CN114218443A - Configuration method and equipment of trend analysis chart - Google Patents
Configuration method and equipment of trend analysis chart Download PDFInfo
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- CN114218443A CN114218443A CN202111314655.2A CN202111314655A CN114218443A CN 114218443 A CN114218443 A CN 114218443A CN 202111314655 A CN202111314655 A CN 202111314655A CN 114218443 A CN114218443 A CN 114218443A
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- G06F16/90—Details of database functions independent of the retrieved data types
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- G06—COMPUTING; CALCULATING OR COUNTING
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- G06F16/90—Details of database functions independent of the retrieved data types
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Abstract
The application discloses a method and equipment for configuring a trend analysis chart, wherein the method comprises the following steps: receiving a trend analysis chart configuration instruction of a user; determining a target data set, wherein each piece of data in the target data set comprises contents corresponding to a plurality of fields respectively; responding to the analysis configuration operation of a user, and performing first analysis configuration on a first trend analysis graph corresponding to the target data set; wherein the first analysis configuration includes selecting different fields as a first statistical classification and a first statistical unit of the first trend analysis graph, respectively; responding to the penetration configuration operation of the user, and performing second analysis configuration on the second trend analysis chart; the second analysis configuration comprises the steps of respectively selecting different fields as a second statistical classification and a second statistical unit of a second trend analysis chart, and the second trend analysis chart is obtained by skipping in response to the preset operation of the first trend analysis chart. Through the mode, the flexibly-configured multi-level penetration trend analysis graph can be provided.
Description
Technical Field
The application relates to the technical field of business intelligent analysis, in particular to a configuration method and equipment of a trend analysis chart.
Background
In data visualization applications, especially in enterprise digital application platforms, how to realize flexible configuration and multi-level penetration of trend contrastive analysis graphs is a significant problem. The traditional implementation method mainly comprises customization development and trend analysis graph configuration built in a data analysis platform, wherein the customization development process is complex and has strong dependence on developers; and the data analysis platform based built-in trend analysis chart configuration has few patterns and poor universality.
Disclosure of Invention
The technical problem mainly solved by the application is to provide a configuration method and equipment of a trend analysis chart, which can provide a flexibly configured and multi-level penetrating trend analysis chart.
In order to solve the above technical problem, a first aspect of the present application provides a method for configuring a trend analysis graph, where the method includes: receiving a trend analysis chart configuration instruction of a user; determining a target data set, wherein each piece of data in the target data set comprises contents corresponding to a plurality of fields respectively; responding to analysis configuration operation of a user, performing first analysis configuration on a first trend analysis graph corresponding to a target data set, wherein the first analysis configuration comprises that different fields are respectively selected as a first statistical classification and a first statistical unit of the first trend analysis graph, and the first trend analysis graph is used for performing classification statistics on content corresponding to the first statistical unit of all data in the target data set based on the first statistical classification; and performing second analysis configuration on the second trend analysis chart in response to the penetration configuration operation of the user, wherein the second analysis configuration comprises selecting different fields as a second statistical classification and a second statistical unit of the second trend analysis chart respectively, the second trend analysis chart is obtained by skipping in response to the preset operation of the first trend analysis chart, and the content corresponding to the second statistical unit of the partial data in the target data set is subjected to classification statistics based on the second statistical classification.
In order to solve the above technical problem, a second aspect of the present application provides an electronic device, which includes a memory and a processor coupled to each other, the memory stores program instructions, and the processor is configured to execute the program instructions stored in the memory, so as to implement the method for configuring a trend analysis graph of the first aspect.
In order to solve the above technical problem, a third aspect of the present application provides a computer-readable storage medium for storing program instructions, which can be executed to implement the above configuration method of the trend analysis graph.
