CN115658778B - Excel data source-based data processing method for visual application creation - Google Patents
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Abstract
The invention relates to the technical field of low-code platforms, in particular to a data processing method based on an Excel data source for visual application creation, which comprises the following steps: s1, prompting data items required by a graphic component according to the visual graphic component selected by a user; s2, acquiring an Excel table uploaded by a user, checking whether a hidden line or a hidden column exists, if so, judging whether the hidden line is an effective data line or not and whether the hidden column is an effective data column or not, and marking the effective data line and the effective data column; s3, reading the non-hidden rows, the non-hidden columns, the marked effective data rows and the marked effective data columns into a data model corresponding to the graphic assembly, and detecting whether merging cells exist or not; if the data exists, splitting the combined cells, and filling corresponding data into each split cell according to preset requirements. The method can enable users in the AI industry field to use the Excel table for data management, and reduce the workload when the data source is accessed.
Description
Technical Field
The invention relates to the technical field of low-code platforms, in particular to a data processing method based on an Excel data source for visual application creation.
Background
Low Code (Low Code) is a visual application development method, which uses less Code to deliver an application program at a faster speed, and the Code which a programmer does not want to develop is automated, which is called Low Code. The low code is a group of digital technology tool platforms, and based on more efficient modes such as graphic dragging, parameterized configuration and the like, quick construction, data arrangement, ecological connection and middle service are realized. Scene application innovation in digital transformation is achieved with little or no code.
In the case where the data visualization application is a low code development platform, various ways of data source access are typically provided, including databases, APIs, excel, and the like. For the AI industry, in the absence of an informationized management system for an enterprise, excel tables are now commonly used for data management. In the process of creating the enterprise data visualization application, when an Excel table is used for data management, an Excel data source needs to be filled according to a table header required by a system, and the Excel table is uploaded to the system for data analysis and conversion.
However, compared with the conventional data source, in the process of manufacturing an Excel table, workers can perform operations such as row hiding, column hiding, parallel combining and the like for the sake of manufacturing and operation borderline. When the existing low-code platform only performs filling work of data during data input, if hidden rows/hidden columns exist, the platform does not know which should be input and which cannot be input; if there are parallel and parallel columns, specific contents of each unit need to be specifically entered due to the fact that the data sources are entered. This results in that, during the data processing, if there are hidden rows, hidden columns, parallel and the like in the Excel table, the user needs to delete the redundant data separately and split the merged cells. If the amount of data to be uploaded is large (there are thousands of data amounts), the process of manually optimizing the format data by the user is very time consuming, labor consuming, and error prone.
Therefore, how to reduce the workload when accessing data sources for users who use Excel tables in the AI industry field is a problem to be solved in the industry at present.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a data processing method based on an Excel data source for visual application creation, which can enable users in the AI industrial field to use an Excel table for data management and reduce the workload when the data source is accessed.
In order to solve the technical problems, the invention adopts the following technical scheme:
the Excel data source-based data processing method for visual application creation comprises the following steps:
s1, prompting data items required by a graphic component according to the visual graphic component selected by a user;
s2, acquiring an Excel table uploaded by a user, checking whether a hidden line or a hidden column exists, if so, judging whether the hidden line is an effective data line or not and whether the hidden column is an effective data column or not, and marking the effective data line and the effective data column;
s3, reading the non-hidden rows, the non-hidden columns, the marked effective data rows and the marked effective data columns into a data model corresponding to the graphic assembly, and detecting whether merging cells exist or not; if the data exists, splitting the combined cells, and filling corresponding data into each split cell according to preset requirements;
and S4, after the merging unit check is completed, storing the data into a server library, and binding the data with the corresponding visualized image component.
Based on the scheme principle and beneficial effects:
by using the method, before data management is carried out, after a user selects a corresponding visual graphic component, the platform prompts data items required by the graphic component, so that the user can conveniently adjust an original Excel table, for example, unnecessary data items are deleted or hidden, and subsequent operation is facilitated; or the missing data item is supplemented, so that the integrity of the data is ensured.
