Method, device and storage medium for data exploration

Abstract

The application discloses a data exploration method, device and storage medium. The data exploration method comprises the following steps: obtaining a data exploration entrance in a toolbar of an electronic form; the data exploration entrance is used for entering a data exploration mode; the data exploration mode comprises a brief mode and a detailed mode; if the data exploration mode is selected as the brief mode, generating exploration result overview information of each column of data according to a data type of the column of data and determining corresponding visualization tools, and displaying an exploration view corresponding to the exploration result overview information of each column of data in the electronic form through the visualization tools; and if the data exploration mode is selected as the detailed mode, generating exploration result detailed information of each column of data according to a data type of the column of data and determining corresponding visualization tools, and displaying an exploration view corresponding to the exploration result detailed information of each column of data in a new window through the visualization tools. The application can enrich data exploration means of the electronic form.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the technical field of computer, in particular to a method, device and storage medium for data exploration. BACKGROUND

[0002] With the development of the Internet, people have got rid of the shackles of having to save, edit and analyze data in local Excel, and can easily do so on the network through WebExcel (Web version of electronic spreadsheets). At the same time, they can share their data with others at any time for viewing and editing.

[0003] However, this does not solve all the problems. At a glance, a pile of messy data in the table, except for the title and type of each column, we know almost nothing about its statistical information. Generally speaking, the more null values, outliers and values that do not conform to the original data type in the data, the poorer the data quality. Therefore, it is of great significance to help users understand the quality, structure, distribution and statistical information of the current data. SUMMARY

[0004] The present disclosure provides a method, device and storage medium for data exploration, which can realize a front-end interaction and display scheme for data exploration, and enrich the data exploration means of electronic spreadsheets.

[0005] In a first aspect, the present disclosure provides a method for data exploration, comprising:

[0006] obtaining a data exploration portal in a toolbar of an electronic spreadsheet; the data exploration portal is used to enter a data exploration mode; the data exploration mode includes a brief mode and a detailed mode;

[0007] if the data exploration mode is selected as the brief mode, generating exploration result overview information of each column of data according to the data type of the column of data and determining corresponding visualization tools, and displaying an exploration view corresponding to the exploration result overview information of each column of data in the electronic spreadsheet through the visualization tools; if the data exploration mode is selected as the detailed mode, generating exploration result detailed information of each column of data according to the data type of the column of data and determining corresponding visualization tools, and displaying an exploration view corresponding to the exploration result detailed information of each column of data in a new window through the visualization tools.

[0008] In a second aspect, the present disclosure provides a device for data exploration, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to realize the steps of the method for data exploration provided in the first aspect.

[0009] In a third aspect, the present disclosure provides a computer readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the data exploration method provided in the first aspect.

[0010] The data exploration method, device and storage medium provided by the embodiments of the present disclosure can obtain a data exploration portal in a toolbar of an electronic table, generate overview information of exploration results of each column of data according to a data type of the column of data in a brief mode and determine corresponding visualization tools, display an exploration view corresponding to the overview information of exploration results of each column of data in the electronic table through the visualization tools, generate detailed information of exploration results of each column of data according to the data type of the column of data in a detailed mode and determine corresponding visualization tools, and display an exploration view corresponding to the detailed information of exploration results of each column of data in a new window through the visualization tools. The data exploration method, device and storage medium can realize a front-end interaction and display scheme of data exploration, and enrich data exploration means of the electronic table.

[0011] Other aspects can become apparent from the following detailed description when read in conjunction with the drawings. BRIEF DESCRIPTION OF DRAWINGS

[0012] The accompanying drawings are included to provide a further understanding of the present disclosure and constitute a part of the specification, which together with the detailed description, serve to explain the present disclosure. The drawings illustrate embodiments of the present disclosure and, together with the detailed description, serve to explain the present disclosure. However, the present disclosure is not limited to the specific embodiments disclosed herein.