In the above scheme, a target data set is determined according to a user instruction, a first analysis configuration is performed on a first trend analysis graph corresponding to the target data set in response to an analysis configuration operation of a user, a second analysis configuration is performed on a second trend analysis graph in response to a penetration configuration operation of the user, the second trend analysis graph is obtained by jumping in response to a preset operation of the first trend analysis graph, that is, a layer-level penetration is configured between the first and second trend analysis graphs, so that the configuration is performed as a multi-level penetration of the trend analysis graphs, and a statistical classification and a statistical unit of each configuration analysis graph of a hierarchical penetration relation can be configured, so that the flexible configuration of the configuration analysis graphs is realized, so that the configuration of the configuration analysis graphs can be performed based on different requirements, and the repeated development of the configuration analysis graphs for different requirements is not required, the development efficiency can be improved.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating a first embodiment of a method for configuring a trend analysis chart according to the present application;
FIG. 2 is a schematic diagram of one embodiment of a first trend analysis graph provided herein;
FIG. 3 is a schematic diagram of one embodiment of a second trend analysis graph provided herein;
FIG. 4 is a schematic flow chart diagram illustrating a second embodiment of a method for configuring a trend analysis chart according to the present application;
FIG. 5 is a schematic view of another embodiment of a first trend analysis graph provided herein;
FIG. 6 is a schematic flow chart diagram illustrating a third embodiment of a method for configuring a trend analysis chart according to the present application;
FIG. 7 is a schematic flow chart diagram illustrating a fourth embodiment of a method for configuring a trend analysis chart according to the present application;
FIG. 8 is a flowchart illustrating an embodiment of step S120 of the method for configuring a trend analysis chart according to the present invention;
FIG. 9 is a schematic flow chart diagram illustrating a fifth embodiment of a method for configuring a trend analysis chart according to the present application;
FIG. 10 is a schematic diagram of a frame structure of an electronic device provided herein;
FIG. 11 is a block diagram of an embodiment of a computer storage medium according to the present application.
Detailed Description
The technical solutions in the embodiments of the present application are clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that, in the embodiments of the present application, there are descriptions related to "first", "second", etc., and the descriptions of "first", "second", etc. are only used for descriptive purposes and are not to be interpreted as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature.
Referring to fig. 1-3, fig. 1 is a schematic flow chart diagram illustrating a first embodiment of a method for configuring a trend analysis chart according to the present application; FIG. 2 is a schematic diagram of one embodiment of a first trend analysis graph provided herein; fig. 3 is a schematic diagram of an embodiment of a second trend analysis chart provided in the present application. The configuration method comprises the following steps:
s110: and receiving a trend analysis chart configuration instruction of a user.
The electronic equipment receives a trend analysis chart configuration instruction of a user and enters a configuration interface of the trend analysis chart, wherein the configuration instruction can be single-click or double-click operation.
S120: a target data set is determined.
Each piece of data in the target data set comprises content corresponding to a plurality of fields respectively.
The data in the target data set can be generated by data in the original database, or newly imported data by the user, or part of the data can be imported for the original database and part of the data can be imported for the user. The data in the target data set is arranged according to fields or sub-fields, wherein the fields include time, organization, region, amount, quantity, etc., and the fields may also contain corresponding sub-fields, for example, the time field may contain sub-fields of year, quarter, month, day, etc.; the organization field may contain subfields such as a superior organization name, a subordinate organization name, a superior organization name code, a subordinate organization name code, etc.; a region may contain subfields such as province, city, district, county, etc. The target data set may contain a plurality of pieces of data, each piece of data may contain contents corresponding to a plurality of fields, for example, one piece of data contains related information corresponding to fields of time, unit name, unit organization code, unit turnover, area, and the like.
S130: and responding to the analysis configuration operation of a user, and performing first analysis configuration on a first trend analysis graph corresponding to the target data set, wherein the first analysis configuration comprises that different fields are respectively selected as a first statistical classification and a first statistical unit of the first trend analysis graph.
And adding a first trend analysis graph in the first graph layer, and setting the first trend analysis graph according to the operation of a user. The first trend analysis graph is obtained by performing classification statistics on the content corresponding to a first statistical unit of all the data in the target data set based on a first statistical classification, where the first statistical classification and the first statistical unit are different fields in the target data set. In other embodiments, the first statistical classification and the first statistical unit may be other fields.
After a first trend analysis graph is generated by using a first statistical classification and a first statistical unit, if the first trend analysis graph is a bar graph, at this time, the abscissa name of the bar graph is the field name corresponding to the first statistical classification, and the ordinate name of the bar graph is the field name corresponding to the first statistical unit, a user can modify the abscissa name and the ordinate name of the bar graph according to requirements, wherein the modification mode comprises: and changing the names, the alignment modes, the display formats and the like of the horizontal and vertical coordinates. It is understood that if the first trend analysis graph is other graphs, corresponding modifications can be made.
