Anaconda Cheat Sheet

If you’re working with Anaconda, then you’ll want to know about some of the most important features and how to use them. This cheat sheet will help you get started. Anaconda is a distribution of Python, R, and other packages that are used for data science and machine learning.

It’s available for free from Continuum Analytics. Anaconda includes over 100 of the most popular Python packages for data science, including NumPy, pandas, matplotlib, and scikit-learn.

If you’re working with the Anaconda distribution of Python, you’ll want to keep this handy cheat sheet close by. It covers the most important topics for working with Anaconda, including managing packages, environments and channels. Package Management:

conda install [package] # install a package from Anaconda’s default channel conda install [package] -c [channel] # install a package from a specific channel conda remove [package] # remove a package

conda update [package] # update a package conda list # list all installed packages Environment Management:

conda create –name [env name] python=[python version] # create a new environment source activate [env name] # activate an environment (Mac/Linux)

Anaconda Beginners Guide for Linux and Windows – Python Working Environments Tutorial

Conda Install -C

Pypi If you’re new to Python, then the idea of installing packages can be a bit daunting. Fortunately, the Anaconda distribution makes it easy to install packages and keep them up-to-date.

In this blog post, we’ll walk through how to use the conda command to install a package from the PyPI repository. First, make sure that you have Anaconda installed on your system. Then open a terminal (or Anaconda Prompt on Windows) and type the following:

conda install -c anaconda pypi This will install the latest version of the PyPI package into your Anaconda environment. The -c option tells conda to use the anaconda channel instead of the default channel.

By default, conda will only search for packages in its own channels (e.g., https://repo.anacondaworkspaces/pkgs/main/ ). However, many popular Python packages are not available in these channels and must be installed from PyPI using pip . The -c option allows you to specify an alternate channel where conda should look for packages.

In this case we’re using anaconda , which is a channel maintained by Anaconda Workspaces that contains many popular Python packages (including those that are not available in other channels). You can find a list of all available channels at https://docs.anacondaworkspaces.com/user-guide/tasks/PackageChannels . After running the conda install command, you should see something like this:

Fetching package metadata ………Solving package specifications: ……….

Package plan for installation in environment /Users/jsmith/anaconda3: Proceed ([y]/n)? y pypi-0 100% |###############################| Time: 0:00:00 1 MB/s Installing collected packages: pypi Successfully installed pypi-0 Cleaning up…

Credit: www.youtube.com

How Can I See All Conda Environments?

Assuming you are using the Anaconda distribution, there are a few ways to see what conda environments you have installed. The first way is to use the command line. With Anaconda Prompt (or your system’s equivalent), simply type:

conda env list This will show you a list of all the environments on your system, as well as their corresponding Python versions. If you want more information about each environment, such as what packages are installed in them, you can use the ‘–verbose’ flag:

How Do I List Anaconda Packages?

If you want to list the packages in Anaconda, you can use the command line or Anaconda Navigator. To list the packages using the command line, open a terminal and type: conda list

This will print out a list of all the packages in your current environment, as well as their versions. You can also use wildcards to filter the results. For example, if you only want to see packages that start with “anaconda”, you would type:

conda list anaconda* If you want to list the packages in Anaconda Navigator, go to the Environments tab and select your current environment. This will open a new page that shows all of the installed packages in that environment.

You can also use the search bar to filter the results.

Is Pip Included in Anaconda?

No, pip is not included in Anaconda. However, Anaconda’s package manager, conda, can be used to install pip.

How Do You Clone the Environment in Anaconda?

Anaconda is a distribution of Python and R that includes over 100 popular packages for data science. It is available for free and runs on all major operating systems. Anaconda can be used to clone your environment so that you can have an identical copy of all the packages and their dependencies.

This is useful if you want to share your environment with others or if you want to create a new environment with the same packages as an existing one. To clone your environment in Anaconda, first open the Anaconda Prompt and type the following command: conda create –name myenv –clone myoldenv

Replace “myenv” with the name of your new environment and “myoldenv” with the name of the old one. This will create an exact copy of your old environment in a new one. You can then activate it by typing:

Conclusion

If you’re new to the Anaconda distribution of Python, then this cheat sheet is for you. It covers the most important aspects of getting started with Anaconda, including installing it, setting up your environment, and working with popular data science tools such as Jupyter Notebooks. Installing Anaconda is simple and only takes a few minutes.

You can download it from the official website or use a package manager like Homebrew on macOS. Once installed, you’ll need to create a new conda environment to get started. This can be done using the command line or by using the Anaconda Navigator GUI.

Once your environment is set up, you can start working with data science tools like Jupyter Notebooks. The Anaconda distribution includes many popular packages such as NumPy, pandas, and matplotlib that make working with data easier. You can also install additional packages using conda or pip.

Whether you’re just getting started with Python or are looking for a quick reference, this cheat sheet will help you get up and running with Anaconda quickly and easily.