[0013] Figure 1 A data exploration method flowchart of the embodiments of the present disclosure;

[0014] Figure 2 A data exploration portal in a brief mode of the data exploration of the embodiments of the present disclosure;

[0015] Figure 3 An exploration view in a brief mode of the data exploration of the embodiments of the present disclosure;

[0016] Figure 4 An exploration view in a detailed mode of the data exploration of the embodiments of the present disclosure;

[0017] Figure 5 A brief mode exploration view of an application example of the present disclosure;

[0018] Figure 6 A brief mode exploration view after a filtering operation of an application example of the present disclosure;

[0019] Figure 7 A detailed mode exploration view of an application example of the present disclosure;

[0020] Figure 8A schematic diagram of a data exploration device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0021] The present disclosure describes a number of embodiments, but the description is illustrative rather than limiting and many other embodiments and implementations will be apparent to those of ordinary skill in the art in view of this disclosure. Although a number of possible combinations of features have been set forth herein, many other combinations will be apparent to those of ordinary skill in the art and can be made without departing from the spirit and scope of embodiments of the disclosure. Unless specifically intended otherwise, any feature or element in any embodiment can be utilized in any other embodiment, whether or not that particular combination of features is specifically stated in the embodiments. In addition, some of these combinations will now be evident to those of ordinary skill in the art and can be implemented, for example, without departing from the spirit or scope of the disclosure.

[0022] The present disclosure includes and contemplates combinations of features and elements known to those of ordinary skill in the art. The presently disclosed embodiments, features and elements can also be combined with any conventional feature or element to form a unique application of the presently claimed disclosure that is not specifically disclosed. Any feature or element of any embodiment can also be combined with features or elements from other applications to form another unique application of the presently claimed disclosure that is not specifically disclosed. Thus, it will be understood that any of the features shown and / or discussed in the present disclosure can be implemented alone or in any combination. Accordingly, except as it can be otherwise limited, the scope of embodiments is not to be limited by the specific recitations of features or steps, nor to the specific combinations of features, steps or feature sets specifically set forth herein, but only by the appended claims, and even those claims to the extent they are drafted to be base on the proper construction of the claims. Furthermore, the use of the terms "a" and "an" and "the" and "at least one" are used generically, and are not intended to be limiting. For example, "an" or "at least one" shall mean one or more unless specified otherwise. The use of the terms "at least one", "one or more" and "and / or" are synonymous.

[0023] Furthermore, in describing representative embodiments, the specification can have presented the method and / or process as a particular sequence of steps. However, to the extent that the method or process depends on more than one step, the method or process should not be construed as limited to the particular sequence of steps described. Other sequences of steps can possible, and should be construed as either implicitly set forth in the description or as explicitly set forth in the claims. The steps of the methods and / or processes described herein are also not limited to the specific recitations of steps, nor to the specific combinations of steps, as set forth. It will be apparent to those skilled in the art that other sequences of steps, including processing and production steps, are possible. Thus, the particular sequence of steps set forth in the specification is not a limitation of the application. Other sequences of steps can carry out the methods and / or processes essentially identical to those described, and are intended to be within the scope of the present application. The descriptions of the steps of various processes and methods are not limited to the specific sequences set forth, but cover any and all sequences consistent with the descriptions.

[0024] Figure 1 A flowchart of a data exploration method according to an embodiment of the present disclosure is shown in Figure 1 As shown, the data exploration method can include:

[0025] At step S10, a data exploration entry is obtained in a toolbar of a spreadsheet; the data exploration entry is used to enter a data exploration mode; the data exploration mode includes a brief mode and a detailed mode.

[0026] If the data exploration mode is selected as the brief mode, the step S20 generates the exploration result overview information of each column of data according to the data type of the column of data and determines the corresponding visualization tool, and displays the exploration view corresponding to the exploration result overview information of each column of data in the electronic table through the visualization tool in the electronic table; if the data exploration mode is selected as the detailed mode, the step S20 generates the exploration result detailed information of each column of data according to the data type of the column of data and determines the corresponding visualization tool, and displays the exploration view corresponding to the exploration result detailed information of each column of data in a new window through the visualization tool;

[0027] In the above embodiment, the data exploration entrance is provided in the toolbar of the electronic table, and two data exploration modes (brief mode and detailed mode) are provided. In the brief mode, the exploration result overview information of each column of data in the electronic table is provided to the user through the visualization tool in the electronic table, and in the detailed mode, the exploration result detailed information of each column of data is displayed in a new window through the visualization tool. Through the analysis and display of data in multiple exploration modes, the user can understand various information of the data in the electronic table.

[0028] In an exemplary embodiment, the data exploration entrance is one or two; when the data exploration entrance is one, the system enters the brief mode first, and then enters the detailed mode through the detailed mode button in the brief mode view; when the data exploration entrance is two, the brief mode and the detailed mode are respectively in the toolbar corresponding to the respective data exploration entrances.