The first statistical class can also be called dimension, and the first statistical class can be time, unit name, unit organization code, region and other fields; the first statistical unit may also be referred to as a measure, and the first statistical unit may be an amount, quantity, or the like field. If a trend analysis graph is configured, selecting time as a first statistical classification, wherein the classification standard of the first statistical classification can be year, month, day, hour and the like, and the data analysis can support two modes of discrete analysis and continuous analysis, wherein the discrete analysis can be performed in a segmented manner from twelve months a year, seven days a week and twenty-four hours a day, namely, partial data corresponding to a time field can be selected from a target data set for analysis, for example, the target data set comprises all data before 12 months and 30 days a 2020, and a user selects the discrete analysis and determines that the first statistical classification is a month under the time field, and then the data in the target data set can be counted monthly; and the continuous analysis is to analyze all data corresponding to the time field in the target data set.
Further, the trend analysis graph also supports two-dimensional analysis, for example, the time and the region can be selected at the same time as the first statistical classification, and the amount selected can be analyzed as the first statistical unit.
S140: and performing a second analysis configuration for the second trend analysis chart in response to the penetration configuration operation of the user, wherein the second analysis configuration comprises selecting different fields as a second statistical classification and a second statistical unit of the second trend analysis chart respectively.
The second trend analysis graph is obtained by skipping in response to the preset operation of the first trend analysis graph, and the content corresponding to the second statistical unit of the partial data in the target data set is subjected to classification statistics based on the second statistical classification.
Specifically, a second trend analysis graph may be established in the second graph layer, and different fields may be selected from the data set as a second statistical classification and a second statistical unit of the second trend analysis graph, where the fields of the second statistical classification need to be the same as the fields of the first statistical classification, and the classification criteria corresponding to the statistical classification may be different. For example, if the first statistical classification is time and the first classification criterion is yearly, then the second statistical classification is also time and the second classification criterion is monthly; if the first classification criterion of the first statistical classification is a superior organization name, the second classification criterion of the second statistical classification is a subordinate organization included in the superior organization.
The user can jump to the second trend analysis graph by clicking the first trend analysis graph, specifically, the user can jump by clicking a field serving as the first statistical classification in the first trend analysis graph, and can also click a graph corresponding to the field. For example, in one embodiment, the first trend analysis graph is a bar graph, as shown in FIG. 2, the first trend analysis graph represents sales of a company in 2017 and 2021, the second trend analysis graph represents sales of each month in 2020, and similarly, the second trend analysis graph is a bar graph, as shown in FIG. 3. Then click 2020 to jump to the second trend analysis graph, or click the corresponding column in 2020 in the first trend analysis graph to jump to the second trend analysis graph. Clicking the first trend analysis graph to jump to the second trend analysis graph can display the second trend analysis graph on the first interface instead of the first trend analysis graph, and can also directly jump to the second interface where the second trend analysis graph is located. It is understood that in other embodiments, the first trend analysis graph and the second trend analysis graph may be other graphs, and are not limited herein.
By the aid of the method, a multi-level penetrating trend analysis chart can be provided, so that a client can analyze data through simple operation, time and cost are saved, and accuracy is improved compared with manual analysis.
Referring to fig. 4-5, fig. 4 is a schematic flow chart diagram illustrating a configuration method of a trend analysis chart according to a second embodiment of the present disclosure; fig. 5 is a schematic diagram of another embodiment of a first trend analysis chart provided in the present application. The configuration method comprises the following steps:
s410: and receiving a trend analysis chart configuration instruction of a user.
S420: a target data set is determined.
Each piece of data in the target data set comprises content corresponding to a plurality of fields respectively.
S430: and responding to analysis configuration operation of a user, and performing first analysis configuration on a first trend analysis graph corresponding to the target data set, wherein the first analysis configuration further comprises a first classification standard for determining the first statistical classification and a first statistical manner corresponding to the first statistical unit.
The first trend analysis graph is obtained by dividing all data in a target data set into a plurality of first classes according to the first classification standard, and counting the first statistical units of the data of each first class according to a first statistical mode.
Specifically, the first classification criteria may be time-based statistical classification, organizational statistical classification, regional statistical classification, or the like, the time-based statistical classification may be statistics according to year, quarter, month, and day, the organizational statistical classification may be statistics according to superior and inferior organizational relationships, and the regional statistical classification may be statistics according to province, city, district, or province, city, county, and village.
The first statistical manner may be a counting manner, a repetition count manner, a summation manner, an averaging manner, a most value manner, and the like, and specifically, the first statistical manner is selected according to a field type of the first statistical unit, the field type may be divided into a text field and a numerical field, and if the field of the first statistical unit selected from the target data set is a text field, the statistical manner such as the counting manner and the repetition count manner may be performed. For example, the user needs to check the number of companies transacting with the company in the last month, the target data set stores related information such as the name of the company transacting with the company, transaction time and the like, and the user can select counting and de-duplication counting during statistics to obtain a statistical result.
