![]() ![]() If you download Python from, you just get Python and The Standard Library but no additional modules. If you download Anaconda, you get Python including the Python Standard Library plus about 600 extra packages. The packages that come with Anaconda includes many of the most common Python packages use to solve problems. These additional packages are all free to install. The Anaconda distribution of Python is advantageous because it includes Python as well as about 600 additional Python packages. Anaconda includes Python plus about 600 additional Python packages However, there are a couple of advantages to using the Anaconda distribution of Python. Regardless if you download Python from or if you download Anaconda (with all the extra stuff it comes with) from, you will be able to write and execute Python code. Why download Anaconda, if I want to use is Python? The Anaconda distribution of Python also includes a program called Anaconda Navigator that allows you to launch Jupyter notebooks quickly. ![]() When you download the Anaconda distribution of Python from, you get a Python Interpreter, the Anaconda Prompt (a command line program), Spyder (a code editor) and about 600 extra Python modules that aren't included in the Python Standard Library. So Python corresponds to both the language that a program is written in as well as the application that runs the program. A program written in the Python programming language is run with the Python Interpreter. The Python Interpreter is an application or program that runs your Python code. When you download Python from, you get the Python Interpreter, a little text editing program called IDLE and all of the Python Standard Library modules. The following section details the differences between the Anaconda distribution of Python and the version of Python you can download from How is Anaconda different from Python? I recommend problem solvers install the Anaconda distribution of Python. The Anaconda Distribution of Python The Anaconda Distribution of Python Problem Solving with Python Book Construction Then I followed the directions in the documentation, which instructed me to issue the following Bash command whether I was in the Bash shell or not: $ bash Anaconda3-5.1.0-Linux-x86_64.Why download Anaconda, if I want to use is Python?Īnaconda includes Python plus about 600 additional Python packagesĪnaconda installs without administrator privilegesĪnaconda makes package management and virtual environments easier To install Anaconda on my Linux laptop (an I3 with 4GB of RAM), I downloaded the Anaconda 5.1 Linux installer and ran md5sum to verify the file: $ md5sum Anaconda3-5.1.0-Linux-x86_64.sh The documentation is incredibly detailed and there is an excellent community of users for additional support. The default environment is Python 3.6, but you can also easily install Python 3.5, Python 2.7, or R. I recommend using Anaconda Navigator, a desktop graphical user interface (GUI) system that includes links to all the applications included with the distribution including RStudio, iPython, Jupyter Notebook, JupyterLab, Spyder, Glue, and Orange. As Anaconda's website says, "The Python and R conda packages in the Anaconda Repository are curated and compiled in our secure environment so you get optimized binaries that 'just work' on your system." The distribution comes with more than 1,000 data packages as well as the Conda package and virtual environment manager, so it eliminates the need to learn to install each library independently. I appreciate that Anaconda eases the frustration of getting started for new users. It is easy to download and install, and it is supported on Linux, MacOS, and Windows. As I was trying to work through the challenges of installing data science packages like NumPy and Matplotlib and solving the various dependencies, I learned about the Anaconda Python distribution.Īnaconda is a complete, open source data science package with a community of over 6 million users. When I took Udemy courses on the R and Python programming languages, I downloaded and installed the applications independently. Like many others, I've been trying to get involved in the rapidly expanding field of data science. ![]()
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