[0029] In an exemplary embodiment, the new window is a pop-up window. In other embodiments, the new window can also be a floating layer, a floating window, or a new page.

[0030] In an exemplary embodiment, the visualization tool includes one or more of the following tools: a chart and a rich text.

[0031] In an exemplary embodiment, the chart includes one or more of the following: a pie chart and a binned column chart.

[0032] In an exemplary embodiment, the data type includes: string type, date type, number type, Boolean type, or mixed type. The mixed type refers to a column of data including two or more data types.

[0033] In an exemplary embodiment, the toolbar of the electronic table is located at the top of the electronic table.

[0034] In an exemplary embodiment, the visualization tool for presenting the overview information of the exploration result of each column of data is located at the top of the spreadsheet where the column of data is located;

[0035] In an exemplary embodiment, the overview information of the exploration result of a column of data comprises one or more of the following information: data type distribution overview of the column of data, numerical value distribution overview of the column of data;

[0036] In an exemplary embodiment, the generating of the overview information of the exploration result of each column of data according to the data type of the column of data and the determining of the corresponding visualization tool comprise:

[0037] If the data type of the column of data is string type or date type, one or more of the following information is taken as the overview information of the exploration result of the column of data: numerical value D of the N top repeated value data in the column of data i and the corresponding proportion a i proportion b of the data amount of the remaining data in the column of data except the N repeated value data; wherein, 1≤i≤N; the data amount sum of the unique value data and the proportion when the data amount sum of the unique value data in the column of data exceeds a first threshold value;

[0038] Rich text is selected as the corresponding visualization tool of the column of data;

[0039] Wherein, the unique value data refers to the data appearing only once in the column of data, and the repeated value data refers to the data appearing more than once in the column of data.

[0040] Wherein, the first threshold value is a value pre-set by the system, for example, the first threshold value is 50%, or other values. N is an integer pre-set by the system; for example, N is equal to 2 or 3, or other values.

[0041] In an exemplary embodiment, the generating of the overview information of the exploration result of each column of data according to the data type of the column of data and the determining of the corresponding visualization tool comprise:

[0042] If the data type of the column of data is numerical type, the column of data is divided into m intervals according to the numerical value range; A≤m≤B, A

[0043] The numerical value range of each interval and the data amount of the interval are taken as the overview information of the exploration result of the column of data;

[0044] The binned column chart is selected as the corresponding visualization tool of the column of data;

[0045] Wherein, A and B are values pre-set by the system, for example, A=4 and B=10. A and B can also be other values.

[0046] In an exemplary embodiment, the generating the overview information of the probe result of each column of data according to the data type of the column of data and determining the corresponding visualization tool comprises:

[0047] If the data type of the column of data is Boolean type, the data amount of each Boolean value accounts for the proportion of the total data amount of the column of data;

[0048] The overview information of the probe result of the column of data includes each Boolean value and the proportion of the data amount of the Boolean value accounts for the total data amount of the column of data;

[0049] The pie chart is selected as the corresponding visualization tool of the column of data;

[0050] In an exemplary embodiment, the generating the overview information of the probe result of each column of data according to the data type of the column of data and determining the corresponding visualization tool comprises:

[0051] If the data type of the column of data is mixed type, the data amount of each data type accounts for the proportion of the total data amount of the column of data;

[0052] The overview information of the probe result of the column of data includes each data type and the proportion of the data amount of the data type accounts for the total data amount of the column of data;

[0053] The pie chart is selected as the corresponding visualization tool of the column of data;

[0054] In an exemplary embodiment, if the data probe mode is selected as the brief mode, the method further comprises:

[0055] The refresh button is obtained, and the refresh button is used to refresh the data of the corresponding column and the probe view of the column in the spreadsheet after one or more columns of data in the spreadsheet are edited or filtered.

[0056] In other embodiments, after one or more columns of data in the spreadsheet are edited or filtered, the data of the corresponding column and the probe view of the column in the spreadsheet can also be automatically refreshed;

[0057] In an exemplary embodiment, the detailed information of the probe result of a column of data includes one or more of the following information: the field name of the column of data, the data type of the column of data, the quality information of the column of data, the data distribution information of the column of data, and the data statistical information of the column of data;

[0058] The data distribution information of the column of data includes one or more of the following: the data type distribution information of the column of data and the numerical value distribution information of the column of data;

[0059] The data statistics of the column data include one or more of the following: a maximum value of the column data, a minimum value of the column data, a sum of values of the column data, a mean value of the column data, and a standard deviation of the column data.

