refers to multi-table association operation among tables in the database, and is convenient for inquiring, modifying, adding and deleting data associated with the same fields among the tables.
In step S220, the first data source is configured according to the mapping relationship, the authority relationship, and the association relationship, and the configured data source is referred to as a second data source.
In step S300, preset chart types, configuration indexes and configuration dimensions are obtained, where the chart types include bar charts, broken line charts, pie charts, radar charts, stacking charts, funnel charts, index charts, bar charts, area charts, scatter charts, biaxial charts, perspective charts, detail charts, maps, gantt charts and the like, and a user may select an appropriate chart type according to actual needs.
In step S400, a configuration index and a configuration dimension meeting the condition are obtained based on the second data source and the chart type, for example, the configuration index is an increase value, the configuration dimension is a date, and the like, and those skilled in the art can set the configuration index and the configuration dimension according to actual requirements.
In step S500, a statistical analysis graph is generated according to the graph type, the configuration index, the configuration dimension, and the second data source.
In some embodiments, as shown in fig. 3, the method for constructing a statistical analysis graph mentioned in the embodiments of the present application specifically further includes the steps of:
s600, acquiring a preset query relation;
s700, configuring a first data source according to the query relationship;
and S800, generating a query field of the first data source according to the configured query relation.
In step S600, a preset query relationship is obtained, where the query relationship includes configuration input, a connection relationship, a calculation field, and an output node, the configuration input refers to configuring an input data node, the connection relationship is the connection relationship of each data node, the calculation field is a database field that needs to be calculated, and the output node is a result obtained by performing addition, deletion, check and modification according to an input node and using an sql statement.
In step S700, configuring a first data source according to a configuration input, a connection relationship, a calculation field, and an output node;
in step S800, a query field of the first data source is generated according to the configured query relationship, where the query field may be a composite database query statement, such as a database multi-table query statement and a database nested query statement.
The configuration manner of the first data source in the embodiment of the present application may be: the input nodes are tableA and tableB respectively, the connection relationship is left connection, the connection field is a user name, and finally the query field of the first data source is as follows: the name of tableA left join table on table a name may be used to construct a statistical analysis graph according to the embodiment of the present application by generating a query field.
In some embodiments of the present application, sdk, that is, a software development kit, needs to be accessed at a front end, and then an access module, such as a reporter-webapi, a reporter-database, and a reporter-adapt, is selected, the front end of a page generated by using the statistical analysis graph construction method according to the embodiments of the present application has two different display forms, that is, a statistical analysis and a dashboard, the statistical analysis system graph is various graphs drawn by geometric graphs, object images, maps, and the like according to statistics, the dashboard is a form of a statistical data report, and a user can select the statistical data report according to actual requirements.
In some embodiments of the present application, the statistical analysis graph construction method supports custom filter access, that is, a field type and a filter formula of data to be filtered are selected according to actual requirements, the filter defaults to provide three different field types, namely, text input, date and number, and has basic filter formulas that are equal to, not equal to, start with, equal to, not equal to, empty, not empty, and the like, and a user can access a specific personnel/department selection component or expand the filter formula and develop the formula secondarily in an sdk access manner if the user needs to access the basic filter formula. The system has a complete life cycle and is convenient for an access person to call back for use.
In some embodiments, the user may enter the front end of the page generated by the statistical analysis graph construction method of the embodiments of the present application. After the page is opened, the user can create a personal chart or a public chart according to the authority, then the statistical analysis editing page is entered, all the users can see the public chart, and the personal chart can only be seen by the user.
In some embodiments, as shown in fig. 4, the method for constructing a statistical analysis chart in the embodiment of the present application specifically further includes the steps of:
s900, acquiring configuration indexes and configuration dimensions;
and S1000, generating corresponding summary parameters according to the configuration indexes and the configuration dimensions.
In step S900, the first data source or the second data source configured in the above steps is selected at the front end of the system, and the data source field appears in the configuration dimension and the configuration index.