After uploading the Excel table, the user can check whether a hidden line or a hidden column exists, if so, whether the hidden line is a valid data line or not and whether the hidden column is a valid data column or not are judged, and the valid data line and the valid data column are marked. By the method, the effective data rows/data columns can be identified completely, and the effective data in the Excel table can be completely recorded in the server. Then, detecting whether a merging cell exists; if the data exists, splitting the combined cells, and filling corresponding data into each split cell according to preset requirements. Through the processing, all effective cells in the Excel table can be ensured to have corresponding data contents, and the stability of subsequent operation is ensured. The data is then stored in a server library and bound with the corresponding visualized image component.
In this way, the user who uses an Excel table for data management in the AI industry can use the Excel table for data management only by performing appropriate operations according to the prompt. Compared with the prior art, the workload of accessing the data source can be greatly reduced.
In conclusion, the method can enable users in the AI industrial field to use the Excel table for data management, and reduce the workload when the data source is accessed.
Preferably, in S2, when checking whether there is a hidden column, the column sequence number of the Excel table is obtained first, then it is determined whether there is a discontinuity in the column sequence numbers, if there is a discontinuity, it is determined that there is a hidden column between the discontinuity sequence numbers, the data columns corresponding to each column sequence number between the discontinuity sequence numbers are extracted, and whether the data codes corresponding to the header of each data column belong to the data items required by the corresponding graphic assembly is checked, if so, the data columns are marked as valid data columns.
The beneficial effects are that: when there are a large number of data columns that are not needed, a user may hide the data columns needed by the graphic assembly when performing a hiding operation. In this way, when the above situation occurs, the hidden valid data columns can be accurately identified and marked, so that the integrity of the data is ensured.
Preferably, in S2, checking whether a hidden line exists, firstly acquiring a line sequence number of an Excel table, and then judging whether a discontinuous condition exists in the line sequence number, if so, judging that a hidden column exists between the discontinuous sequence numbers; extracting the data corresponding to each line number between the discontinuous line numbers, returning to display, and prompting a user to confirm whether each data line is valid or not; and if the valid signal is received, marking the corresponding data line as a valid data line.
The beneficial effects are that: by the method, the hidden effective data line can be accurately identified and marked, so that the data integrity is ensured.
Preferably, in S3, the merging cells include a longitudinal merging cell and a transverse merging cell, and it is detected whether the longitudinal merging cell exists first, and then whether the transverse merging cell exists.
The beneficial effects are that: because the situation of a plurality of rows and columns of data merging cells exists, when whether a longitudinal merging cell exists or not is detected, the situation can be conveniently identified and processed, and whether a transverse merging cell exists or not is detected subsequently, and only the detection of each data row is needed.
Preferably, in S3, when checking the longitudinal merging cells, if there are longitudinal merging cells, acquiring a start position row and an end position row of the longitudinal merging cells, and acquiring data of the longitudinal merging cells and a column sequence number of a data column where the longitudinal merging cells are located;
if the number of the column numbers is greater than 1, judging that the combination of a plurality of rows and a plurality of columns is performed; respectively calculating similarity values of data of the longitudinal merging cells and data of data columns corresponding to serial numbers of all columns, splitting the longitudinal merging cells into a plurality of cells before merging, and marking the cells as cells to be processed; sequentially filling the data of the longitudinal merging cells into each cell to be processed in a data column with the highest similarity value, and marking the rest cells to be processed as empty;
if the number of the column numbers is equal to 1, splitting the longitudinal merging cells into a plurality of cells before merging, and sequentially filling the data of the longitudinal merging cells into the plurality of cells before merging.
The beneficial effects are that: in this way, it is possible to accurately identify the combination of a plurality of rows and a plurality of columns and the case where only the combination of a plurality of columns is involved, and to perform the corresponding data filling processing, respectively. When a vertical merging cell occurs, the data in each merged cell is generally consistent, the data entry personnel operate for convenient viewing, but a plurality of rows and columns occur, and the similarity value of the data of the vertical merging cell and the data of the data column corresponding to each column serial number is different, the situation that an error may occur is illustrated, because the same data cannot be matched with two data types at the same time. Therefore, the invention can identify and fill the data into the data column which should be filled, and the data column and the abnormal cell are marked as empty, so that the personnel can check and process the data conveniently.
