Anaconda is the leading open data science platform powered by Python. The
open source version of Anaconda is a high performance distribution of Python
and R and includes over 100 of the most popular Python, R and Scala packages
for data science.
Additionally, you'll have access to over 720 packages that can easily be
installed with conda, our renowned package, dependency and environment manager,
that is included in Anaconda. See the
packages
included with Anaconda and the Anaconda
changelog
1.What is the Jupyter Notebook?
In this page briefly introduce the
main components of the Jupyter Notebook environment. For a more complete
overview see References.
1.1.
Notebook document
Notebook documents (or “notebooks”, all lower case) are documents produced
by the
Jupyter Notebook App, which contain both computer code
(e.g. python) and rich text elements (paragraph, equations, figures, links,
etc...). Notebook documents are both human-readable documents containing the
analysis description and the results (figures, tables, etc..) as well as
executable documents which can be run to perform data analysis.
1.2. Jupyter Notebook App
The
Jupyter Notebook App is a server-client application that allows
editing and running
notebook documents via a web browser. The
Jupyter
Notebook App can be executed on a local desktop requiring no internet
access (as described in this document) or can be installed on a remote server
and accessed through the internet.
In addition to displaying/editing/running notebook documents, the
Jupyter
Notebook App has a “Dashboard” (
Notebook Dashboard), a “control panel” showing local files
and allowing to open notebook documents or shutting down their
kernels.
1.3. kernel
A notebook
kernel is a “computational engine” that executes the
code contained in a
Notebook document. The
ipython kernel, referenced
in this guide, executes python code. Kernels for many other languages exist (
official
kernels).
When you open a
Notebook document, the associated
kernel is
automatically launched. When the notebook is
executed (either
cell-by-cell or with menu
Cell -> Run All), the
kernel
performs the computation and produces the results. Depending on the type of
computations, the
kernel may consume significant CPU and RAM. Note
that the RAM is not released until the
kernel is shut-down.
1.4. Notebook Dashboard
The
Notebook Dashboard is the component which is shown first when
you launch
Jupyter Notebook App. The
Notebook Dashboard is
mainly used to open
notebook documents, and to manage the running
kernels (visualize and shutdown).
The
Notebook Dashboard has other features similar to a file
manager, namely navigating folders and renaming/deleting files.
2. Installation
2.1. Step 0: The browser
Step “zero” consists in installing a modern standard-compliant browser.
Either Mozilla Firefox or Google Chrome will work well. Try to avoid MS
Explorer.
2.2. Step 1: Installation
The easiest way to install the
Jupyter Notebook App consists in
installing a scientific python distribution which includes it. In this guide,
we will use the Anaconda distribution created by Continuum. Note that Anaconda
currently (mid 2015) still uses the old name
IPython Notebook instead
of
Jupyter Notebook App but the software is the same.
- Download Continuum Anaconda
(free version, approx. 400MB), python 3, 64 bits.
- Install it
using the default settings for a single user.
3. Running the Jupyter Notebook
3.1. Launching Jupyter Notebook App
The
Jupyter Notebook App can be launched by clicking on the
Jupyter
Notebook icon installed by Anaconda in the start menu (Windows) or
by typing in a terminal (
cmd on Windows):
jupyter notebook
This will launch a new browser window (or a new tab) showing the
Notebook Dashboard, a sort of control panel that allows
(among other things) to select which notebook to open.
When started, the
Jupyter Notebook App can access only files within its
start-up folder (including any sub-folder). If you store the notebook documents
in a subfolder of your user folder no configuration is necessary. Otherwise,
you need to choose a folder which will contain all the notebooks and set this
as the
Jupyter Notebook App start-up folder.
See below for platform-specific instructions on how to start
Jupyter Notebook App in a specific folder.
3.1.1. Change Jupyter Notebook startup folder (Windows)
- Copy the Jupyter Notebook launcher from
the menu to the desktop.
- Right
click on the new launcher and change the “Start in” field by pasting the
full path of the folder which will contain all the notebooks.
- Double-click
on the Jupyter Notebook desktop
launcher (icon shows [IPy]) to start the Jupyter Notebook App, which will open in a new
browser window (or tab). Note also that a secondary terminal window (used
only for error logging and for shut down) will be also opened. If only the
terminal starts, try opening this address with your browser: http://localhost:8888/.
3.1.2. Change Jupyter Notebook startup folder (OS X)
To launch
Jupyter Notebook App:
- Click on
spotlight, type terminal to open a terminal window.
- Enter the
startup folder by typing cd
/some_folder_name.
- Type jupyter
notebook to launch the Jupyter Notebook App (it will appear in a new browser
window or tab).
3.2. Shut down the Jupyter Notebook App
In a nutshell, closing the browser (or the tab)
will not close
the
Jupyter Notebook App. To completely shut it down you need
to
close the associated terminal.
In more detail, the
Jupyter Notebook App is a server that appears in your
browser at a default address (
http://localhost:8888). Closing
the browser will not shut down the server. You can reopen the previous address
and the
Jupyter Notebook App will be redisplayed.
You can run many copies of the
Jupyter Notebook App and they will show up at a similar
address (only the number after ”:”, which is the port, will increment for each
new copy). Since with a single
Jupyter Notebook App you can already open many notebooks,
we do not recommend running multiple copies of
Jupyter Notebook App.
3.3. Close a notebook: kernel shut down
When a notebook is opened, its “computational engine” (called the
kernel) is automatically started. Closing the notebook
browser tab, will not shut down the
kernel, instead the kernel will keep running until is
explicitly shut down.
To shut down a kernel, go to the associated notebook and click on menu
File
->
Close and Halt. Alternatively, the
Notebook Dashboard has a tab named
Running
that shows all the running notebooks (i.e. kernels) and allows shutting them
down (by clicking on a
Shutdown button).
3.4. Executing a notebook
Download the notebook you want to execute and put it in your notebook folder
(or a sub-folder of it).
Then follow these steps:
- Launch the
Jupyter Notebook App (see previous section).
- In the Notebook Dashboard navigate to find the notebook:
clicking on its name will open it in a new browser tab.
- Click on
the menu Help -> User Interface Tour
for an overview of the Jupyter Notebook App user interface.
- You can
run the notebook document step-by-step (one cell a time) by pressing shift + enter.
- You can
run the whole notebook in a single step by clicking on the menu Cell -> Run All.
- To restart
the kernel (i.e. the computational engine), click on the
menu Kernel -> Restart. This can
be useful to start over a computation from scratch (e.g. variables are
deleted, open files are closed, etc...).
More information on editing a notebook:
