print "Hallo Welt!"
Hallo Welt!
2**200
1606938044258990275541962092341162602522202993782792835301376L
# Multi-line editing. Syntax-coloring.
for num in ['eins', 'zwei', 'drei']:
print "Line %s" % num
Line eins Line zwei Line drei
Normaler Text in ganzen Sätzen. Formatiert als Markdown: hervorgehoben fett
s="hallo welt"
#s?
#s.encode(
s.encode("base64")
'aGFsbG8gd2VsdA==\n'
Abspeichern als JSON, wieder einladen
!ls -l
insgesamt 10272 -rw-rw-rw- 1 dloss dloss 302868 Mai 2 14:41 Bitcoin.ipynb -rw-rw-rw- 1 dloss dloss 1147 Mai 2 14:37 bitcoin_weighted_prices.json drwxrwxr-x 2 dloss dloss 4096 Apr 29 18:42 bundesliga -rw-rw-rw- 1 dloss dloss 119335 Apr 7 16:37 bundesliga.ipynb -rw-rw-r-- 1 dloss dloss 408138 Mai 2 16:28 Chapter1_Introduction.ipynb drwxrwxr-x 7 dloss dloss 12288 Apr 29 18:42 crosscompute-tutorials drwxrwxrwx 3 dloss dloss 4096 Mai 1 17:46 datasets -rw-rw-rw- 1 dloss dloss 2353817 Mai 3 09:54 datenanalyse-ipython-pandas.pdf -rw-rw-rw- 1 dloss dloss 2727936 Mai 2 15:30 datenanalyse-ipython-pandas.ppt -rw-rw-rw- 1 dloss dloss 792146 Apr 7 17:00 E1_BEZIRK_201112.csv -rw-rw-rw- 1 dloss dloss 225923 Nov 24 20:17 ergebnisse-1963-2010.zip -rw-r--r-- 1 dloss dloss 2048 Mai 2 15:38 foo.db -rw-rw-rw- 1 dloss dloss 2037 Apr 20 12:59 genua-vortrag.txt drwxrwxrwx 4 dloss dloss 4096 Mai 1 17:03 hpf -rw-rw-rw- 1 dloss dloss 326577 Mai 2 13:58 hpf-admin.ipynb -rw-rw-rw- 1 dloss dloss 148820 Mai 2 15:41 IPython-Demo.ipynb -rw-rw-r-- 1 dloss dloss 27092 Mai 1 16:35 ipy.vim -rw-rw-r-- 1 dloss dloss 217 Mai 3 10:14 links.txt -rw-rw-rw- 1 dloss dloss 861410 Apr 27 21:29 mtgox.csv -rw-rw-rw- 1 dloss dloss 861218 Mai 2 16:33 mtgoxUSD.csv -rw-rw-rw- 1 dloss dloss 167366 Apr 7 18:28 Muenchen.ipynb -rw-rw-r-- 1 dloss dloss 21907 Mai 2 16:23 mypicture.pdf drwxrwxr-x 6 dloss dloss 4096 Mai 1 13:25 notebooks -rw-rw-rw- 1 dloss dloss 355731 Mai 2 15:37 OpenBSD.ipynb drwxrwxr-x 11 dloss dloss 4096 Mai 2 10:59 other -rw-rw-rw- 1 dloss dloss 54449 Mär 28 21:00 pandas_basics.ipynb -rw-rw-rw- 1 dloss dloss 84604 Mär 30 21:11 Pandas Cookbook.ipynb drwxrwxr-x 3 dloss dloss 4096 Apr 29 18:49 pandas-demo drwxrwxr-x 3 dloss dloss 4096 Apr 29 18:53 pcap -rw-rw-rw- 1 dloss dloss 31161 Mai 2 13:02 pcap.ipynb -rw-rw-rw- 1 dloss dloss 26785 Mai 1 13:01 Pi.ipynb -rw-rw-rw- 1 dloss dloss 191731 Apr 28 22:17 python-slices.graffle -rw-rw-r-- 1 dloss dloss 76393 Mai 1 16:30 stock_data.csv drwxrwxr-x 3 dloss dloss 12288 Apr 29 18:42 tippkick -rw-rw-r-- 1 dloss dloss 7943 Mai 1 16:30 tips.csv drwxr-xr-x 7 dloss dloss 4096 Apr 30 23:08 tutorials -rw-rw-r-- 1 dloss dloss 2267 Mai 2 16:12 Vortrag.ipynb
!head -20 IPython-Demo.ipynb
{ "metadata": { "name": "IPython-Demo" }, "nbformat": 3, "nbformat_minor": 0, "worksheets": [ { "cells": [ { "cell_type": "code", "collapsed": false, "input": [ "print \"Hallo Welt!\"" ], "language": "python", "metadata": {}, "outputs": [ { "output_type": "stream",
Python-Variablen übergeben
interface="eth0"
data = !ifconfig $interface
data.fields()
[['/bin/sh:', '1:', 'ifconfig:', 'not', 'found']]
# Interrupt with CTRL-m i
!ping -c 6 8.8.8.8
