Writing Great R Code
Modern data analysis requires that you have two jobs: being a statistician and being a programmer. This is especially true with R, where pointing and clicking to analyze data is mostly not an option.Fortunately, the jump from "writing code like a statistician" to "being a statistical...
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| Idioma: | Inglés |
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O'Reilly Media, Inc
2014.
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| Edición: | 1st edition |
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| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009629599406719 |
| Sumario: | Modern data analysis requires that you have two jobs: being a statistician and being a programmer. This is especially true with R, where pointing and clicking to analyze data is mostly not an option.Fortunately, the jump from "writing code like a statistician" to "being a statistical programmer" isn't that far. This webcast covers a few simple skills that will get you started, including:Writing stylish code.Finding bad functions with the sig package.Writing robust code with the assertive package.Testing your code with the testthat package.Documenting your code with the roxygen2 package. |
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| Notas: | Title from title screen (viewed February 17, 2015). Date of publication taken from resource description page. |
| Descripción Física: | 1 online resource (1 video file, approximately 59 min.) |