If the field of the selected first statistical unit is a numerical field, statistical modes such as summation, averaging, and maximum value calculation can be performed, for example, the first statistical classification is a month in the time field, the first statistical unit is money, and the statistical mode can be the number of the month (summation), so that all sales of the month can be obtained; the statistical method can also be the number of the month (averaging), so that the average daily sales of the month can be obtained.
The data in the target data set are classified into a plurality of classes according to a first classification standard, a display interface displays sub-fields corresponding to the data in the class, and when a client selects a certain sub-field, all data corresponding to the sub-field in the target data set are automatically loaded. For example, when a customer selects this sub-field of the year, the system automatically loads the corresponding data in the target data set. After the first statistical classification and the first statistical unit are determined, the first statistical unit of each type of data can be counted according to a first statistical mode. As shown in FIG. 5, in one embodiment, the user selects the first statistical classification as time and the first classification criteria is a monthly classification, i.e., "time (month)" corresponding to the row display contained in the dimension of FIG. 5; the first statistical unit is the amount of money corresponding to the "number of months" shown in the metrics in fig. 5, and the first statistical manner is the sum corresponding to the "(sum)" shown in the metrics in fig. 5. After the selection is finished, the system automatically generates a trend analysis chart according to the selection of the user.
S440: and responding to the penetration configuration operation of the user, performing second analysis configuration on a second trend analysis chart, wherein the second analysis configuration further comprises second classification standards for determining the second statistical classification and a second statistical mode corresponding to the second statistical unit.
The second trend analysis graph divides the data in the first class into a plurality of second classes according to the second classification standard, and counts the second statistical unit of the data of each second class according to a second statistical mode.
When the second analysis configuration is performed, the first statistical classification and the second statistical classification correspond to the same field, the range of the first classification standard is larger than the range of the second classification standard, for example, the first statistical classification and the second statistical classification correspond to a time field, and if the first classification standard is a yearly classification, the second classification standard is a monthly classification; the first statistical classification and the second statistical classification correspond to an organization field, and if the first classification standard is a classification according to a superior organization, the second classification standard is a subordinate organization classification.
The second statistical method also includes counting, de-duplication counting, summing, averaging, or calculating the most value, and when the trend analysis graph is configured, the second statistical unit may be the same as the first statistical unit or different from the first statistical unit, and similarly, the second statistical method may be the same as or different from the first statistical method. In one embodiment, the first classification criterion is a classification by year, the first statistical unit is sales, the first statistical manner is summation, and the first trend analysis graph is used for counting sales per year. The second classification standard is classified according to months, the first statistical unit is sales, the first statistical mode is summation, and the second trend analysis graph is used for counting the sales of each month; in another embodiment, the first trend analysis graph is also used for counting sales per year, the second classification criterion is monthly classification, the first statistical unit is sales, and the first statistical manner is averaging, then the second trend analysis graph is used for counting average sales per day per month; in other embodiments, the first trend analysis graph is set to be constant, the second classification criterion is a monthly classification, the first statistical unit is the amount of products sold, the first statistical manner is a summation, and the second trend analysis graph is used for counting the number of products sold per month.
Referring to fig. 6, fig. 6 is a flowchart illustrating a third embodiment of a method for configuring a trend analysis chart according to the present application. The configuration method comprises the following steps:
s610: and receiving a trend analysis chart configuration instruction of a user.
S620: responding to the layout configuration operation of a user, displaying a plurality of layout modes, and acquiring the layout mode selected by the user from the plurality of layout modes as a target layout mode; and/or determining the processing authority of the first trend analysis chart and/or the second trend analysis chart in response to the authority configuration operation of the user.
The layout comprises a standard layout mode and a free layout mode, the standard layout mode is used for displaying a subsequently generated trend analysis chart according to a preset layout, the free layout mode is used for enabling a user to adjust the layout of the subsequently generated trend analysis chart, and the target layout mode is used as a layout mode corresponding to the first trend analysis chart and/or the second trend analysis chart; the processing rights include at least one of viewing rights and modification rights.
