Audio interfaces are the heart of every digital studio. In this article, we’ll show you how to resolve audio interface issues on your Mac. Windows PC users can read more in our Resolving Audio Interface Issues on Windows 10. Whether you have no sound, the USB ports are not working, or your output device isn’t showing up, following this. RStudio 1.3.1093 for Mac is free to download from our application library. This free Mac application is a product of RStudio, Inc. This Mac download was scanned by our built-in antivirus and was rated as malware free. RStudio was developed to work on Mac OS X 10.6.0 or later. The bundle identifier for RStudio for Mac is org.rstudio.RStudio.
- Cant Download R Studio On Mac Osx Sierra 10.13
- Cant Download R Studio On Mac Osx Sierra Mac
- Cant Download R Studio On Mac Osx Sierra Version
- Cant Download R Studio On Mac Osx Sierra 10.12
Tutorials
This tutorial will demonstrate how you can install Anaconda, a powerful package manager, on your Mac.
Anaconda is a package manager, an environment manager, and Python distribution that contains a collection of many open source packages. An installation of Anaconda comes with many packages such as numpy, scikit-learn, scipy, and pandas preinstalled and is also the recommended way to install Jupyter Notebooks. This tutorial will include:
With that, let’s get started
Graphical Installation of Anaconda
Installing Anaconda using a graphical installer is probably the easiest way to install Anaconda.
1 ‒ Go to the Anaconda Website and choose a Python 3.x graphical installer (A) or a Python 2.x graphical installer (B). If you aren’t sure which Python version you want to install, choose Python 3. Do not choose both.
2 - Locate your download and double click it.
3 - Click on Continue
4 - Click on Continue
5 - Note that when you install Anaconda, it modifies your bash profile with either anaconda3 or anaconda2 depending on what Python version you choose. This can important for later. Click on Continue.
6 - Click on Continue to get the License Agreement to appear.
You will need to read and click Agree to the license agreement before clicking on Continue again.
7 - Click on Install
8 - You’ll be prompted to give your password, which is usually the one that you also use to unlock your Mac when you start it up. After you enter your password, click on Install Software.
9 - Click on Continue. You can install Microsoft Visual Studio Code if you like, but it is not required. It is an Integrated Development Environment. You can learn about Python Integrated Development Environments here.
10 - You should get a screen saying the installation has completed. Close the installer and move it to the trash.
Test your Installation
1 - Open a new terminal on your Mac. You can do this by clicking on the Spotlight magnifying glass at the top right of the screen, type “terminal” then click on the terminal icon. Now, type the following command into your terminal
If you had chosen a Python 3 version of Anaconda (like the one in the image above), you will get an output similar to above.
If you had chosen a Python 2 version of Anaconda, you should get a similar output to the one below.
2 - Another good way to test your installation is to try and open a Jupyter Notebook. You can type the command below in your terminal to open a Jupyter Notebook. If the command fails, chances are that Anaconda isn’t in your path. See the next section on Common Issues.
The image below shows a Jupyter Notebook in action. Jupyter notebooks contain both code and rich text elements, such as figures, links, and equations. You can learn more about Jupyter Notebooks here.
Common Issues
The image below shows step 5 of the Graphical Installation of Anaconda from earlier in this tutorial. Notice that when you install Anaconda, it modifies your .bash_profile to put Anaconda in your path.
The problem is that sometimes people have installed multiple different versions of Anaconda and consequently they have multiple versions of Anaconda in their path. For example, say a person needs Python 2 and they install a Python 2 version of Anaconda, That same person then finds that they need Python 3, so they install a Python 3 version of Anaconda. The problem is that you really only need 1 version of Anaconda. A lot of people think that is that if you install a Python 2 version of Anaconda, you are stuck with Python 2. Anaconda is also an environment manager and makes it very easy to go back and forth between Python 2 and 3 on a single installation of Anaconda (learn more here).
To see if you have more than 1 version of anaconda installed and to fix it if you do, let’s first look at your .bash_profile.
Cant Download R Studio On Mac Osx Sierra 10.13
1 - Open a new terminal and go to your home directory. You can do this by using the command below.
Cant Download R Studio On Mac Osx Sierra Mac
2 - Use the
cat
command to see the contents of the hidden file .bash_profile. Type the following command into your terminal.You should only see one anaconda version added to your path as you see below, this isn’t a problem for you. Move to the conclusion of the tutorial.
If you see more than one Anaconda version, proceed to step 3.
3 - To remove the old version of Anaconda from your .bash_profile use the command below to edit the file using the nano editor.
From the image above, notice there is a newer Version of Anaconda. Simply remove the older version of Anaconda. Type control + X to exit out of nano.
Save changes by typing Y.
Close that terminal and open a new one. You should be okay now. Keep in mind that this isn’t the only issue you can have when installing Anaconda, but it is a very common issue.
Conclusion
This tutorial provided a quick guide to install Anaconda on Mac as well as dealing with a common installation issue. A graphical install of Anaconda isn’t the only way to install Anaconda as you can Install Anaconda by a Command Line Installer, but it is the easiest. If you aren’t sure what to do after installing Anaconda, here are a few things you can do:
- If you would like to learn more about Anaconda, you can learn about more here.
- If you want to start coding on your local computer, you can check out the the Jupyter Notebook Definitive Guide to learn how to code in Jupyter Notebooks.
- If you want to learn Python, you can check out DataCamp's Intro to Python for Data Science course.
If you any questions or thoughts on the tutorial, feel free to reach out in the comments below or through Twitter.