Preferably, in S3, when the lateral merging cells are checked, if the lateral merging cells exist, the column number of the data column where the lateral merging cells are located and the data of the lateral merging cells are obtained;
respectively calculating similarity values of data of the transverse merging cells and data of data columns corresponding to serial numbers of all columns, splitting the transverse merging cells into a plurality of cells before merging, and marking the cells as cells to be processed; and filling the data of the transverse merging cells into the cells to be processed in the data column with the highest similarity value, and carrying out association filling on the rest cells to be processed and other data lines according to preset association requirements.
The beneficial effects are that: in this way, the present invention can accurately identify when a lateral merge cell occurs and fill the data into the data column that it should fill. Unlike multiple rows and columns, the occurrence of a lateral merge cell may be that a hand mistake has merged adjacent lateral cells that do not need to be merged. If this is the case, the remaining units to be processed should have their own data. By using the method, the association filling can be carried out with other data, so that the integrity of the data is ensured as much as possible.
Preferably, in S3, the association requirement is that after the to-be-processed cell filled with the data of the horizontal merging cell is recorded as a comparison cell, the data of the comparison cell is compared with the data of other cells in the data column where the comparison cell is located, if the same data exists, the data row where the same data exists is used as a reference data row, and each data in the reference data row and each remaining to-be-processed cell located in the same data column is sequentially filled into each remaining to-be-processed cell.
The beneficial effects are that: in data management, the association relationship between each column of data is usually fixed, for example, model number and price. By means of the method, the association relation can be well utilized, and data of the remaining cells to be processed are filled, so that the integrity of the data is guaranteed as much as possible.
Preferably, in S3, when checking the vertical merging cells, if the data format of the vertical merging cells is a special format, returning to the vertical merging cells, and prompting manual processing; when the transverse merging cells are checked, if the data format of the transverse merging cells is a special format, returning the transverse merging cells, and prompting manual processing; the special formats include integers, floating point numbers, and computational formulas.
The beneficial effects are that: by the arrangement, the validity of the input data can be ensured.
Preferably, in S3, the similarity value is calculated by comparing the data type with the data item.
The beneficial effects are that: the reliability of the result of the similar reading calculation can be ensured.
Drawings
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the present invention will be described in further detail with reference to the accompanying drawings, in which:
FIG. 1 is a flow chart of a method of data processing based on Excel data sources for visualization application creation of the present invention;
fig. 2 is a schematic diagram of an example of S3 in the embodiment.
Detailed Description
The following is a further detailed description of the embodiments:
examples:
as shown in fig. 1, the embodiment discloses a data processing method based on Excel data sources for visual application creation, which comprises the following steps:
s1, prompting data items required by the graphic assembly according to the visual graphic assembly selected by a user. In other embodiments, an Excel table template may be provided to allow the user to enter data by way of data replication, but such an operation is also relatively cumbersome to operate when the amount of data is large.
S2, acquiring an Excel table uploaded by a user, checking whether a hidden line or a hidden column exists, if so, judging whether the hidden line is an effective data line or not and whether the hidden column is an effective data column or not, and marking the effective data line and the effective data column.
When the hidden columns are detected, firstly acquiring the column serial numbers of the Excel table, judging whether the column serial numbers are discontinuous, if yes, judging that the hidden columns exist between the discontinuous serial numbers, extracting the data columns corresponding to the column serial numbers between the discontinuous column serial numbers, respectively checking whether the data codes corresponding to the table heads of the data columns belong to the data items needed by the corresponding graphic assemblies, and if yes, marking the data columns as valid data columns. Checking whether hidden lines exist, firstly acquiring row sequence numbers of an Excel table, then judging whether discontinuous conditions exist in the row sequence numbers, and if so, judging that hidden columns exist between the discontinuous sequence numbers; extracting the data corresponding to each line number between the discontinuous line numbers, returning to display, and prompting a user to confirm whether each data line is valid or not; and if the valid signal is received, marking the corresponding data line as a valid data line.
When there are a large number of data columns that are not needed, a user may hide the data columns needed by the graphic assembly when performing a hiding operation. In this way, when the above situation occurs, the hidden valid data columns can be accurately identified and marked, so that the integrity of the data is ensured. In the same way, the hidden effective data line can be accurately identified and marked, so that the data integrity is ensured.