In step S1000, generating corresponding summary parameters, such as summary parameters of configuration dimensions, for example, a date dimension, according to the configuration index and the configuration dimensions, where the summary parameters include but are not limited to year, quarter, month, week, and day; for example, the summary parameters of the configuration indexes include default summary parameters such as sum, maximum, minimum, average, and count. In addition, the same-ring ratio parameters can be configured, and include a ring ratio increase value, a ring ratio increase rate, a same-ring ratio increase value, and a same-ring ratio increase rate, wherein the increase value is current-period value-last-period value, the increase rate is (current-period value-last-period value)/ABS last-period value, the format of the increase rate defaults to percentage and two-bit decimal number. Then, the configuration dimension and the sorting mode and the numerical format of the configuration index can be selected.
The calculation process of the same-loop ratio is specifically described herein, wherein the same-loop ratio refers to comparison at a same time point in an adjacent period, and the loop ratio refers to comparison with a continuous period. Such as: the data 5 corresponds to 1 month and 1 day in 2014, the data 5 corresponds to 1 month and 4 months in 2014, the data 5 corresponds to 1 month and 1 day in 2015, the data 6 corresponds to 1 month and 4 months in 2015, the data 12 corresponds to 1 month and 1 day in 2016, the dimensionality is set up to be quarterly, the indexes are summarized to be sum, the sum is set to be the same-ratio growth value in the last year, the subtraction output is carried out on the value of a certain quarter and the value of the same quarter in the last year at the moment, and the output is as follows: data 0 in the first quarter of 2015, data 1 in the second quarter of 2015, and data 7 in the first quarter of 2016. If the ring ratio increase rate is set to be actually the ring ratio increase rate in the first quarter, then the outputs are 0.00% in the second quarter in 2014 and 20.00% in the second quarter in 2015.
In some embodiments of the present application, the summary parameter may be set by a dimension configuration and a configuration index, such as a date dimension, which may be selected from year, quarter, month, week, and day. For example, the data records the number of steps per day in 2019-2020, specifically: 1000 steps are corresponding to 1/2020, 2000 steps are corresponding to 5/1/2020, and 1500 steps are corresponding to 3/2/2019, and when the summary parameter is selected to be year, the annual indexes are automatically summarized and displayed, and the finally output data structure is as follows: 3000 steps are carried out in 2020, and 1500 steps are carried out in 2019; if the summary parameter is selected as a quarter, 1000 steps are output in the first quarter in 2020, 2000 steps are output in the second quarter in 2020, and 1500 steps are output in the first quarter in 2019, which is not limited to the summary mode setting of multiple dimensions such as date, time, address, speed, etc.
In some embodiments of the present application, the summary parameter may select a sum, maximum, minimum, average, count, and default to a sum value. For example, the data records the number of steps per day in 2020, specifically: 1000 steps are corresponding to 1/2020, 2000 steps are corresponding to 2/1/2020, and 1500 steps are corresponding to 3/2/2020. If the summary parameters select quarter and average, then there are 1500 steps in the first quarter of 2020.
In some embodiments of the present application, a configuration index and a configuration dimension corresponding to a chart type may also be obtained according to the chart type of the statistical analysis chart.
In some embodiments, as shown in fig. 5, the method for constructing a statistical analysis graph mentioned in the embodiments of the present application specifically further includes the steps of:
s1100, acquiring at least one statistical analysis chart and corresponding screening parameters;
s1200, screening the statistical analysis chart according to the screening parameters, and updating the screened statistical analysis chart.
In step S1100, at least one statistical analysis chart and corresponding screening parameters are obtained, and the screening parameters are used to screen some indexes of the statistical analysis chart according to actual conditions, and can be flexibly adjusted, specifically: the filter condition can be set, and the filter formula editing is supported.
In step S1200, the statistical analysis chart is filtered according to the filtering parameters, and the filtered statistical analysis chart is updated.
