Now you can use P圜harm to create python files in your project folder, just by right-clicking on the folder overview and adding new python files. P圜harm should now set the created environment as your project interpreter. Now press “OK” for all three open windows. Here you have to navigate to the created environment for example /Users//anaconda/envs/TestEnv/bin/python3. Here select “Virtual Environment” then click on “Existing environment” then click on the icon containing “…”. When P圜harm is opened you should see something like the image below.Ī new window will open. I use Dropbox a lot, therefore, all my local project folders are created in the path /Users//Dropbox/project_folders/.Ĭreate a project folder, for example, named ProjectTestEnv. You can create the folder anywhere you want on your machine. Here I assume you have installed P圜harm.įirst, we want to create a folder which will be our project folder. Now we want to use P圜harm to create a project and execute Python code using the created environment. Now you have installed Anaconda and created an environment. If the libraries are correctly installed you should not get any errors. >import numpy >import pandas >import sklearn >import matplotlib pythonĪfter the Python console is up and running execute the following and press enter for each of the four libraries. This is accomplished by executing the following. When the libraries are installed you can check that everything is ok by starting a Python console. In terms of getting started with learning Machine Learning, these four libraries should get you a long way. This should install the four libraries numpy, pandas, scikit-learn and matplotlib. conda install numpy pandas scikit-learn matplotlib In order to do that execute the following command. Next, we want to install four third-party Python libraries. To activate the created environment execute the following command. conda create -name TestEnv python=3īefore we can install any new python libraries into the new environment we need to activate the environment. In order to create a new environment execute the following command. Otherwise, navigate to your install location. Remember this will only work if you have installed Anaconda in the default directory. So if you want to go ahead and cd into the envs folder. I always cd to the envs folder before creating a new environment. The default path to the Envs folder where all your created environments will be placed is /Users//anaconda/envs/. If you see something similar the below image then you have succesbully install Anaconda and Conda CLI. Using the Conda CLI to create an environmentĪfter installing Anaconda open a terminal window, type conda and pres enter. Follow the on-screen instructions when installing the software, then everything should be good. I recommend installing the community edition of P圜harm, as it is free.Īs for Anaconda installation, the same applies to Pycharm installation. There is nothing special about the installation, therefore, if you follow the on-screen installation instruction everything should be good. I have provided a link for each libraries documentation if you are interested in reading more.Īnaconda can be downloaded from here. The following Python libraries are of interest. The following software will be installed. Having basic knowledge of bash commands or command line (depends on the operating system, Mac or Windows).Requirements - You should be familiar with the following topics: I myself use both so no preference there. This article is focused on Mac users, however, don’t panic, I will make short comments on how to achieve the same results on Windows. In this article, I will explain and show how I use Python with Anaconda and P圜harm to set up a python data science environments ready for local experimentation with the most popular Python libraries for Machine Learning / Data Science. Originally published at Find the updated version of this post on my blog
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