S3, reading the non-hidden rows, the non-hidden columns, the marked effective data rows and the marked effective data columns into a data model corresponding to the graphic assembly, and detecting whether merging cells exist or not; if the data exists, splitting the combined cells, and filling corresponding data into each split cell according to preset requirements.
The merging unit comprises a longitudinal merging unit and a transverse merging unit, and detects whether the longitudinal merging unit exists or not and then detects whether the transverse merging unit exists or not. Because the situation of a plurality of rows and columns of data merging cells exists, when whether a longitudinal merging cell exists or not is detected, the situation can be conveniently identified and processed, and whether a transverse merging cell exists or not is detected subsequently, and only the detection of each data row is needed.
When the method is implemented, when the longitudinal merging cells are checked, if the longitudinal merging cells exist, acquiring a starting position row and an ending position row of the longitudinal merging cells, and acquiring data of the longitudinal merging cells and a column sequence number of a data column where the longitudinal merging cells are located; if the number of the column numbers is greater than 1, judging that the combination of a plurality of rows and a plurality of columns is performed; respectively calculating similarity values of data of the longitudinal merging cells and data of data columns corresponding to serial numbers of all columns, splitting the longitudinal merging cells into a plurality of cells before merging, and marking the cells as cells to be processed; sequentially filling the data of the longitudinal merging cells into each cell to be processed in a data column with the highest similarity value, and marking the rest cells to be processed as empty; if the number of the column numbers is equal to 1, splitting the longitudinal merging cells into a plurality of cells before merging, and sequentially filling the data of the longitudinal merging cells into the plurality of cells before merging. In this way, it is possible to accurately identify the combination of a plurality of rows and a plurality of columns and the case where only the combination of a plurality of columns is involved, and to perform the corresponding data filling processing, respectively. When a vertical merging cell occurs, the data in each merged cell is generally consistent, the data entry personnel operate for convenient viewing, but a plurality of rows and columns occur, and the similarity value of the data of the vertical merging cell and the data of the data column corresponding to each column serial number is different, the situation that an error may occur is illustrated, because the same data cannot be matched with two data types at the same time. Therefore, the invention can identify and fill the data into the data column which should be filled, and the data column and the abnormal cell are marked as empty, so that the personnel can check and process the data conveniently.
When the transverse merging cells are checked, if the transverse merging cells exist, acquiring the column serial numbers of the data columns where the transverse merging cells are positioned and the data of the transverse merging cells; respectively calculating similarity values of data of the transverse merging cells and data of data columns corresponding to serial numbers of all columns, splitting the transverse merging cells into a plurality of cells before merging, and marking the cells as cells to be processed; and filling the data of the transverse merging cells into the cells to be processed in the data column with the highest similarity value, and carrying out association filling on the rest cells to be processed and other data lines according to preset association requirements. Thus, when a lateral merge cell occurs, the present invention can accurately identify and fill the data into the data column that it should fill. Unlike multiple rows and columns, the occurrence of a lateral merge cell may be that a hand mistake has merged adjacent lateral cells that do not need to be merged. If this is the case, the remaining units to be processed should have their own data. By using the method, the association filling can be carried out with other data, so that the integrity of the data is ensured as much as possible.
The association requirement is that after the to-be-processed cell filled with the data of the transverse merging cell is marked as a comparison cell, the data of the comparison cell is compared with the data of other cells in the data column where the comparison cell is located, if the same data exists, the data row where the same data is located is used as a reference data row, and each data in the reference data row and each remaining to-be-processed cell are located in the same data column, and each remaining to-be-processed cell is sequentially filled. In data management, the association relationship between each column of data is usually fixed, for example, model number and price. By means of the method, the association relation can be well utilized, and data of the remaining cells to be processed are filled, so that the integrity of the data is guaranteed as much as possible.
In S3, when checking the vertical merging cells, if the data format of the vertical merging cells is a special format, returning to the vertical merging cells, and prompting manual processing; when the transverse merging cells are checked, if the data format of the transverse merging cells is a special format, returning the transverse merging cells, and prompting manual processing; the special formats include integers, floating point numbers, and computational formulas. In this way, the validity of the entered data can be ensured. And the similarity value is calculated in a comparison mode according to the data type and the data item.
