# data[].attributes.body
Making rapid changes to plots / analysis etc.

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Command-line programming is easier (ultimately) and more hands on.

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Command-line programming is easier (ultimately) and more hands on.

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It is proper research computing and we offer research-led teaching. Better than teaching with software that may be good for teaching but not for real-world and research applications.

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It is proper research computing and we offer research-led teaching. Better than teaching with software that may be good for teaching but not for real-world and research applications.

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R can process data very quickly

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Critique - DO less but in more detail

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Lots of help available across the internet. Lots of functions already written for data manipulation/ analysis

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Lots of help available across the internet. Lots of functions already written for data manipulation/ analysis

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Critique - lots of models etc are not is R so there are issues with being able to use python etc codes and models

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Critique - lots of models etc are not is R so there are issues with being able to use python etc codes and models

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R can deal with large datasets, whereas other software like Excel and Arcmap cannot handle.

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R can deal with large datasets, whereas other software like Excel and Arcmap cannot handle.

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Can be used to write publishable materials, websites and other outputs.

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Can be used to write publishable materials, websites and other outputs.

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Keep the learning environment consistent.

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Extensible: you’re not limited by options that are directly supported, you can build what you meed

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R requires less headaches to get it work (less codding skills, less thinking about error) 

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R requires less headaches to get it work (less codding skills, less thinking about error) 

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More intuitive than 0-indexing, as used in python

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Industry desirable skill set

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R is used widely in industry, and it is open source.

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R is used widely in industry, and it is open source.

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Wide usage through academia and projects

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Wide usage through academia and projects

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available to Mac and Windows users

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R can manage large datasets that spss etc can't manage

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R can manage large datasets that spss etc can't manage

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S has become R so there is a long history of using R

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S has become R so there is a long history of using R

# data[].attributes.headline
R has much more accessible help framework than alternatives such as python.

# data[].attributes.subject
R has much more accessible help framework than alternatives such as python.