Tutorials
Anaconda Individual Edition is the world’s most popular Python distribution platform with over 20 million users worldwide. You can trust in our long-term commitment to supporting the Anaconda open-source ecosystem, the platform of choice for Python data science. Download the installer: Miniconda installer for macOS. Anaconda installer for macOS. Verify your installer hashes. Install: Miniconda-In your terminal window, run: bash Miniconda3-latest-MacOSX-x8664. Anaconda-Double-click the.pkg file. Follow the prompts on the installer screens. If you are unsure about any setting, accept the.
This tutorial will demonstrate how you can install Anaconda, a powerful package manager, on your Mac.
- This tutorial will help you to install Anaconda for Mac OS. Anaconda is both a package manager, python distribution and is incredibly useful for data tasks as it comes bundled with many scientific packages including sci-kit learn, SciPy, Pandas and NumPy. Additionally it’s the recommended method for installing Jupyter Notebooks.
- Free download Anaconda-Navigator Anaconda-Navigator for Mac OS X. Anaconda-Navigator - Anaconda Navigator is a desktop graphical user interface included in Anaconda that allows you to launch applications and easily manage conda packages.
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
Agate
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.
1 - Open a new terminal and go to your home directory. You can do this by using the command below.
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.
There are different ways to install scikit-learn:
- Install the latest official release. Thisis the best approach for most users. It will provide a stable versionand pre-built packages are available for most platforms.
- Install the version of scikit-learn provided by youroperating system or Python distribution.This is a quick option for those who have operating systems or Pythondistributions that distribute scikit-learn.It might not provide the latest release version.
- Building the package from source. This is best for users who want thelatest-and-greatest features and aren’t afraid of runningbrand-new code. This is also needed for users who wish to contribute to theproject.
Installing the latest release¶
Operating SystemPackager
Install the 64bit version of Python 3, for instance from https://www.python.org.Install Python 3 using homebrew (
brew install python
) or by manually installing the package from https://www.python.org.Install python3 and python3-pip using the package manager of the Linux Distribution.Install conda (no administrator permission required).Then run:
In order to check your installation you can use
Note that in order to avoid potential conflicts with other packages it isstrongly recommended to use a virtual environment, e.g. python3
virtualenv
(see python3 virtualenv documentation) or conda environments.Using an isolated environment makes possible to install a specific version ofscikit-learn and its dependencies independently of any previously installedPython packages.In particular under Linux is it discouraged to install pip packages alongsidethe packages managed by the package manager of the distribution(apt, dnf, pacman…).
Note that you should always remember to activate the environment of your choiceprior to running any Python command whenever you start a new terminal session.
If you have not installed NumPy or SciPy yet, you can also install these usingconda or pip. When using pip, please ensure that binary wheels are used,and NumPy and SciPy are not recompiled from source, which can happen when usingparticular configurations of operating system and hardware (such as Linux ona Raspberry Pi).
If you must install scikit-learn and its dependencies with pip, you can installit as
scikit-learn[alldeps]
.Anaconda Download Macos Catalina
Scikit-learn plotting capabilities (i.e., functions start with “plot_”and classes end with “Display”) require Matplotlib (>= 2.1.1). For running theexamples Matplotlib >= 2.1.1 is required. A few examples requirescikit-image >= 0.13, a few examples require pandas >= 0.18.0, some examplesrequire seaborn >= 0.9.0.
Warning
Scikit-learn 0.20 was the last version to support Python 2.7 and Python 3.4.Scikit-learn 0.21 supported Python 3.5-3.7.Scikit-learn 0.22 supported Python 3.5-3.8.Scikit-learn now requires Python 3.6 or newer.
Note
For installing on PyPy, PyPy3-v5.10+, Numpy 1.14.0+, and scipy 1.1.0+are required.
Third party distributions of scikit-learn¶
Some third-party distributions provide versions ofscikit-learn integrated with their package-management systems.
These can make installation and upgrading much easier for users sincethe integration includes the ability to automatically installdependencies (numpy, scipy) that scikit-learn requires.
The following is an incomplete list of OS and python distributionsthat provide their own version of scikit-learn.
Arch Linux¶
Arch Linux’s package is provided through the official repositories as
python-scikit-learn
for Python.It can be installed by typing the following command:Debian/Ubuntu¶
Anaconda Mac Download
The Debian/Ubuntu package is splitted in three different packages called
python3-sklearn
(python modules), python3-sklearn-lib
(low-levelimplementations and bindings), python3-sklearn-doc
(documentation).Only the Python 3 version is available in the Debian Buster (the more recentDebian distribution).Packages can be installed using apt-get
:Fedora¶
The Fedora package is called
python3-scikit-learn
for the python 3 version,the only one available in Fedora30.It can be installed using dnf
:NetBSD¶
scikit-learn is available via pkgsrc-wip:
MacPorts for Mac OSX¶
The MacPorts package is named
py<XY>-scikits-learn
,where XY
denotes the Python version.It can be installed by typing the followingcommand:Canopy and Anaconda for all supported platforms¶
Canopy and Anaconda both ship a recentversion of scikit-learn, in addition to a large set of scientific pythonlibrary for Windows, Mac OSX and Linux.
Anaconda offers scikit-learn as part of its free distribution.
Intel conda channel¶
Intel maintains a dedicated conda channel that ships scikit-learn:
This version of scikit-learn comes with alternative solvers for some commonestimators. Those solvers come from the DAAL C++ library and are optimized formulti-core Intel CPUs.
Note that those solvers are not enabled by default, please refer to thedaal4py documentationfor more details.
Compatibility with the standard scikit-learn solvers is checked by running thefull scikit-learn test suite via automated continuous integration as reportedon https://github.com/IntelPython/daal4py.
WinPython for Windows¶
The WinPython project distributesscikit-learn as an additional plugin.
Troubleshooting¶
Error caused by file path length limit on Windows¶
It can happen that pip fails to install packages when reaching the default pathsize limit of Windows if Python is installed in a nested location such as the
AppData
folder structure under the user home directory, for instance:In this case it is possible to lift that limit in the Windows registry byusing the
regedit
tool:- Type “regedit” in the Windows start menu to launch
regedit
. - Go to the
ComputerHKEY_LOCAL_MACHINESYSTEMCurrentControlSetControlFileSystem
key. - Edit the value of the
LongPathsEnabled
property of that key and setit to 1. - Reinstall scikit-learn (ignoring the previous broken installation):