For ease of understanding, S3 will be described as an example. The system feeds back an order data model, wherein the data items to be filled comprise an order number, a delivery date, a part code, a part name, a quantity and a unit; after the user uploads the corresponding Excel table, the non-hidden rows, the non-hidden columns, the marked valid data rows and the marked valid data columns are shown in fig. 2.
When the detection of the merging cells is performed, the detection of the longitudinal merging cells is performed first. Checking whether longitudinal merging cells exist or not through longitudinal data, acquiring a start position line, a start position line and an end position line finish of the longitudinal merging cells, and checking the position of transverse data based on the longitudinal positions of the acquired longitudinal merging cells;
in column a, there are longitudinal merging cells, and a start position line, start=3, and an end position line, finish=7 of the longitudinal merging cells are obtained; performing lateral data position verification based on the acquired longitudinal merging cell longitudinal position, and if count (col) =1, then m-data: "D1566454" is stuffed into data [3] [ A ] -data [7] [ A ];
in the column B, there are longitudinal merging cells, and a start position line, start=3, and an end position line, finish=7 of the longitudinal merging cells are obtained; performing lateral data position verification based on the acquired longitudinal merging cell longitudinal position, and if count (col) =1, then m-data: "6.5" is stuffed into data [3]B ] -data [7] [ B ];
in the C column, no longitudinal merging unit cell exists, and data does not need to be processed;
in the E column, no longitudinal merging unit cell exists, and data does not need to be processed;
in the F column, there is a longitudinal merging cell, and a start position line, start=2, and an end position line, finish=8 of the longitudinal merging cell are obtained; performing lateral data position verification based on the acquired longitudinal merging cell longitudinal position, and if count (col) =1, then m-data: the sleeve is filled into the data [1] [ F ] -data [8] [ F ];
then, the detection of the lateral merging unit cell is performed. In this example, only the 4 th data row has a lateral merge cell. Acquiring a start position row col. Start=c and an end position row col. Finish=d of the transverse merging cells, and performing longitudinal data position verification based on the acquired transverse positions of the transverse merging cells; merging the lateral cell data m-data: the fitting A is subjected to data type and data item similarity comparison with the data of the row, a data comparison similarity value simi of each row is obtained, similarity D column data is larger than C columns, data m-data in a transverse merging cell is filled into data [4] [ D ] in the current row, multi-row association verification is carried out according to the row data aiming at the C column data, and when the condition of data [2] [ D ] = data [4] [ D ] is in, the filling data [4] [ C ] is data [2] [ C ]. Value ().
And S4, after the merging unit check is completed, storing the data into a server library, and binding the data with the corresponding visualized image component.
By using the method, before data management is carried out, after a user selects a corresponding visual graphic component, the platform prompts data items required by the graphic component, so that the user can conveniently adjust an original Excel table, for example, unnecessary data items are deleted or hidden, and subsequent operation is facilitated; or the missing data item is supplemented, so that the integrity of the data is ensured.
After uploading the Excel table, the user can check whether a hidden line or a hidden column exists, if so, whether the hidden line is a valid data line or not and whether the hidden column is a valid data column or not are judged, and the valid data line and the valid data column are marked. By the method, the effective data rows/data columns can be identified completely, and the effective data in the Excel table can be completely recorded in the server. Then, detecting whether a merging cell exists; if the data exists, splitting the combined cells, and filling corresponding data into each split cell according to preset requirements. Through the processing, all effective cells in the Excel table can be ensured to have corresponding data contents, and the stability of subsequent operation is ensured. The data is then stored in a server library and bound with the corresponding visualized image component.
In this way, the user who uses an Excel table for data management in the AI industry can use the Excel table for data management only by performing appropriate operations according to the prompt. Compared with the prior art, the workload of accessing the data source can be greatly reduced.
Finally, it should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the technical solution, and those skilled in the art should understand that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the present invention, and all such modifications and equivalents are included in the scope of the claims.
