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Some examples of these will be provided for each language.
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## Help files
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R and Matlab provide offline help files for understanding package functionalities and APIs.
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### Useful Packages
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**numpy - Fast numerical processing.
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**pandas - Table data structures.
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**jupyter-notebook - For running jupyter-notebooks.
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**scipy - Wide range of packages for scientific computing.
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**scikit-learn - Machine learning in python.
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**plotly - Interactive charts.
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**nPYc Toolbox - NPC built toolbox for NMR and MS import, preprocessing, QC, and generating reports.
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- numpy - Fast numerical processing.
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- pandas - Table data structures.
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- jupyter-notebook - For running jupyter-notebooks.
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- scipy - Wide range of packages for scientific computing.
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- scikit-learn - Machine learning in python.
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- plotly - Interactive charts.
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- nPYc Toolbox - NPC built toolbox for NMR and MS import, preprocessing, QC, and generating reports.
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# Further Reading
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We recommend further reading and training. The Software Carpentry courses are available online and are recommended for more in-depth training on specific languages and technologies.
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