Specifically, after clicking a layout mode button, a user selects one layout mode as a target layout mode, and generates a trend analysis graph in the target layout mode. The layout modes comprise a free layout mode and a standard layout mode, the layout modes are suitable for different scenes, the standard layout mode is suitable for the condition that the boundary lines between charts are not obvious and the charts have related linkage, and the free layout mode has higher adjustment degree on the layout and is suitable for professional people to use. A plurality of layout modes are provided, and more choices can be provided for a user. The standard layout mode is preset, and in the standard layout mode, a user cannot randomly change the position of the generated trend analysis chart. For example, if the selected template is that only two trend analysis graphs can be displayed on one display interface, and the two trend analysis graphs account for 50% of the display interface, the two generated trend analysis graphs can be displayed only according to the layout which accounts for 50% of the display interface. In the free layout mode, the user can freely move the positions of the trend analysis graphs, so that the two trend analysis graphs can be overlapped or partially overlapped, and the data comparison result is more visual.
Furthermore, the user can set the authority for the trend analysis chart according to the requirement, and understandably, the authority setting can be performed after selecting the layout mode before generating the trend analysis chart; or after generating the trend analysis graph, which is not limited herein. After the authority is set, the generated trend analysis graph can be shared to other users according to the authority.
In one embodiment, after the user selects the layout mode, the user sets the authority of the trend analysis graph to be generated, and determines the processing authority item of the generated trend analysis graph, wherein the processing authority includes at least one of viewing authority and modifying authority. Specifically, data between different clients may be isolated, and all users under the same role of the same client have the same processing authority, for example, all members of a financial department of a certain provincial power grid group may be set to have the same authority. When the authority is set, the organization can be associated, and the intersection of the organization and the authority of the user group can be taken (when one application has the organization authority set in the role, whether the organization of the user has the authority is judged). For example, a certain trend analysis graph is set to have authority for all members of a financial department, and meanwhile, the trend analysis graph is set to have organization authority, only a certain urban power grid group can view the trend analysis graph, and the trend analysis graph and the organization authority need to take an intersection, that is, only employees of the financial department of a certain urban power grid have processing authority.
When setting the authority, the authority can be set through a Restful development mode, the development mode calls resources through interfaces of a service layer and a controller layer by adopting an http interface, and the authority is intercepted through a gateway; for those that do not require authority authentication, the configuration may be performed at a corresponding service layer or controller layer, or a built-in proxy user may log in through a built-in proxy user method (e.g., a mockfiginclient factory method). By setting the authority for the trend analysis chart, the safety of data can be guaranteed.
S630: a target data set is determined.
Each piece of data in the target data set comprises content corresponding to a plurality of fields respectively.
S640: and responding to the analysis configuration operation of a user, and performing first analysis configuration on a first trend analysis graph corresponding to the target data set, wherein the first analysis configuration comprises that different fields are respectively selected as a first statistical classification and a first statistical unit of the first trend analysis graph.
S650: and performing a second analysis configuration for the second trend analysis chart in response to the penetration configuration operation of the user, wherein the second analysis configuration comprises selecting different fields as a second statistical classification and a second statistical unit of the second trend analysis chart respectively.
Steps S630 to S650 can refer to steps S120 to S140 of the first embodiment, and are not described herein again.
Referring to fig. 5 and 7 in combination, fig. 7 is a schematic flow chart diagram illustrating a fourth embodiment of a method for configuring a trend analysis chart according to the present application. The configuration method further comprises the following steps:
s710: and receiving a trend analysis chart configuration instruction of a user.
S720: determining a target data set, wherein each piece of data in the target data set comprises contents corresponding to a plurality of fields respectively.
S730: setting a style parameter of the first trend analysis graph in response to a first style configuration operation by a user.
Wherein the style parameter includes at least one of: setting parameters of the background, the width, the height, the column spacing, the text attribute and the coordinate axis of the trend analysis chart, wherein the text attribute comprises the position, the size and the color of the text.
The user can set the background, the width and the height of the trend analysis chart according to the requirement, as shown in fig. 5, in an embodiment, the trend analysis chart is a column chart, basic styles such as a region background color, a chart width, a chart brightness, a text color, a font style and a font size of the column chart can be set on the right side of the display interface, a distance between columns, a color of the columns and a region of a rectangular coordinate system can be set, and color, position, size and the like can be set on an axis scale of a coordinate axis and a text label corresponding to the axis scale and a name of the coordinate axis. In practical application, in order to more visually display the numerical value represented by each column in the bar chart, text can be added above the column, and the added text is set in color, position, size and the like; a legend may be added above or to one side of the trend analysis chart to show the information expressed by each column, and the position of the legend and the text in the legend may also be set.