- Install R and RStudio on windows
Cant Download R Studio On Mac Osx Sierra Version
In our previous article, we described what is R and why you should learn R. In this article, we’ll describe briefly how to install R and RStudio on Windows, MAC OSX and Linux platforms. RStudio is an integrated development environment for R that makes using R easier. It includes a console, code editor and tools for plotting.
To make things simple, we recommend to install first R and then RStudio.
- R can be downloaded and installed on Windows, MAC OSX and Linux platforms from the Comprehensive R Archive Network (CRAN) webpage (http://cran.r-project.org/).
- After installing R software, install also the RStudio software available at: http://www.rstudio.com/products/RStudio/.
Install R for windows
- Download the latest version of R, for Windows, from CRAN at : https://cran.r-project.org/bin/windows/base/
- Double-click on the file you just downloaded to install R
- Cick ok –> Next –> Next –> Next …. (no need to change default installation parameters)
Install Rtools for Windows
Rtools contains tools to build your own packages on Windows, or to build R itself.
- Download Rtools version corresponding to your R version at: https://cran.r-project.org/bin/windows/Rtools/. Use the latest release of Rtools with the latest release of R.
- Double-click on the file you just downloaded to install Rtools (no need to change default installation parameters)
Install RStudio on Windows
- Download RStudio at : https://www.rstudio.com/products/rstudio/download/
- Download the latest version of R, for MAC OSX, from CRAN at : https://cran.r-project.org/bin/macosx/
- Double-click on the file you just downloaded to install R
- Cick ok –> Next –> Next –> Next …. (no need to change default installation parameters)
- Download and install the latest version of RStudio for MAC at: https://www.rstudio.com/products/rstudio/download/
- R can be installed on Ubuntu, using the following Bash script:
sudo apt-get install r-base
- RStudio for Linux is available at https://www.rstudio.com/products/rstudio/download/
To install the latest version of R for linux, read this: Installing R on Ubuntu
It is relatively simple to install R, but if you need further help you can try the following resources:
- Previous chapters
- Next chapters
This analysis has been performed using R software (ver. 3.2.3).
Enjoyed this article? I’d be very grateful if you’d help it spread by emailing it to a friend, or sharing it on Twitter, Facebook or Linked In.
Show me some love with the like buttons below... Thank you and please don't forget to share and comment below!!
Show me some love with the like buttons below... Thank you and please don't forget to share and comment below!!
Avez vous aimé cet article? Je vous serais très reconnaissant si vous aidiez à sa diffusion en l'envoyant par courriel à un ami ou en le partageant sur Twitter, Facebook ou Linked In.
Montrez-moi un peu d'amour avec les like ci-dessous ... Merci et n'oubliez pas, s'il vous plaît, de partager et de commenter ci-dessous!
Montrez-moi un peu d'amour avec les like ci-dessous ... Merci et n'oubliez pas, s'il vous plaît, de partager et de commenter ci-dessous!
Cant Download R Studio On Mac Osx Sierra 10.12
Recommended for You!
More books on R and data science
Recommended for you
This section contains best data science and self-development resources to help you on your path.
Coursera - Online Courses and Specialization
Data science
- Course: Machine Learning: Master the Fundamentals by Standford
- Specialization: Data Science by Johns Hopkins University
- Specialization: Python for Everybody by University of Michigan
- Courses: Build Skills for a Top Job in any Industry by Coursera
- Specialization: Master Machine Learning Fundamentals by University of Washington
- Specialization: Statistics with R by Duke University
- Specialization: Software Development in R by Johns Hopkins University
- Specialization: Genomic Data Science by Johns Hopkins University
Popular Courses Launched in 2020
- Google IT Automation with Python by Google
- AI for Medicine by deeplearning.ai
- Epidemiology in Public Health Practice by Johns Hopkins University
- AWS Fundamentals by Amazon Web Services
Trending Courses
- The Science of Well-Being by Yale University
- Google IT Support Professional by Google
- Python for Everybody by University of Michigan
- IBM Data Science Professional Certificate by IBM
- Business Foundations by University of Pennsylvania
- Introduction to Psychology by Yale University
- Excel Skills for Business by Macquarie University
- Psychological First Aid by Johns Hopkins University
- Graphic Design by Cal Arts
Books - Data Science
Our Books
- Practical Guide to Cluster Analysis in R by A. Kassambara (Datanovia)
- Practical Guide To Principal Component Methods in R by A. Kassambara (Datanovia)
- Machine Learning Essentials: Practical Guide in R by A. Kassambara (Datanovia)
- R Graphics Essentials for Great Data Visualization by A. Kassambara (Datanovia)
- GGPlot2 Essentials for Great Data Visualization in R by A. Kassambara (Datanovia)
- Network Analysis and Visualization in R by A. Kassambara (Datanovia)
- Practical Statistics in R for Comparing Groups: Numerical Variables by A. Kassambara (Datanovia)
- Inter-Rater Reliability Essentials: Practical Guide in R by A. Kassambara (Datanovia)
Others
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham & Garrett Grolemund
- Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems by Aurelien Géron
- Practical Statistics for Data Scientists: 50 Essential Concepts by Peter Bruce & Andrew Bruce
- Hands-On Programming with R: Write Your Own Functions And Simulations by Garrett Grolemund & Hadley Wickham
- An Introduction to Statistical Learning: with Applications in R by Gareth James et al.
- Deep Learning with R by François Chollet & J.J. Allaire
- Deep Learning with Python by François Chollet
Want to Learn More on R Programming and Data Science?
Follow us by EmailOn Social Networks:
Get involved :
Click to follow us on Facebook and Google+ :
Comment this article by clicking on 'Discussion' button (top-right position of this page)
Click to follow us on Facebook and Google+ :
Comment this article by clicking on 'Discussion' button (top-right position of this page)