A brief tour of the IPython notebook

This document will give you a brief tour of the capabilities of the IPython notebook.
You can view its contents by scrolling around, or execute each cell by typing Shift-Enter. After you conclude this brief high-level tour, you should read the accompanying notebook titled 01_notebook_introduction, which takes a more step-by-step approach to the features of the system.

The rest of the notebooks in this directory illustrate various other aspects and capabilities of the IPython notebook; some of them may require additional libraries to be executed.

NOTE: This notebook must be run from its own directory, so you must cd to this directory and then start the notebook, but do not use the --notebook-dir option to run it from another location.

The first thing you need to know is that you are still controlling the same old IPython you're used to, so things like shell aliases and magic commands still work:



In [1]:

    
pwd









    Out[1]:





u'/media/datos/Desarrollos/wakari/examples'



In [2]:

    
ls









    



00_notebook_tour.ipynb          nba_analysis.py      python-logo.svg
01_notebook_introduction.ipynb  nfl_analysis.py      uefa_2012_analysis.py
auto-mpg.csv                    nhl_analysis.py      weather_station.py
ising_model.py                  numba_mandelblot.py  webplot_example.py
logo.png                        pairs_plotting.py
mlb_analysis.py                 pandas_example.py



In [3]:

    
message = 'The IPython notebook is great!'
# note: the echo command does not run on Windows, it's a unix command.
!echo $message









    



The IPython notebook is great!

Plots with matplotlib: do not execute the next below if you do not have matplotlib installed or didn't call the %matplolib magic, as the code will not work.



In [4]:

    
%matplotlib inline



In [5]:

    
import matplotlib.pyplot as plt
import numpy as np

x = np.linspace(0, 3*np.pi, 500)
plt.plot(x, np.sin(x**2))
plt.title('A simple chirp');

You can paste blocks of input with prompt markers, such as those from the official Python tutorial



In [6]:

    
>>> the_world_is_flat = 1
>>> if the_world_is_flat:
...     print "Be careful not to fall off!"









    



Be careful not to fall off!

Errors are shown in informative ways:



In [7]:

    
%run non_existent_file









    



ERROR: File `u'non_existent_file.py'` not found.



In [8]:

    
x = 1
y = 4
z = y/(1-x)









    



---------------------------------------------------------------------------
ZeroDivisionError                         Traceback (most recent call last)
<ipython-input-8-dc39888fd1d2> in <module>()
      1 x = 1
      2 y = 4
----> 3 z = y/(1-x)

ZeroDivisionError: integer division or modulo by zero

When IPython needs to display additional information (such as providing details on an object via x? it will automatically invoke a pager at the bottom of the screen:



In [9]:

    
magic

Non-blocking output of kernel

If you execute the next cell, you will see the output arriving as it is generated, not all at the end.



In [10]:

    
import time, sys
for i in range(8):
    print i,
    time.sleep(0.5)









    



0 1 2 3 4 5 6 7

Clean crash and restart

We call the low-level system libc.time routine with the wrong argument via ctypes to segfault the Python interpreter:



In [ ]:

    
from ctypes import CDLL
# This will crash a linux system; equivalent calls can be made on Windows or Mac
libc = CDLL("libc.so.6") 
libc.time(-1)  # BOOM!!

Markdown cells can contain formatted text and code

You can italicize, boldface

build
lists

and embed code meant for illustration instead of execution in Python:

def f(x):
    """a docstring"""
    return x**2

or other languages:

if (i=0; i<n; i++) {
  printf("hello %d\n", i);
  x += 4;
}

Courtesy of MathJax, you can include mathematical expressions both inline: $e^{i\pi} + 1 = 0$ and displayed:

$$e^x=\sum_{i=0}^\infty \frac{1}{i!}x^i$$

Rich displays: include anyting a browser can show

Note that we have an actual protocol for this, see the display_protocol notebook for further details.

Images



In [11]:

    
from IPython.core.display import Image
Image(filename='logo.png')









    Out[11]:

An image can also be displayed from raw data or a url



In [12]:

    
Image('http://python.org/static/img/python-logo-large.png')









    Out[12]:

SVG images are also supported out of the box (since modern browsers do a good job of rendering them):



In [13]:

    
from IPython.core.display import SVG
SVG(filename='python-logo.svg')









    Out[13]:

Video

And more exotic objects can also be displayed, as long as their representation supports the IPython display protocol.

For example, videos hosted externally on YouTube are easy to load (and writing a similar wrapper for other hosted content is trivial):



In [1]:

    
from IPython.lib.display import YouTubeVideo
# a talk about IPython at Sage Days at U. Washington, Seattle.
# Video credit: William Stein.
YouTubeVideo('1j_HxD4iLn8')









    Out[1]:

External sites

You can even embed an entire page from another site in an iframe; for example this is today's Wikipedia page for mobile users:



In [15]:

    
from IPython.core.display import HTML
HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350>')









    Out[15]:

Mathematics

And we also support the display of mathematical expressions typeset in LaTeX, which is rendered in the browser thanks to the MathJax library.

Note that this is different from the above examples. Above we were typing mathematical expressions in Markdown cells (along with normal text) and letting the browser render them; now we are displaying the output of a Python computation as a LaTeX expression wrapped by the Math() object so the browser renders it:



In [16]:

    
from IPython.core.display import Math
Math(r'$F(k) = \int_{-\infty}^{\infty} f(x) e^{2\pi i k} dx$')









    Out[16]:





$$F(k) = \int_{-\infty}^{\infty} f(x) e^{2\pi i k} dx$$

Loading external codes

Drag and drop a .py in the dashboard
Use %loadpy with any local or remote url: the Matplotlib Gallery!

In this notebook we've kept the output saved so you can see the result, but you should run the next cell yourself (with an active internet connection).



In [17]:

    
%loadpy http://matplotlib.sourceforge.net/mpl_examples/pylab_examples/integral_demo.py



In [18]:

    
#!/usr/bin/env python

# implement the example graphs/integral from pyx
from pylab import *
from matplotlib.patches import Polygon

def func(x):
    return (x-3)*(x-5)*(x-7)+85

ax = subplot(111)

a, b = 2, 9 # integral area
x = arange(0, 10, 0.01)
y = func(x)
plot(x, y, linewidth=1)

# make the shaded region
ix = arange(a, b, 0.01)
iy = func(ix)
verts = [(a,0)] + list(zip(ix,iy)) + [(b,0)]
poly = Polygon(verts, facecolor='0.8', edgecolor='k')
ax.add_patch(poly)

text(0.5 * (a + b), 30,
     r"$\int_a^b f(x)\mathrm{d}x$", horizontalalignment='center',
     fontsize=20)

axis([0,10, 0, 180])
figtext(0.9, 0.05, 'x')
figtext(0.1, 0.9, 'y')
ax.set_xticks((a,b))
ax.set_xticklabels(('a','b'))
ax.set_yticks([])
show()