Further, when generating the trend analysis graph, the user may also perform settings such as multi-scale splitting, abbreviating axes, auxiliary lines, whether to cross natural periods, displaying the latest N pieces, and the like. For example, the trend analysis chart is a bar chart, in an embodiment, the user determines that the first statistical classification is a region and the first statistical unit is an amount, further, the user determines that the first classification standard of the first statistical unit is a year, the corresponding first statistical manner is a sum, that is, the year (sum), the second classification standard of the first statistical unit is a month, the corresponding first statistical manner is a sum, that is, the month (sum), the abscissa of the generated bar chart is each region, and the ordinate is the amount. If the multi-scale splitting is not selected, each region is represented by a column in the generated bar graph, each column comprises two parts, one part represents the numerical value of the current year (sum) of a region, the other part represents the numerical value of the current month (sum) of a region, and the two parts are distinguished by different colors; if multi-metric splitting is chosen, each region is represented by two bars, one bar representing the value of the year (sum) of a region and the other bar representing the value of the month (sum) of a region.
In another embodiment, when the first statistical classification and the first statistical unit contain more data, all the data cannot be completely displayed due to the small display area, and at this time, the thumbnail axis may be set for sliding viewing. In order to determine whether the statistical data is expected or not, the user may set an auxiliary line in the trend analysis chart, and the user may consider that the auxiliary line is expected.
In another embodiment, the target data set includes data of months 1 to 8 months 2010 to 2011, the user wants to count the data of months 8 to 8 months 2010 to 2011, the user can set to view the data across a natural period, and if the data across the natural period is not set, the user can only view the data of year 2011, wherein the period may be one year, one quarter or one month.
In other embodiments, the user may also select the data in the target data set for analysis, for example, if the user sets to display the last 10 items, the system automatically selects the ten items of data in the target data set closest to the current date for statistical analysis.
S740: and responding to the analysis configuration operation of a user, and performing first analysis configuration on a first trend analysis graph corresponding to the target data set, wherein the first analysis configuration comprises that different fields are respectively selected as a first statistical classification and a first statistical unit of the first trend analysis graph.
S750: and performing a second analysis configuration for the second trend analysis chart in response to the penetration configuration operation of the user, wherein the second analysis configuration comprises selecting different fields as a second statistical classification and a second statistical unit of the second trend analysis chart respectively.
For detailed descriptions of steps S740 and S750, refer to steps S130 and S140 of the first embodiment, which are not described herein again.
S760: setting a style parameter of the second trend analysis graph in response to a second style configuration operation of a user.
The second trend analysis graph may also be subjected to the style setting as described in step S430, and it is understood that the style of the second trend analysis graph may be the same as or different from that of the first trend analysis graph, for example, in an embodiment, the first trend analysis graph and the second trend analysis graph are both bar graphs; in one embodiment, the first trend analysis graph is a bar graph and the second trend analysis graph is a pie graph.
The trend analysis graph may be set in a style after the trend analysis graph is generated, or may be set before the trend analysis graph is generated, which is not limited herein.
The application provides trend analysis chart of multiple style, and the user can set up according to the demand, easy operation, and the ease for use is high, and the flexibility ratio is high.
Referring to fig. 8, fig. 8 is a flowchart illustrating an embodiment of step S120 in the first embodiment of the method for configuring a trend analysis chart according to the present application, and the determining a target data set includes:
s810: and responding to the data configuration operation of the user, and acquiring the data selected by the user from the original data set and/or the data imported by the user to obtain the target data set.
The data in the target data set may be data imported from the original data set, or data imported directly into the target data set by the user, wherein the data of the original data set is stored in the database.
When data in the target data set is imported from the original data set, a single condition can be input according to actual requirements for searching, for example, a time period is input, and the data in the time period is searched; a plurality of conditions can be input for searching, for example, a time period and a region are input, and data of a certain region in the time period can be searched, so that the time of a user is saved.
S820: and responding to the modification operation of the user on the target data set, and correspondingly updating the target data set.
Wherein the modifying operation comprises at least one of: modifications to data, adding data, deleting data, replacing data, and adding or deleting fields to data. If partial data already exists in the target data set, the user finds that the data is still lacking or the existing data is wrong, the user can newly add the data or modify the wrong data, and similarly, the user can add or delete a field corresponding to the data.
After the data of the target data set is modified, if the first trend analysis graph or the second trend analysis graph is displayed currently, the first trend analysis graph and the second trend analysis graph are updated according to the updated target data set, and the updated first trend analysis graph or the updated second trend analysis graph is displayed.