[0060] The quality information of the column data includes one or more of the following: a number and a rate of null values of the column data, a number and a proportion of valid values of the column data, and a number and a proportion of unique values of the column data.

[0061] In an exemplary embodiment, the detailed information of the exploration result of each column data is generated according to the data type of the column data, and the corresponding visualization tool is determined, including:

[0062] If the data type of the column data is a string type or a date type, one or more of the following information is used as the detailed information of the exploration result of the column data: a field name of the column data, a data type of the column data, a data volume of the column data, a number and a proportion of unique values of the column data, a number and a rate of null values of the column data, a number and a proportion of valid values of the column data, and a number and a proportion of top M repeated value data of the column data.

[0063] Rich text is selected as the corresponding visualization tool of the column data.

[0064] In an exemplary embodiment, the detailed information of the exploration result of each column data is generated according to the data type of the column data, and the corresponding visualization tool is determined, including:

[0065] If the data type of the column data is a number type, one or more of the following information is used as the detailed information of the exploration result of the column data: a field name of the column data, a data type of the column data, a data volume of the column data, a number and a proportion of zero values of the column data, a number and a proportion of unique values of the column data, a number and a rate of null values of the column data, a number and a proportion of valid values of the column data, a number and a proportion of top M repeated value data of the column data, data statistics of the column data, and value distribution information of the column data.

[0066] Rich text and a binned column chart are selected as the corresponding visualization tool of the column data.

[0067] In an exemplary embodiment, the detailed information of the exploration result of each column data is generated according to the data type of the column data, and the corresponding visualization tool is determined, including:

[0068] If the data type of the column data is Boolean, one or more of the following information is taken as the exploration result details of the column data: the field name of the column data, the data type of the column data, the data volume of the column data, the number and proportion of zero values of the column data, the number and proportion of unique values of the column data, the number of null values and the null value rate of the column data, the number and proportion of valid values of the column data, the top M repeated value data of the column data in terms of data volume and the corresponding proportion, and the data volume proportion of each Boolean value of the column data;

[0069] Rich text and pie chart are selected as the visualization tools corresponding to the column data.

[0070] In an exemplary embodiment, generating the exploration result details of each column data and determining the corresponding visualization tools according to the data type of the column data comprises:

[0071] If the data type of the column data is mixed, one or more of the following information is taken as the exploration result details of the column data: the field name of the column data, the data type of the column data, the data volume of the column data, the number and proportion of zero values of the column data, the number and proportion of unique values of the column data, the number of null values and the null value rate of the column data, the number and proportion of valid values of the column data, the top M repeated value data of the column data in terms of data volume and the corresponding proportion, and the data volume proportion of each data type of the column data.

[0072] Rich text and pie chart are selected as the visualization tools corresponding to the column data.

[0073] Wherein, M is an integer preset by the system; for example, M is equal to 5 or other values.

[0074] In an exemplary embodiment, the method further comprises:

[0075] Upon detecting a drill-down operation on the binned column chart view, taking all data within the data range corresponding to the drill-down operation as a new data set, dividing the new data set into n intervals according to the numerical value range, each interval corresponding to a bin column in the new binned column chart, and displaying the new binned column chart; wherein A≤n≤B, A

[0076] Upon detecting a click on the return button on the new binned column chart view, returning to the original binned column chart view or the view of the previous binned column chart.

[0077] Wherein, the drill-down operation can be one or more levels of drill-down.

[0078] For numerical data in spreadsheets, displaying the numerical distribution of a column of data using a binned bar chart can employ dynamic binning. Dynamic binning can use either bin height or step size mechanisms. When using a step size mechanism, assuming the number of bins *n* satisfies the condition 4 ≤ *n* ≤ 10, if the number of bins with data below the threshold is greater than or equal to half the total number of bins, the number of bins can be reduced, and binning can be restarted until the total number of bins reaches four. This ensures that at most two bins have data below the threshold, and the bins with larger data volumes can be drilled down to examine their specific distribution information.

[0079] like Figure 2 As shown, a data exploration entry point is provided in the toolbar at the top of the spreadsheet. After the user clicks the data exploration entry button, the system enters data exploration mode. The data exploration mode is a simplified mode by default (or the system default).

