Data analysis is a field of mathematics and computer science that deals with the construction and research of the most general mathematical methods and computational algorithms for extracting knowledge from experimental data. The process of exploring, filtering, transforming and modeling data in order to extract useful information and make decisions. To do this, you need to get the data using web scraping. Data analysis has many aspects and approaches, covers different methods in various fields of science and activity.
The described problem of recognition of numbers can be solved by trying to independently select a function that implements the corresponding display. It will work out, most likely, not very quickly and not very well. On the other hand, you can resort to machine learning methods, that is, use a manually labeled sample (or, in other cases, one or another historical data) to automatically select a decision function. Thus, hereinafter, I will call a (generalized) machine learning algorithm an algorithm that, one way or another, based on data, forms a non-deterministic algorithm that solves a particular problem.
The data analysis engine is a set of embedded language objects interacting with each other, which allows the developer to use its constituent parts in any combination in any application solution. Built-in objects allow you to easily organize the interactive setting of analysis parameters by the user, and also allow you to display the analysis result in a form that is convenient for display in a spreadsheet document.


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