Specifically, if the first trend analysis graph or the second trend analysis graph has been generated based on the data of the original target data set, after the data of the target data set is modified, the trend analysis graph associated with the modified data is displayed, and at this time, the data of the trend analysis graph is updated based on the data of the target data set, and the updated first trend analysis graph or the updated second trend analysis graph is displayed.
Referring to fig. 9, fig. 9 is a flowchart illustrating a fifth embodiment of a method for configuring a trend analysis chart according to the present application. The configuration method comprises the following steps:
s910: and receiving a trend analysis chart configuration instruction of a user.
S920: in response to the trend analysis graph configuration instructions, metadata is initialized.
The metadata is used for recording configuration parameters of the trend analysis chart configured at this time. The configuration parameters include basic data such as layout mode, loading data set data, style font, color, size, style, and thickness.
S930: a target data set is determined.
The data of the target data set can be the original data set and/or the user import, and can also be obtained by modifying the imported data.
S940: and responding to the analysis configuration operation of a user, and performing first analysis configuration on a first trend analysis graph corresponding to the target data set, wherein the first analysis configuration comprises that different fields are respectively selected as a first statistical classification and a first statistical unit of the first trend analysis graph.
S950: and performing a second analysis configuration for the second trend analysis chart in response to the penetration configuration operation of the user, wherein the second analysis configuration comprises selecting different fields as a second statistical classification and a second statistical unit of the second trend analysis chart respectively.
For detailed descriptions of steps S940 and S950, refer to steps S130 and S140 of the first embodiment, which are not described herein again.
S960: and setting and saving the metadata based on the configuration of the first trend analysis chart and the second trend analysis chart by the user.
When the trend analysis graph is configured, all the operations are online and timely dynamically rendering the trend analysis graph, one of client rendering, server rendering and isomorphic rendering can be adopted as a dynamic rendering mode, and after the configuration of the first trend analysis graph and the second trend analysis graph is completed, the configuration parameters selected by all the operations are stored in a metadata base of the trend analysis graph, so that the next time of direct calling is facilitated.
Referring to fig. 10, fig. 10 is a schematic diagram of a frame structure of an electronic device provided in the present application.
The electronic device 100 comprises a memory 101 and a processor 102 coupled to each other, the memory 101 storing program instructions, and the processor 102 being configured to execute the program instructions stored in the memory 101 to implement the steps of any of the above-described method embodiments. In one particular implementation scenario, electronic device 100 may include, but is not limited to: a microcomputer, a server, and the electronic device 100 may further include a mobile device such as a notebook computer, a tablet computer, and the like, which is not limited herein.
Specifically, the processor 102 is configured to control itself and the memory 101 to implement the steps of any one of the above-mentioned display method embodiments of the target variable and the impact factor. Processor 102 may also be referred to as a CPU (Central Processing Unit). The processor 102 may be an integrated circuit chip having signal processing capabilities. The Processor 102 may also be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. Additionally, the processor 102 may be commonly implemented by integrated circuit chips.
Referring to fig. 11, fig. 11 is a block diagram illustrating a computer storage medium according to an embodiment of the present invention.
The computer readable storage medium 110 stores program instructions 111, and the program instructions 111, when executed by the processor, are configured to implement the steps of any of the above-described method embodiments.
The computer-readable storage medium 110 may be a medium that can store a computer program, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or may be a server that stores the computer program, and the server can send the stored computer program to another device for running or can run the stored computer program by itself.
The above description is only for the purpose of illustrating embodiments of the present application and is not intended to limit the scope of the present application, and all modifications of equivalent structures and equivalent processes, which are made by the contents of the specification and the drawings of the present application or are directly or indirectly applied to other related technical fields, are also included in the scope of the present application.
Claims (10)
1. A method for configuring a trend analysis graph, the method comprising:
receiving a trend analysis chart configuration instruction of a user;
determining a target data set, wherein each piece of data in the target data set comprises contents corresponding to a plurality of fields respectively;
responding to an analysis configuration operation of a user, performing first analysis configuration on a first trend analysis chart corresponding to the target data set, wherein the first analysis configuration comprises that different fields are respectively selected as a first statistical classification and a first statistical unit of the first trend analysis chart, and the first trend analysis chart is used for performing classification statistics on contents corresponding to the first statistical unit of all data in the target data set based on the first statistical classification;
and responding to a penetration configuration operation of a user, performing second analysis configuration on a second trend analysis graph, wherein the second analysis configuration comprises a second statistical classification and a second statistical unit which respectively select different fields as the second trend analysis graph, the second trend analysis graph is obtained by skipping in response to a preset operation of the first trend analysis graph, and the content corresponding to the second statistical unit of the partial data in the target data set is subjected to classification statistics based on the second statistical classification.
