![]() "If you also want to remove all traces of the configuration files and directories from Anaconda and its programs, you can download and use the Anaconda-Clean program first, then do a simple remove. As indicated by the guide, a deep clean requires the operations in both Option B and A. You may follow the official guide of performing a deep clean of Anaconda. The default location of the System install is C:\Program Files\Microsoft VS Code.ĭelete the directory C:\Users\username\AppData\Roaming\Codeĭelete the directory C:\Users\username\.vscode The location depends on the installer type, System or User. Run the uninstall program unins000.exe in the directory of your VS Code.The last video chapter shows how to remove VS Code from Mac. Remove Visual Studio Code and its Extensions MacOS If you have neither one previously installed, you go directly to Section 2 SET UP THE PYTHON ENVIRONMENT FOR DATA SCIENCE. Therefore the guide first shows you, in Section 1 UNINSTALL, the removal of Visual Studio Code as well as Anaconda from MacOS and Windows, respectively. Then you may follow the guide and set up a brand new environment. If you have already installed either one or both and they are not working as expected, you may perform a complete removal of them as well as configurations and libraries. We will install Visual Studio Code and Anaconda. If not, you can refer to another post and install Python first: Fully Remove Python and Install a Fresh Python in MacOS and Windows. I assume you have previously installed a standalone Python in your local computer. Conda is a package and environment management tool, which not only helps you create, load and switch between environments, but also makes it easy to find and install over 7500 packages.īefore continuing reading the post, check the following two notes:.A bundled Python3 distribution, but you can still install other versions separately from Anaconda.Both the classical Jupyter Notebook and a modern notebook interface JupyterLab support interactive development and reproducible work. ![]() The benefits of using Anaconda come from its powerful components, which includes: Specifically, you will create virtual environments with Conda manage dependencies of projects with virtual environments add a virtual environment as a Jupyter kernel and connect a notebook to a kernel in JupyterLab. You will know how to set up a Python environment where you do machine learning and data science in an interactive notebook which allows other people reproduce your work. The video can be navigated through by the video chapters, including:Īn introduction to the relevant terms in this particular setting: ![]() Anaconda offers free individual edition, which currently the easiest way to learning from data with Python. If all of the above mentioned are true, this post is a handy reference to setting up the most popular Python data science platform Anaconda in your local computer. Right now you are working on setting up a Python environment in your Mac or PC. This was done on Ubuntu 18.04 and will probably also work on MacOS.You are just getting started with Data Science, Machine Learning or Artificial Intelligence, and Python is one of the languages you have chosen. "/home/me/anaconda3/etc/profile.d/conda.sh"Įxport PATH="/home/me/anaconda3/bin:$PATH" _conda_setup="$('/home/me/anaconda3/bin/conda' 'shell.bash' 'hook' 2> /dev/null)" # !! Contents within this block are managed by 'conda init' !! Remove everything that looks like it has been added by/for anaconda: # > conda initialize > Remove the files rm -rf rm -rf ~/.anaconda_backupĭelete lines added by conda from environment file(s) Run the cleaner (base) anaconda-clean -yesĭeactivate the 'base' virtual environment (base) conda deactivate Install the cleaner conda install anaconda-cleanĪctivate the 'base' virtual environment source ~/anaconda3/bin/activate MacOS Big Sur and MacOS High Sierra differ: the anaconda folder is ~/opt/anaconda3 instead of ~/anaconda3, according to the comment by jmgonet and answer by Laknath.
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