PING 8.8.8.8 (8.8.8.8) 56(84) bytes of data. From 192.168.253.1 icmp_seq=1 Destination Port Unreachable From 192.168.253.1 icmp_seq=2 Destination Port Unreachable From 192.168.253.1 icmp_seq=3 Destination Port Unreachable From 192.168.253.1 icmp_seq=4 Destination Port Unreachable From 192.168.253.1 icmp_seq=5 Destination Port Unreachable From 192.168.253.1 icmp_seq=6 Destination Port Unreachable --- 8.8.8.8 ping statistics --- 6 packets transmitted, 0 received, +6 errors, 100% packet loss, time 5001ms
%%ruby
name = "Ruby"
3.times { puts "Hallo #{ name }" }
Hallo Ruby Hallo Ruby Hallo Ruby
%%perl
# https://github.com/peelle/Perl-Euler-Solutions/blob/master/1/solution.pl
# Straight forward iteration over each number
my $sum_of_multiples = 0;
foreach my $number ( 1..999 ) {
# using modulus to filter
next if ( $number % 3 and $number % 5 );
$sum_of_multiples += $number;
}
print $sum_of_multiples;
233168
%%bash --out output --err error
echo "Zeilen:"
for i in a b c d; do echo $i; done
Stdout wurde an output übergeben:
print output
Zeilen: a b c d
%%script lua
function allwords ()
local line = "Hallo Lua program"
local pos = 1 -- current position in the line
return function () -- iterator function
while line do -- repeat while there are lines
local s, e = string.find(line, "%w+", pos)
if s then -- found a word?
pos = e + 1 -- next position is after this word
return string.sub(line, s, e) -- return the word
else
line = io.read() -- word not found; try next line
pos = 1 -- restart from first position
end
end
return nil -- no more lines: end of traversal
end
end
-- use example
for word in allwords() do
print(word)
end
Hallo Lua program
%pylab inline
Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline]. For more information, type 'help(pylab)'.
x = np.random.normal(size=1000)
y = np.random.normal(size=1000)
scatter(x, y, alpha=0.2)
savefig("mypicture.pdf")
x = np.linspace(1, 18, 100)
y = x[:, np.newaxis]
im = y * np.sin(x)
plt.imshow(im, cmap=matplotlib.cm.gray)
<matplotlib.image.AxesImage at 0x2c99850>
%load http://matplotlib.org/mpl_examples/api/radar_chart.py
"""
Example of creating a radar chart (a.k.a. a spider or star chart) [1]_.
Although this example allows a frame of either 'circle' or 'polygon', polygon
frames don't have proper gridlines (the lines are circles instead of polygons).
It's possible to get a polygon grid by setting GRIDLINE_INTERPOLATION_STEPS in
matplotlib.axis to the desired number of vertices, but the orientation of the
polygon is not aligned with the radial axes.
.. [1] http://en.wikipedia.org/wiki/Radar_chart
"""
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.path import Path
from matplotlib.spines import Spine
from matplotlib.projections.polar import PolarAxes
from matplotlib.projections import register_projection
def radar_factory(num_vars, frame='circle'):
"""Create a radar chart with `num_vars` axes.
This function creates a RadarAxes projection and registers it.
Parameters
----------
num_vars : int
Number of variables for radar chart.
frame : {'circle' | 'polygon'}
Shape of frame surrounding axes.