2. The method of claim 1, wherein the first analysis configuration further comprises determining a first classification criterion of the first statistical classification and a first statistical approach corresponding to the first statistical unit; the first trend analysis graph divides all data in a target data set into a plurality of first types according to the first classification standard, and counts the first statistical units of the data of each first type according to a first statistical mode;
the second analysis configuration further comprises a second classification criterion for determining the second statistical classification and a second statistical manner corresponding to the second statistical unit; the second trend analysis graph divides the data in the first class into a plurality of second classes according to the second classification standard, and counts the second statistical unit of the data of each second class according to a second statistical mode.
3. The method of claim 2, wherein the first statistical classification and the second statistical classification correspond to the same field, and wherein the range of the first classification criterion is greater than the range of the second classification criterion;
and/or if the first statistical unit or the second statistical unit is a text field, the corresponding first statistical mode or the second statistical mode comprises counting or duplicate removal; if the first statistical unit or the second statistical unit is a value field, the corresponding first statistical mode or the second statistical mode includes summing, averaging, taking a maximum value or taking a minimum value.
4. The method of claim 1, wherein after receiving a trend analysis graph configuration instruction from a user, the method further comprises:
responding to the layout configuration operation of a user, displaying a plurality of layout modes, and acquiring the layout mode selected by the user from the plurality of layout modes as a target layout mode; the layout mode comprises a standard layout mode and a free layout mode, the standard layout mode is used for displaying a subsequently generated trend analysis chart according to a preset layout, the free layout mode is used for enabling a user to adjust the layout of the subsequently generated trend analysis chart, and the target layout mode is used as a layout mode corresponding to the first trend analysis chart and/or the second trend analysis chart; and/or the presence of a gas in the gas,
and determining the processing authority of the first trend analysis chart and/or the second trend analysis chart in response to the authority configuration operation of the user, wherein the processing authority comprises at least one of viewing authority and modifying authority.
5. The method of claim 1, wherein after the determining a target data set, the method further comprises:
setting a style parameter of the first trend analysis graph in response to a first style configuration operation of a user;
after the performing a second analysis configuration for a second trend analysis graph in response to a penetration configuration operation by a user, the method further comprises:
setting a style parameter of the second trend analysis graph in response to a second style configuration operation of a user.
6. The method of claim 5, wherein the style parameter comprises at least one of: setting parameters of the background, the width, the height, the column spacing, the text attribute and the coordinate axis of the trend analysis chart, wherein the text attribute comprises the position, the size and the color of the text.
7. The method of claim 1, wherein the determining a target data set comprises:
responding to data configuration operation of a user, and acquiring data selected by the user from an original data set and/or data imported by the user to obtain the target data set;
the method further comprises the following steps:
in response to a modification operation of the target data set by a user, correspondingly updating the target data set, wherein the modification operation comprises at least one of the following operations: modifying data, adding data, deleting data, replacing data and adding or deleting fields for the data;
if the first trend analysis graph or the second trend analysis graph is displayed currently, updating the first trend analysis graph and the second trend analysis graph according to the updated target data set, and displaying the updated first trend analysis graph or the updated second trend analysis graph.
8. The method of claim 1, wherein after receiving a trend analysis graph configuration instruction from a user, the method further comprises:
responding to the trend analysis chart configuration instruction, initializing metadata, wherein the metadata is used for recording configuration parameters of the configured trend analysis chart;
after the configuration of the first trend analysis chart and the second trend analysis chart is completed, the metadata is set and saved based on the configuration of the first trend analysis chart and the second trend analysis chart by the user.
9. An electronic device comprising a memory and a processor coupled to each other,
the memory stores program instructions;
the processor is configured to execute program instructions stored in the memory to implement the method of any of claims 1-8.
10. A computer-readable storage medium for storing program instructions executable to implement the method of any one of claims 1-8.
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| CN114398140A (en) * | 2022-03-25 | 2022-04-26 | 深圳市鼎阳科技股份有限公司 | Dynamic generation method of trend graph, electronic measurement device and storage medium |
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| CN114398140A (en) * | 2022-03-25 | 2022-04-26 | 深圳市鼎阳科技股份有限公司 | Dynamic generation method of trend graph, electronic measurement device and storage medium |
| CN114398140B (en) * | 2022-03-25 | 2022-05-31 | 深圳市鼎阳科技股份有限公司 | Dynamic generation method of trend graph, electronic measurement device and storage medium |
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