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Code generation is the process of generating executable code (e.g. SQL, Python, R, or other executable instructions) that will transform the data based on the desired and defined data mapping rules. [4] Typically, the data transformation technologies generate this code [5] based on the definitions or metadata defined by the developers.
Pandoc is a free-software document converter, widely used as a writing tool (especially by scholars) [2] and as a basis for publishing workflows. [3] It was created by John MacFarlane, a philosophy professor at the University of California, Berkeley. [4]
deskUNPDF: PDF converter to convert PDFs to Word (.doc, docx), Excel (.xls), (.csv), (.txt), more; GSview: File:Convert menu item converts any sequence of PDF pages to a sequence of images in many formats from bit to tiffpack with resolutions from 72 to 204 × 98 (open source software) Google Chrome: convert HTML to PDF using Print > Save as PDF.
Decision tables are a concise visual representation for specifying which actions to perform depending on given conditions. Decision table is the term used for a Control table or State-transition table in the field of Business process modeling; they are usually formatted as the transpose of the way they are formatted in Software engineering.
PDF's emphasis on preserving the visual appearance of documents across different software and hardware platforms poses challenges to the conversion of PDF documents to other file formats and the targeted extraction of information, such as text, images, tables, bibliographic information, and document metadata. Numerous tools and source code ...
Solid Converter PDF is document reconstruction software from Solid Documents which converts PDF files to editable formats. Originally released for the Microsoft Windows operating system, a Mac OS X version was released in 2010. The current versions are Solid Converter PDF 9.0 for Windows and Solid PDF to Word for Mac 2.1.
which shows which documents contain which terms and how many times they appear. Note that, unlike representing a document as just a token-count list, the document-term matrix includes all terms in the corpus (i.e. the corpus vocabulary), which is why there are zero-counts for terms in the corpus which do not also occur in a specific document.
In Python NumPy arrays implement the flatten method, [note 1] while in R the desired effect can be achieved via the c() or as.vector() functions. In R , function vec() of package 'ks' allows vectorization and function vech() implemented in both packages 'ks' and 'sn' allows half-vectorization.