"""
# calculate evenly-spaced axis angles
theta = 2*np.pi * np.linspace(0, 1-1./num_vars, num_vars)
# rotate theta such that the first axis is at the top
theta += np.pi/2
def draw_poly_patch(self):
verts = unit_poly_verts(theta)
return plt.Polygon(verts, closed=True, edgecolor='k')
def draw_circle_patch(self):
# unit circle centered on (0.5, 0.5)
return plt.Circle((0.5, 0.5), 0.5)
patch_dict = {'polygon': draw_poly_patch, 'circle': draw_circle_patch}
if frame not in patch_dict:
raise ValueError('unknown value for `frame`: %s' % frame)
class RadarAxes(PolarAxes):
name = 'radar'
# use 1 line segment to connect specified points
RESOLUTION = 1
# define draw_frame method
draw_patch = patch_dict[frame]
def fill(self, *args, **kwargs):
"""Override fill so that line is closed by default"""
closed = kwargs.pop('closed', True)
return super(RadarAxes, self).fill(closed=closed, *args, **kwargs)
def plot(self, *args, **kwargs):
"""Override plot so that line is closed by default"""
lines = super(RadarAxes, self).plot(*args, **kwargs)
for line in lines:
self._close_line(line)
def _close_line(self, line):
x, y = line.get_data()
# FIXME: markers at x[0], y[0] get doubled-up
if x[0] != x[-1]:
x = np.concatenate((x, [x[0]]))
y = np.concatenate((y, [y[0]]))
line.set_data(x, y)
def set_varlabels(self, labels):
self.set_thetagrids(theta * 180/np.pi, labels)
def _gen_axes_patch(self):
return self.draw_patch()
def _gen_axes_spines(self):
if frame == 'circle':
return PolarAxes._gen_axes_spines(self)
# The following is a hack to get the spines (i.e. the axes frame)
# to draw correctly for a polygon frame.
# spine_type must be 'left', 'right', 'top', 'bottom', or `circle`.
spine_type = 'circle'
verts = unit_poly_verts(theta)
# close off polygon by repeating first vertex
verts.append(verts[0])
path = Path(verts)
spine = Spine(self, spine_type, path)
spine.set_transform(self.transAxes)
return {'polar': spine}
register_projection(RadarAxes)
return theta
def unit_poly_verts(theta):
"""Return vertices of polygon for subplot axes.
This polygon is circumscribed by a unit circle centered at (0.5, 0.5)
"""
x0, y0, r = [0.5] * 3
verts = [(r*np.cos(t) + x0, r*np.sin(t) + y0) for t in theta]
return verts
def example_data():
#The following data is from the Denver Aerosol Sources and Health study.
#See doi:10.1016/j.atmosenv.2008.12.017
#
#The data are pollution source profile estimates for five modeled pollution
#sources (e.g., cars, wood-burning, etc) that emit 7-9 chemical species.
#The radar charts are experimented with here to see if we can nicely
#visualize how the modeled source profiles change across four scenarios:
