Processing method for presenting data index hierarchies and classifications in spreadsheet

Abstract

The invention discloses a processing method for presenting data index hierarchies and classifications in a spreadsheet, and the method comprises the steps: building an index index structure S, presenting indexes and hierarchies, index classification description and hierarchies, application scenes of index and index classification description and other implicit attributes in a spreadsheet mode according to the personalized selection of a user, so that index expression is simpler, readability is higher, accurate expression of two-dimensional table data can be achieved, and a presented table is easier to understand. And on the basis, indexes and index classification description can be flexibly and variously combined and displayed, so that the displayed result is more diversified, flexible andpersonalized.

Description

technical field [0001] The invention belongs to the technical field of big data processing, in particular to a processing method for presenting data index levels and classifications in an electronic form. Background technique [0002] In the process of big data governance, the sources of data are diverse, and tabular data files are one of the common types. [0003] Most of the existing statistical data are presented in the form of two-dimensional tables. The actual meaning represented by each value in the table needs to be understood in combination with the title of the table and the indicators corresponding to the horizontal and vertical coordinates of the value, such as figure 1 In , the indicator area of ​​the table can be divided into X coordinate area and Y coordinate area, that is, the indicators of the X coordinate area are "number of enterprises (units)", "#number of enterprises with R&D activities", "#number of enterprises with scientific and technological instituti...

AI Technical Summary

Problems solved by technology

Most of the new indicators formed by the direct combination of XY (or YX) in this way are not standard (or conventional) indicators, and have many defects such as too long indicator names, irregularities, inaccuracies, poor readability, and ambiguity. When there are multiple layers of superior-subordinate or containment relationships, this combination is difficult to express clearly or cannot be expressed at all

Especially in the process of multi-source data fusion, the indicators formed in this way are difficult to form a unified indicator library, and it is also not conducive to large-scale combination operations of data and mining of implicit information such as the relationship between indicators. Realize the needs of on-demand display and flexible combination

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