The embodiment of the application supports the configuration of the drill-down of the statistical chart (including the drill-down of the map and the common statistical chart), and when a certain configuration dimension or configuration area of the statistical chart is clicked, the lower-level statistics of the dimension is entered.
It should be noted that the statistical analysis graph construction method according to the embodiment of the present application further supports custom screening, where the screening function is to screen the first data source or the second data source, and may affect data returned by the interface. The filter can be generated by a user-defined filtering method, the filter supports multi-chart filtering, and a user can select the chart acted by the user when using the filter. The filter also needs to select the filter fields in different filter graphs, and since one filter needs to act on multiple graphs simultaneously, the filter fields are required to be of the same type. The filter may select a filter formula that includes equal to, not equal to, beginning with, equal to, not equal to, empty, not empty, etc. The filter can select filter components, default components are provided with text, date, range date, number range and other components, if more components are needed, such as personnel and department filters, sdk injection components are needed when accessing.
When injecting components, different custom components need to be selected according to the field types in the first data source or the second data source, for example: the metadata field type is 260, and the parameters of the component are "personnel singleton"; the metadata field type is 261, and the parameters of the component are "department singleton"; the metadata field type is 270, and the parameters of the component are 'personnel multiple choice'; the metadata field type is 271, and the parameters of the component are 'department multiple choice'; the metadata field type is 9 and the parameters of the component are "flow state". When the filter is accessed, the current field type can be obtained, a user only needs to transmit the field type to the self-packaged front-end component, the front-end component can be selected from the filter components, and then the filter can be normally selected for use in the created filter when the filter is used.
In some embodiments, as shown in fig. 6, the method for constructing a statistical analysis graph mentioned in the embodiments of the present application specifically further includes the steps of:
s1300, comparing whether the second data sources of the at least two statistical analysis graphs are equal or not;
and S1400, if the two statistical analysis graphs are equal, generating a correlation analysis graph according to a preset configuration dimension and the at least two statistical analysis graphs.
In step S1300, at least two statistical analysis charts are acquired, and whether the second data sources of the acquired statistical analysis charts are equal or not is compared.
In step S1400, if they are equal, it indicates that the two have a common data source, and updates at least two statistical analysis graphs according to the preset configuration dimension, and generates a correlation analysis graph. The method specifically comprises the following steps: using different graphs of the same data source, when clicking on a dimension, such as the time dimension, a statistical graph of the dimension is jointly drilled down and named as a correlation analysis graph.
In a second aspect, an embodiment of the present application further provides a statistical analysis chart construction system for executing the statistical analysis chart construction method mentioned in the embodiment of the first aspect.
In some embodiments, as shown in fig. 7, the statistical analysis graph building system includes a first obtaining module 100, a configuring module 200, a second obtaining module 300, and a generating module 400. The first obtaining module 100 obtains a preconfigured first data source; the configuration module 200 configures the first data source to generate a second data source; the second obtaining module 300 obtains preset chart types, configuration indexes and configuration dimensions; acquiring corresponding configuration indexes and configuration dimensions based on a second data source and the chart type; the generation module 400 generates a statistical analysis graph based on the graph type, the configuration index, the configuration dimension, and the second data source. The data required by the statistical analysis chart can be flexibly selected by configuring the first data source and the second data source; the mapping and connection relation of the data of the statistical analysis graph is designed through the graph type, the configuration index and the configuration dimension, and different forms of statistical analysis graphs can be generated according to actual requirements.
In a third aspect, an embodiment of the present application further provides an electronic device.
In some embodiments, an electronic device includes: at least one processor, and a memory communicatively coupled to the at least one processor; the memory stores instructions, and the instructions are executed by the at least one processor, so that the at least one processor can implement any statistical analysis graph construction method in the embodiment of the present application when executing the instructions.
The processor and memory may be connected by a bus or other means.
