If you download Python 2.7, our tutorial codes will not work. The Windows users can find an option in WinPython. You will be downloading the Python 3 version (any version 3.5 or later is good). Now, run the following command from the Linux terminal −Ĭanopy and ActiveState are the most sought after choices for Windows, macOS and common Linux platforms. You can choose between adding Anaconda in PATH variable and registering Anaconda as your default Python.įor installation on Linux, download installers for 32 bit and 64 bit installers from the downloads page − This tutorial demonstrates the installation for Windows. Take your first steps using Anaconda Distribution, working with conda, and writing your first Python program. The standard installation of Anaconda consists of. Anaconda Certified: Python Fundamentals for Data Analysis Learn to read, write, and solve real-life problems with Python, and build a foundation for using pandas for data analysis in Python. Installation is a fairly straightforward wizard based process. Anaconda is a distribution of Python and R for data science and scientific computing. For installation on Windows, 32 and 64 bit binaries are available − The advantage of Anaconda is that you have access to over 720 packages that can easily be installed with Anaconda's Conda, a package, dependency, and environment manager.Īnaconda distribution is available for installation at. It also easily creates, saves, loads, and switches between environments on your local computer. Conda quickly installs, runs, and updates packages and their dependencies. Package versions are managed by the package management system Conda. Conda is an open-source package and environment management system that runs on Windows, macOS, and Linux. Matplotlib and lots of other useful (data) science tools form part of the distribution. The distribution makes package management and deployment simple and easy. Anaconda is a free and open source distribution of the Python and R programming languages for large-scale data processing, predictive analytics, and scientific computing.
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