[0080] like Figure 3 As shown, in simplified mode, a visualization tool at the top of the spreadsheet displays an overview of the exploration results for each column of data. When a column's data type is Boolean or Combined, a pie chart is displayed at the top, showing the percentage of each Boolean value (or data type within a Combined type) in the column's total data. When a column's data type is numeric (Int or Float), a binned bar chart is displayed at the top, showing the numerical distribution of the data. When a column's data type is String or Date, rich text is displayed at the top, showing the values ​​and percentages (50%, 20%) of the two most frequent duplicate values ​​in the column, and the percentage of the remaining data excluding these two duplicate values ​​(30%).

[0081] like Figure 4 As shown, in detailed mode, a new window (pop-up) displays the exploration view corresponding to the detailed exploration results of each column of data through visualization tools.

[0082] If the data type of a column of data is string or date, the following is displayed in a new window through rich text: the field name of the column of data, the data type of the column of data (string or date), the number of fields of the column of data (data volume), the number and proportion of unique values of the column of data, the number and proportion of valid values of the column of data, the number of null values of the column of data and the null value rate, the top 5 repeated value data of the column of data in terms of data volume and the corresponding proportion.

[0083] If the data type of a column of data is number (integer or float), the following is displayed in a new window through rich text: the field name of the column of data, the data type of the column of data (number (integer or float)), the number of fields of the column of data (data volume), the number and proportion of unique values of the column of data, the number and proportion of zero values of the column of data, the number of null values of the column of data and the null value rate, the top 5 repeated value data of the column of data in terms of data volume and the corresponding proportion; the data statistical information of the column of data; the following is displayed in a new window through a binned column chart: the numerical value distribution information of the column of data.

[0084] If the data type of a column of data is Boolean, the following is displayed in a new window through rich text: the field name of the column of data, the data type of the column of data (Boolean), the number of fields of the column of data (data volume), the number and proportion of unique values of the column of data, the number and proportion of zero values of the column of data, the number of null values of the column of data and the null value rate, the top 5 repeated value data of the column of data in terms of data volume and the corresponding proportion; the following is displayed in a new window through a pie chart: the data volume proportion of each Boolean value of the column of data;

[0085] If the data type of a column of data is mixed, the following is displayed in a new window through rich text: the field name of the column of data, the data type of the column of data (mixed), the number of fields of the column of data (data volume), the number and proportion of unique values of the column of data, the number and proportion of zero values of the column of data, the number of null values of the column of data and the null value rate, the top 5 repeated value data of the column of data in terms of data volume and the corresponding proportion; the following is displayed in a new window through a pie chart: the data volume proportion of each data type of the column of data.

[0086] In an exemplary embodiment, the electronic spreadsheet includes: a web-based electronic spreadsheet, or an electronic spreadsheet directly running on an operating system;

[0087] The web-based spreadsheet is a spreadsheet running in a browser. The web-based spreadsheet includes, for example, a spreadsheet running directly in a browser on a PC, a spreadsheet running in a client-embedded browser, a spreadsheet running in a webview embedded in an APP, and the like. The web-based spreadsheet has a host of a browser and relies on browser-related technologies. The browser-related technologies include JavaScript, HTML, CSS, and the like.

[0088] The spreadsheet running directly on an operating system includes, for example, a spreadsheet running on a general computer client and a spreadsheet running in a native APP of a mobile phone. The spreadsheet running directly on an operating system has a host of a bottom-layer operating system and relies on bottom-layer operating system-related technologies. The bottom-layer operating system-related technologies include Windows, Mac, Ios, Android, and the like.

[0089] In an exemplary embodiment, for the web-based spreadsheet, the browser directly completes the above data exploration process on the browser side after obtaining the spreadsheet data, thereby avoiding the user from modifying or screening the data and then transmitting the data back to the server for analysis, saving the time for data transmission between the browser and the server, improving the computing performance and reducing the server overhead, and providing a smoother interactive experience. The above data exploration process can be optimized by using the worker mechanism of the browser. The worker is a multi-thread processing means provided by the browser. Through the worker mechanism, the main thread of the page can not be occupied by a large amount of calculation in the data exploration process, thereby avoiding the occurrence of UI freeze. In addition to the embodiment in which the above data exploration process is processed on the browser front end, in other embodiments, part of the calculation tasks of the above data exploration process can be placed on the back-end server, and data can be transmitted through an interface by using the Http protocol.

