#Canopy install jupyter notebook download#
Image 1 | Anaconda for Python 3 Download Link Īs you can see in Image 1, this is a large file (500+ MB) so it will take sometime to download, depending upon your internet connection speed. Another important thing to note is the variety of available packages: > Anaconda 2 (Download only if you are intending to use Python ? 2.7 ), and > Anaconda for Python 3 (Recommended (Allows creating virtual environments to use Python 2, if required). For this process, you need to be aware of 2 critical pieces of information about the Operating System on our computer: > Type (Windows/Macintosh/Linux), and > Architecture(32/64 bit). Once you have a clean system, the next step is to download Anaconda distribution (as this is a guide for beginners, we will avoid Miniconda). Also, you must ensure that these Python IDEs don?t have their PATH added in Environment Variables.
The first task (for beginners and near beginners) will be to ensure that you properly uninstall any other Python IDEs (like P圜harm, Python IDLE, etc.) that may be on your computer (see the link at the end of this article for a guide to uninstalling). We will focus on getting Jupyter Notebook up and running through Anaconda Distribution from Continuum Analytics.
The linked caption above directs to the Jupyter official webpage, which has an exhaustive step-by-step guide to installation. Jupyter/IPython Notebook Official Quick Start Guide Setting up Anaconda Distribution Jupyter Notebook can also be run without any installation. It also has a Dashboard (Notebook Dashboard) and a control panel, displaying local files and allowing you to open notebook documents or shut down their kernels. A server-client application that allows editing and running notebook documents via the web browser of our choice, it can be executed on a local desktop requiring no internet access, or installed on a remote server and accessed through the internet. If you run into any problems, double check that you have installed both the upgraded version of PySAL and folium (see above).Jupyter Notebook (formerly, IPython Notebook) is an application, widely used in the Data Science domain, for creating and sharing documents that contain Live code, Equations, Visualizations, and Explanatory text. In the second cell in the notebook enter.Then (i.e., hit the Shift then the Enter Key) In the first cell in the notebook enter.Once you have installed all the dependencies, you can check to confirm everything is ready to go. From the menu select Tools Canopy Terminal.Upgrading in Canopy can be done as follows: For this course we will be using PySAL 1.10. Note that the Academic version of Canopy comes with PySAL version 1.7. Source deactivate PySAL via Enthought Canopy When you are done working in this environment, you can get back to your default environment with: conda create -n pysal110 scipy matplotlib jupyter ipython pandas ipywidgets.If you already have Anaconda installed and you did not want to modify your default environment, you can create a custom conda environment for this session using the following commands: Open a terminal (Mac or Linux) or Powershell (Windows).Both of these distributions also allow for installation of additional dependencies. Moreover, both allow for updating PySAL to the most recent release (1.10 released July 31, 2015) which is more current that what is listed in either distribution.
These have the advantages of including most of the dependencies for PySAL as well as PySAL itself. For the course, if you do not yet have the dependencies installed we suggest using one of two scientific Python distributions (below).
There are a number of ways to install PySAL and these dependencies. For the course we will require the following packages be installed
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