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Linking Github and R Studio

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As Ferramentas do Cientista de Dados

Universidade Johns Hopkins

4.5 (21,609 classificações) | 360K alunos inscritos

Curso 1 de 5 no Data Science: Foundations using R Programa de cursos integrados

In this course you will get an introduction to the main tools and ideas in the data scientist's toolbox. The course gives an overview of the data, questions, and tools that data analysts and data scientists work with. There are two components to this course. The first is a conceptual introduction to the ideas behind turning data into actionable knowledge. The second is a practical introduction to the tools that will be used in the program like version control, markdown, git, GitHub, R, and RStudio.

Visualizar o programa do curso

Habilidades que você aprenderá

Data Science, Github, R Programming, Rstudio

Avaliações

4.5 (21,609 classificações)

5 stars
14,274 ratings
4 stars
5,484 ratings
3 stars
1,407 ratings
2 stars
283 ratings
1 star
161 ratings

AM

Jul 22, 2017

Great Primer for what Data Science is about. It also provides the infrastructure of tools needed. This was what I was after, a way to provide other data scientist hardware and infrastructure support.

WC

Sep 26, 2017

I really don't know much about this stuff, I think the jury's still out on whether the last four weeks will be helpful in the future. We'll see how much I think I've learned at the end of the course

Na lição

Version Control and GitHub

During this module, you'll learn about version control and why it's so important to data scientists. You'll also learn how to use Git and GitHub to manage version control in data science projects.

Linking Github and R Studio4:11

Ministrado por

Jeff Leek, PhD
Associate Professor, Biostatistics
Roger D. Peng, PhD
Associate Professor, Biostatistics
Brian Caffo, PhD
Professor, Biostatistics

Transcrição

Now that we have both RStudio and Git set up on your computer in a GitHub account, it's time to link them together so that you can maximize the benefits of using RStudio in your version control pipelines. To link RStudio in Git, in RStudio, go to Tools, then Global Options, then Git/SVN. Sometimes the default path to the Git executable is not correct. Confirm that git.exe resides in the directory that RStudio has specified. If not, change the directory to the correct path. Otherwise, click "Okay" or "Apply". Rstudio and Git are now linked. Now, to link RStudio to GitHub in that same RStudio option window, click "Create RSA Key" and when there is complete, click "Close". Following this, in that same window again, click "View public key" and copy the string of numbers and letters. Close this window. You have now created a key that is specific to you which we will provide to GitHub so that it knows who you are when you commit a change from within RStudio. To do so, go to github.com, log in if you are not already, and go to your account settings. There, go to SSH and GPG keys and click "New SSH key". Paste in the public key you have copied from RStudio into the key box and give it a title related to RStudio. Confirm the addition of the key with your GitHub password. GitHub and RStudio are now linked. From here, we can create a repository on GitHub and link to RStudio. To do so, go to GitHub and create a new repository by going to your Profile, Repositories and New. Name your new test repository and give it a short description. Click "Create Repository", copy the URL for your new repository. In RStudio, go to File, New Project, select Version Control, select Git as your version control software. Paste in the repository URL from before, select the location where you would like the project stored. When done, click on "Create Project". Doing so will initialize a new project linked to the GitHub repository and open a new session of RStudio. Create a new R script by going to File, New File, R Script and copy and paste the following code: print("This file was created within RStudio") and then on a new line paste, print("And now it lives on GitHub"). Save the file. Note that when you do so, the default location for the file is within the new project directory you created earlier. Once that is done, looking back at RStudio, in the Git tab of the environment quadrant, you should see your file you just created. Click the checkbox under Staged to stage your file. Click on it. A new window should open that lists all of the changed files from earlier and below that shows the differences in the stage files from previous versions. In the upper quadrant, in the.Commit message box, write yourself a commit message. Click Commit, close the window. So far, you have created a file, saved it, staged it, and committed it. If you remember your version control lecture, the next step is to push your changes to your online repository, push your changes to the GitHub repository, go to your GitHub repository and see that the commit has been recorded. You've just successfully pushed your first commit from within RStudio to GitHub. In this lesson, we linked Git and RStudio so that RStudio recognizes you are using it as your version control software. Following that, we linked RStudio to GitHub so that you can push and pull repositories from within RStudio. To test this, we created a repository on GitHub, linked it with a new project within RStudio, created a new file and then staged, committed and pushed the file to your GitHub repository.

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