[0090] The data exploration method of the present disclosure can be applied to a cloud-based big data development platform (such as DataWorks of Ali Cloud). DataWorks is a PaaS (Platform as a Service) platform product that can provide data integration, data development, data mapping, data analysis, and data services, and the like. Customers can use the DataWorks data analysis platform to perform operations such as data transmission, conversion, and integration, import data from different data storage, and perform conversion and development. The processed data can be synchronized to other data systems. Users can import local data or remote data source data into a web-based spreadsheet on the DataWorks data analysis platform and perform data exploration.

[0091] The data exploration method of the present disclosure can also be applied to a cloud service providing an electronic table data exploration function. A user uploads an electronic table on a server providing the cloud service, or selects an electronic table on the server providing the cloud service, or gives a link address of a remote electronic table (the link address can be an electronic table storage address of another website providing an electronic table service), and then the server providing the cloud service displays the electronic table in a website interface and provides an exploration entry. When the user operates in the website interface, the server performs corresponding operations, and displays the obtained exploration result in the website interface to the user.

[0092] The data exploration method of the present disclosure can also be applied to a client providing an electronic table data exploration function. A user specifies an electronic table in a local or a link in an interface of the client, and the client displays the electronic table and provides an exploration entry. The user performs data exploration operations in the client, and the client generates a request to a server according to the data exploration operations. The server processes the request, and returns the processing result to the client. The client displays the data exploration result.

[0093] The data exploration method of the present disclosure can also be applied to an APP (an application program embedded with a browser) providing an electronic table data exploration function. A user specifies an electronic table in a local or a link in an interface of the APP, and the APP displays the electronic table and provides an exploration entry. The user performs data exploration operations in the APP, and the APP generates a request to a server according to the data exploration operations. The server processes the request, and returns the processing result to the APP. The APP displays the data exploration result.

[0094] The data exploration method of the present disclosure can also be applied to an electronic table software independently running on a terminal device. After the software is run on the device, the software displays an electronic table in an interface and provides an exploration entry after the user submits the electronic table. Subsequently, the software performs data exploration processing according to user operations to obtain a processing result, and displays the processing result in a software interface.

[0095] Taking the DataWorks data analysis platform as an example, combined with Figure 5 , attached Figure 6 and attached Figure 7This describes the process of data exploration using the data exploration method disclosed herein. For example, if Client A of the DataWorks data analysis platform is a market research company, when conducting market research on mobile apps, they can first import relevant data on currently available mobile applications into a spreadsheet on the DataWorks data analysis platform. This relevant data includes, for example, app categories, ratings, pricing categories, number of reviews, downloads, prices, versions, and last update times. If Client A wants to understand the quality of the data after importing the market research data into the DataWorks data analysis platform spreadsheet, they can use the data exploration method of this application to conduct data exploration.

[0096] Suppose the client chooses to explore the data in simplified mode. For example... Figure 5 As shown, in simplified mode, a visualization tool at the top of the spreadsheet displays an overview of the exploration results for each column of data. The first column is a list of app names, with rich text at the top showing the app name statistics: 30 app names. The second column is a list of app categories, with rich text at the top showing the category statistics: Family (17%), Communication (17%), and Other (66%). The third column is a list of ratings, with a binned bar chart at the top showing the distribution of ratings from 0 to 5 stars. The fourth column is a list of paid categories, with rich text at the top showing the category statistics: Free apps (57%), Paid apps (43%). The fifth column is a list of review counts, with a binned bar chart at the top showing the review count distribution. The sixth column is a list of downloads, with a binned bar chart at the top showing the download count distribution. The seventh column is the price list, with a pie chart displayed at the top showing the percentage of the top-ranked price in the column. The eighth column is the version information list, with a binned bar chart at the top showing the distribution of version information. The ninth column is the most recent update time list, with rich text at the top displaying the categorized statistics: applications last updated in 2015 account for 23%, applications last updated in 2016 account for 23%, and applications last updated in other years account for 54%.

[0097] The simplified mode also provides filtering functions, such as Figure 6 As shown, assuming the user selects only the free type in the paid categories, the data in the spreadsheet will be refreshed, retaining only the data rows of free applications while filtering out the data rows of paid applications. At the top of the spreadsheet, a visualization tool will be used to display an overview of the exploration results for each column of updated data.