Claims (5)
1. The Excel data source-based data processing method for visual application creation is characterized by comprising the following steps:
s1, prompting data items required by a graphic component according to the visual graphic component selected by a user;
s2, acquiring an Excel table uploaded by a user, checking whether a hidden line or a hidden column exists, if so, judging whether the hidden line is an effective data line or not and whether the hidden column is an effective data column or not, and marking the effective data line and the effective data column;
s3, reading the non-hidden rows, the non-hidden columns, the marked effective data rows and the marked effective data columns into a data model corresponding to the graphic assembly, and detecting whether merging cells exist or not; if the data exists, splitting the combined cells, and filling corresponding data into each split cell according to preset requirements;
s4, after the detection of the merging unit grids is completed, storing the data into a server library, and binding the data with the corresponding visualized image components;
in S2, when checking whether there is a hidden column, firstly acquiring a column sequence number of an Excel table, then judging whether there is a discontinuous condition of the column sequence numbers, if yes, judging that there is a hidden column between the discontinuous sequence numbers, extracting a data column corresponding to each column sequence number between the discontinuous column sequence numbers, and respectively checking whether a data code corresponding to a table head of each data column belongs to a data item required by a corresponding graphic assembly, if yes, marking the data column as a valid data column;
s2, checking whether a hidden line exists, firstly acquiring a line sequence number of an Excel table, then judging whether the line sequence number is discontinuous, and if so, judging that a hidden column exists between the discontinuous sequence numbers; extracting the data corresponding to each line number between the discontinuous line numbers, returning to display, and prompting a user to confirm whether each data line is valid or not; if the valid signal is received, marking the corresponding data line as a valid data line;
s3, the merging unit cells comprise longitudinal merging unit cells and transverse merging unit cells, and whether the longitudinal merging unit cells exist or not is detected firstly, and then whether the transverse merging unit cells exist or not is detected; s3, when the longitudinal merging cells are checked, if the longitudinal merging cells exist, acquiring a starting position row and an ending position row of the longitudinal merging cells, and acquiring data of the longitudinal merging cells and a column sequence number of a data column where the longitudinal merging cells are located;
if the number of the column numbers is greater than 1, judging that the combination of a plurality of rows and a plurality of columns is performed; respectively calculating similarity values of data of the longitudinal merging cells and data of data columns corresponding to serial numbers of all columns, splitting the longitudinal merging cells into a plurality of cells before merging, and marking the cells as cells to be processed; sequentially filling the data of the longitudinal merging cells into each cell to be processed in a data column with the highest similarity value, and marking the rest cells to be processed as empty;
if the number of the column numbers is equal to 1, splitting the longitudinal merging cells into a plurality of cells before merging, and sequentially filling the data of the longitudinal merging cells into the plurality of cells before merging.
2. The Excel data source-based data processing method for visualization application creation of claim 1, wherein: s3, when the transverse merging cells are checked, if the transverse merging cells exist, acquiring the column serial numbers of the data columns where the transverse merging cells are located and the data of the transverse merging cells;
respectively calculating similarity values of data of the transverse merging cells and data of data columns corresponding to serial numbers of all columns, splitting the transverse merging cells into a plurality of cells before merging, and marking the cells as cells to be processed; and filling the data of the transverse merging cells into the cells to be processed in the data column with the highest similarity value, and carrying out association filling on the rest cells to be processed and other data lines according to preset association requirements.
3. The Excel data source-based data processing method for visualization application creation of claim 2, wherein: and S3, marking the to-be-processed cell filled with the data of the transverse merging cell as a comparison cell, comparing the data of the comparison cell with the data of other cells in a data column where the comparison cell is located, taking the data row where the same data is located as a reference data row if the same data exists, and sequentially filling each data in the reference data row, which is located in the same data column as each remaining to-be-processed cell, into each remaining to-be-processed cell.
4. The Excel data source-based data processing method for visualization application creation of claim 3, wherein: s3, when the longitudinal merging cells are checked, if the data format of the longitudinal merging cells is a special format, returning the longitudinal merging cells, and prompting manual processing; when the transverse merging cells are checked, if the data format of the transverse merging cells is a special format, returning the transverse merging cells, and prompting manual processing; the special formats include integers, floating point numbers, and computational formulas.
5. The Excel data source-based data processing method for visualization application creation of claim 4, wherein: and S3, comparing and calculating the similarity value according to the data type and the data item.
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