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In the Print/export section select Download as PDF. The rendering engine starts and a dialog appears to show the rendering progress. When rendering is complete, the dialog shows "The document file has been generated. Download the file to your computer." Click the download link to open the PDF in your selected PDF viewer.
Before starting a download of a large file, check the storage device to ensure its file system can support files of such a large size, check the amount of free space to ensure that it can hold the downloaded file, and make sure the device(s) you'll use the storage with are able to read your chosen file system.
Older (.OPJ), but not newer (.OPJU), Origin project files can be read by the open-source LabPlot or SciDAVis software. The files can also be read by QtiPlot but only with a paid "Pro" version. Finally the liborigin [1] library can also read .OPJ files such as by using the opj2dat script, which exports the data tables contained in the file.
Orange is an open-source software package released under GPL and hosted on GitHub.Versions up to 3.0 include core components in C++ with wrappers in Python.From version 3.0 onwards, Orange uses common Python open-source libraries for scientific computing, such as numpy, scipy and scikit-learn, while its graphical user interface operates within the cross-platform Qt framework.
Computer-assisted (or aided) qualitative data analysis software (CAQDAS) offers tools that assist with qualitative research such as transcription analysis, coding and text interpretation, recursive abstraction, content analysis, discourse analysis, [1] grounded theory methodology, etc.
SAS is a software suite that can mine, alter, manage and retrieve data from a variety of sources and perform statistical analysis on it. [3] SAS provides a graphical point-and-click user interface for non-technical users and more through the SAS language.
R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]