[0098] Assume that the customer selects to explore the data in the detailed mode. As shown in Figure 7 , the customer wants to explore the ratings of the users on the applications, for example, from the detailed mode exploration view as shown in Figure 7 , various statistical results including the null rate can be obtained. For the data information of the rating column, the null rate is 20%, that is, 6 out of 30 applications are not rated by the customer

[0099] Figure 8 An example diagram of an apparatus for data exploration is provided in the embodiments of the present disclosure. As shown in Figure 8 , the apparatus for data exploration provided in the example embodiment includes a processor 100 and a memory 200; wherein the processor 100 and the memory 200 are connected through a bus, the memory 200 stores a computer program, and the computer program is executed by the processor 100 to implement the steps of the method for data exploration.

[0100] It should be understood that the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), ready programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0101] The memory can include read-only memory and random access memory, and provide instructions and data to the processor. A portion of the memory can also include non-volatile random access memory. For example, the memory can also store device type information.

[0102] The bus can include not only a data bus, but also a power supply bus, a control bus, a status signal bus, etc.

[0103] In the implementation process, the processing performed by the apparatus for generating a page can be completed by the integrated logic circuit of hardware in the processor or the instructions in the form of software. That is, the steps of the method in the embodiments of the present disclosure can be implemented by the hardware processor to complete, or by the combination of hardware and software modules in the processor to complete. The software module can be located in a storage medium such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, register, etc. The storage medium is located in the memory, and the processor reads the information in the memory and combines the hardware to complete the steps of the above method. To avoid repetition, the specific content of the method will not be described in detail here.

[0104] The embodiment of the present disclosure provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the steps of the method for data exploration.

[0105] Those skilled in the art can understand that all or some steps in the method disclosed above, functions of the modules / units in the system and the device can be implemented as software, firmware, hardware and appropriate combinations thereof. In the hardware implementation, the division between the function modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component can have multiple functions, or one function or step can be performed by several physical components in cooperation. Some or all of the components can be implemented as software executed by a processor such as a digital signal processor or a microprocessor, or as hardware, or as an integrated circuit such as an application-specific integrated circuit. Such software can be distributed on a computer readable medium, which can include computer storage media (or non-transitory media) and communication media (or transitory media). As known to those skilled in the art, the term computer storage media includes volatile and non-volatile, 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. 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 tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. In addition, it is known to those skilled in the art that communication media generally includes 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 can include any information delivery medium.

[0106] It should be noted that the present disclosure can have other various embodiments, and those skilled in the art can make various corresponding changes and modifications to the present disclosure according to the present disclosure without departing from the spirit and essence of the present disclosure. However, these corresponding changes and modifications should all fall within the protection scope of the claims attached to the present disclosure.

Claims

1. A method for data exploration, comprising: obtaining a data exploration entry in a toolbar of a spreadsheet displayed by a cloud service; the spreadsheet comprises a web-based spreadsheet or a spreadsheet running directly on an operating system; the data exploration entry is used to enter a data exploration mode; the data exploration mode comprises a brief mode and a detailed mode; if the data exploration mode is selected as the brief mode, generating overview information of a data exploration result of each column of data according to a data type of the column of data and determining a corresponding visualization tool, and displaying a data exploration view corresponding to the overview information of the data exploration result of each column of data in the spreadsheet by the visualization tool; obtaining a refresh button, the refresh button is used to refresh data of a corresponding column and a data exploration view of the column in the spreadsheet after one or more columns of data in the spreadsheet are edited or filtered; if the data exploration mode is selected as the detailed mode, generating detailed information of a data exploration result of each column of data according to a data type of the column of data and determining a corresponding visualization tool, and displaying a data exploration view corresponding to the detailed information of the data exploration result of each column of data in a new window by the visualization tool; In response to detecting a drill-down operation on the binned column chart view, binning all data in a data range corresponding to the drill-down operation into n intervals, each interval corresponding to a bin in a new binned column chart, and displaying the new binned column chart; wherein , ; wherein the drill-down operation is a click on a bin of the binned column chart, and the binned column chart is a visualization tool corresponding to column data of a data type of number. detecting that a return button on a new binned column chart view is clicked, and returning to a view of an original binned column chart or a view of a previous binned column chart; wherein the drill-down operation is one or more levels of drill-down. 2.The method of claim 1, wherein: the generating overview information of a data exploration result of each column of data according to a data type of the column of data and determining a corresponding visualization tool comprises: If the data type of the column data is string type or date type, one or more of the following information is taken as the overview information of the exploration result of the column data: the values of the top N repeated value data in the column data in terms of data amount and the corresponding proportion , the proportion b of the data amount of the remaining data in the column data excluding the N repeated value data; wherein the total data amount and the proportion of the unique value data when the total data amount of the unique value data in the column data exceeds the first threshold value selecting a rich text as the visualization tool corresponding to the column of data. 3.The method of claim 1, wherein: the generating overview information of a data exploration result of each column of data according to a data type of the column of data and determining a corresponding visualization tool comprises: If the data type of the column data is a numeric type, the column data is divided into m intervals according to the value range. , ; taking a numerical range of each interval and a data amount of the interval as the overview information of the data exploration result of the column of data; selecting a binned column chart as the visualization tool corresponding to the column of data. 4.The method of claim 1, wherein: the generating overview information of a data exploration result of each column of data according to a data type of the column of data and determining a corresponding visualization tool comprises: if the data type of the column of data is a Boolean type, calculating a proportion of a data amount of each Boolean value in a total data amount of the column of data; taking each Boolean value and the proportion of the data amount of the Boolean value in the total data amount of the column of data as the overview information of the data exploration result of the column of data; selecting a pie chart as the visualization tool corresponding to the column of data. 5.The method of claim 1, wherein: the generating overview information of a data exploration result of each column of data according to a data type of the column of data and determining a corresponding visualization tool comprises: if the data type of the column of data is a mixed type, calculating a proportion of a data amount of each data type in a total data amount of the column of data; taking each data type and the proportion of the data amount of the data type in the total data amount of the column of data as the overview information of the data exploration result of the column of data; selecting a pie chart as the visualization tool corresponding to the column of data.