The memory, which is a non-transitory computer readable storage medium, may be used to store a non-transitory software program and a non-transitory computer executable program, such as the statistical analysis graph construction method described in the embodiments of the present application. The processor implements the statistical analysis graph construction method described above by running a non-transitory software program and instructions stored in memory.
The memory may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area can store and execute the statistical analysis chart construction method. Further, the memory may include high speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory located remotely from the processor, and these remote memories may be connected to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The non-transitory software programs and instructions required to implement the statistical analysis graph construction method described above are stored in a memory and, when executed by one or more processors, perform the statistical analysis graph construction method mentioned in the first embodiment of the above aspect.
In a fourth aspect, the present application further provides a computer-readable storage medium.
In some embodiments, the computer-readable storage medium stores computer-executable instructions for performing the statistical analysis graph construction method mentioned in the embodiments of the first aspect.
In some embodiments, the storage medium stores computer-executable instructions that, when executed by one or more control processors, for example, by a processor in the electronic device, cause the one or more processors to perform the statistical analysis graph construction method.
The above-described embodiments of the apparatus are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may also be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
One of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
The embodiments of the present application have been described in detail with reference to the drawings, but the present application is not limited to the embodiments, and various changes can be made within the knowledge of those skilled in the art without departing from the gist of the present application. Furthermore, the embodiments and features of the embodiments of the present application may be combined with each other without conflict.
Claims (10)
1. The statistical analysis graph construction method is characterized by comprising the following steps:
acquiring a pre-configured first data source;
configuring the first data source to generate a second data source;
acquiring preset chart types, configuration indexes and configuration dimensions;
acquiring a corresponding configuration index and a corresponding configuration dimension based on the second data source and the chart type;
and generating a statistical analysis graph according to the chart type, the configuration index, the configuration dimension and the second data source.
2. The method of constructing a statistical analysis graph according to claim 1, wherein the configuring the first data source to generate a second data source comprises:
configuring the first data source according to a preset data relation;
and generating a second data source according to the configured first data source.
3. The statistical analysis graph construction method according to claim 2, further comprising:
acquiring a preset query relation;
configuring the first data source according to the query relation;
and generating a query field of the first data source according to the configured query relation.
4. The statistical analysis graph construction method according to claim 3, further comprising:
acquiring the configuration index and the configuration dimension;
and generating corresponding summary parameters according to the configuration indexes and the configuration dimensions.
5. The method according to claim 4, wherein the obtaining the configuration index and the configuration dimension comprises:
and acquiring the configuration index and the configuration dimension corresponding to the chart type according to the chart type of the statistical analysis chart.
6. The statistical analysis graph construction method according to claim 5, further comprising:
acquiring at least one statistical analysis chart and corresponding screening parameters;
and screening the statistical analysis chart according to the screening parameters, and updating the screened statistical analysis chart.
7. The statistical analysis graph construction method according to claim 6, further comprising:
comparing whether the second data sources of at least two of the statistical analysis graphs are equal;
and if so, generating a correlation analysis graph according to a preset configuration dimension and at least two statistical analysis graphs.
8. The statistical analysis graph construction system is characterized by comprising:
a first obtaining module: the first acquisition module is used for acquiring a pre-configured first data source;
a configuration module: the configuration module is used for configuring the first data source to generate a second data source;
a second obtaining module: acquiring preset chart types, configuration indexes and configuration dimensions; acquiring a corresponding configuration index and a corresponding configuration dimension based on the second data source and the chart type;
a generation module: and generating a statistical analysis graph according to the chart type, the configuration index, the configuration dimension and the second data source.
9. An electronic device, comprising:
at least one processor, and,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions for execution by the at least one processor to cause the at least one processor, when executing the instructions, to implement the statistical analysis graph construction method of any one of claims 1 to 8.
10. Computer-readable storage media, characterized in that the computer-readable storage media stores computer-executable instructions for performing the statistical analysis graph construction method according to any one of claims 1 to 8.
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