6. The method of claim 1, wherein: generating the detailed information of the exploration result of each column of data according to the data type of the column of data and determining the corresponding visualization tool comprises: if the data type of the column of data is string type or date type, taking one or more of the following information as the detailed information of the exploration result of the column of data: the field name of the column of data, the data type of the column of data, the data volume of the column of data, the number and proportion of unique values of the column of data, the number and proportion of null values of the column of data, the number and proportion of valid values of the column of data, the top M repeated value data of the column of data in terms of data volume and the corresponding proportion; and selecting rich text as the corresponding visualization tool of the column of data.

7. The method of claim 1, wherein: generating the detailed information of the exploration result of each column of data according to the data type of the column of data and determining the corresponding visualization tool comprises: if the data type of the column of data is numeric type, taking one or more of the following information as the detailed information of the exploration result of the column of data: the field name of the column of data, the data type of the column of data, the data volume of the column of data, the number and proportion of zero values of the column of data, the number and proportion of unique values of the column of data, the number and proportion of null values of the column of data, the number and proportion of valid values of the column of data, the top M repeated value data of the column of data in terms of data volume and the corresponding proportion, the data statistical information of the column of data, and the numerical value distribution information of the column of data; selecting rich text and binned column chart as the corresponding visualization tool of the column of data.

8. The method of claim 1, wherein: generating the detailed information of the exploration result of each column of data according to the data type of the column of data and determining the corresponding visualization tool comprises: if the data type of the column of data is Boolean type, taking one or more of the following information as the detailed information of the exploration result of the column of data: the field name of the column of data, the data type of the column of data, the data volume of the column of data, the number and proportion of zero values of the column of data, the number and proportion of unique values of the column of data, the number and proportion of null values of the column of data, the number and proportion of valid values of the column of data, the top M repeated value data of the column of data in terms of data volume and the corresponding proportion, and the data volume proportion of each Boolean value of the column of data; selecting rich text and pie chart as the corresponding visualization tool of the column of data.

9. The method of claim 1, wherein: generating the detailed information of the exploration result of each column of data according to the data type of the column of data and determining the corresponding visualization tool comprises: if the data type of the column of data is mixed type, taking one or more of the following information as the detailed information of the exploration result of the column of data: the field name of the column of data, the data type of the column of data, the data volume of the column of data, the number and proportion of zero values of the column of data, the number and proportion of unique values of the column of data, the number and proportion of null values of the column of data, the number and proportion of valid values of the column of data, the top M repeated value data of the column of data in terms of data volume and the corresponding proportion, and the data volume proportion of each data type of the column of data. Rich Text and Pie Chart are selected as the visualization tools corresponding to the data in the column.

10. The method of claim 1, wherein: The spreadsheet comprises a web-based spreadsheet.

11. An apparatus for data exploration, comprising: A memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to implement the steps of the data exploration method in any one of claims 1-10.

12. A computer readable storage medium storing a computer program, and the computer program is executed by a processor to implement the steps of the data exploration method in any one of claims 1-10.

Images