# 1) No gas-phase species present, just seven particulate counts on
# Sulfate
# Nitrate
# Elemental Carbon (EC)
# Organic Carbon fraction 1 (OC)
# Organic Carbon fraction 2 (OC2)
# Organic Carbon fraction 3 (OC3)
# Pyrolized Organic Carbon (OP)
# 2)Inclusion of gas-phase specie carbon monoxide (CO)
# 3)Inclusion of gas-phase specie ozone (O3).
# 4)Inclusion of both gas-phase speciesis present...
data = {
'column names':
['Sulfate', 'Nitrate', 'EC', 'OC1', 'OC2', 'OC3', 'OP', 'CO',
'O3'],
'Basecase':
[[0.88, 0.01, 0.03, 0.03, 0.00, 0.06, 0.01, 0.00, 0.00],
[0.07, 0.95, 0.04, 0.05, 0.00, 0.02, 0.01, 0.00, 0.00],
[0.01, 0.02, 0.85, 0.19, 0.05, 0.10, 0.00, 0.00, 0.00],
[0.02, 0.01, 0.07, 0.01, 0.21, 0.12, 0.98, 0.00, 0.00],
[0.01, 0.01, 0.02, 0.71, 0.74, 0.70, 0.00, 0.00, 0.00]],
'With CO':
[[0.88, 0.02, 0.02, 0.02, 0.00, 0.05, 0.00, 0.05, 0.00],
[0.08, 0.94, 0.04, 0.02, 0.00, 0.01, 0.12, 0.04, 0.00],
[0.01, 0.01, 0.79, 0.10, 0.00, 0.05, 0.00, 0.31, 0.00],
[0.00, 0.02, 0.03, 0.38, 0.31, 0.31, 0.00, 0.59, 0.00],
[0.02, 0.02, 0.11, 0.47, 0.69, 0.58, 0.88, 0.00, 0.00]],
'With O3':
[[0.89, 0.01, 0.07, 0.00, 0.00, 0.05, 0.00, 0.00, 0.03],
[0.07, 0.95, 0.05, 0.04, 0.00, 0.02, 0.12, 0.00, 0.00],
[0.01, 0.02, 0.86, 0.27, 0.16, 0.19, 0.00, 0.00, 0.00],
[0.01, 0.03, 0.00, 0.32, 0.29, 0.27, 0.00, 0.00, 0.95],
[0.02, 0.00, 0.03, 0.37, 0.56, 0.47, 0.87, 0.00, 0.00]],
'CO & O3':
[[0.87, 0.01, 0.08, 0.00, 0.00, 0.04, 0.00, 0.00, 0.01],
[0.09, 0.95, 0.02, 0.03, 0.00, 0.01, 0.13, 0.06, 0.00],
[0.01, 0.02, 0.71, 0.24, 0.13, 0.16, 0.00, 0.50, 0.00],
[0.01, 0.03, 0.00, 0.28, 0.24, 0.23, 0.00, 0.44, 0.88],
[0.02, 0.00, 0.18, 0.45, 0.64, 0.55, 0.86, 0.00, 0.16]]}
return data
if __name__ == '__main__':
N = 9
theta = radar_factory(N, frame='polygon')
data = example_data()
spoke_labels = data.pop('column names')
fig = plt.figure(figsize=(9, 9))
fig.subplots_adjust(wspace=0.25, hspace=0.20, top=0.85, bottom=0.05)
colors = ['b', 'r', 'g', 'm', 'y']
# Plot the four cases from the example data on separate axes
for n, title in enumerate(data.keys()):
ax = fig.add_subplot(2, 2, n+1, projection='radar')
plt.rgrids([0.2, 0.4, 0.6, 0.8])
ax.set_title(title, weight='bold', size='medium', position=(0.5, 1.1),
horizontalalignment='center', verticalalignment='center')
for d, color in zip(data[title], colors):
ax.plot(theta, d, color=color)
ax.fill(theta, d, facecolor=color, alpha=0.25)
ax.set_varlabels(spoke_labels)
# add legend relative to top-left plot
plt.subplot(2, 2, 1)
labels = ('Factor 1', 'Factor 2', 'Factor 3', 'Factor 4', 'Factor 5')
legend = plt.legend(labels, loc=(0.9, .95), labelspacing=0.1)
plt.setp(legend.get_texts(), fontsize='small')
plt.figtext(0.5, 0.965, '5-Factor Solution Profiles Across Four Scenarios',
ha='center', color='black', weight='bold', size='large')
plt.show()
from IPython.core.display import Image, HTML, SVG
Image(filename="/usr/share/doc/texlive-doc/latex/ctable/penguin.jpg")
SVG(filename="/usr/share/doc/ipython/examples/notebooks/python-logo.svg")
from IPython.display import HTML
HTML('<iframe src=http://www.genua.de width=650 height=250></iframe>')
from IPython.display import YouTubeVideo
YouTubeVideo("2G5YTlheCbw")
import IPython
IPython.display.Math(r"\sum_{n=1}^\infty \frac{1}{n^2} = \frac{\pi^2}{6}")
LaTeX innerhalb von Markdown geht auch: $\frac{1}{\sqrt{ 2 \pi \sigma^2 }} e^{ - \frac{ (x - \mu)^2 } {2 \sigma^2} }$
class Disc(object):
def __init__(self, size, color='red'):
self.size = size
self.color = color
def _repr_svg_(self):
return """<svg xmlns="http://www.w3.org/2000/svg" version="1.1">
<circle cx="{0:d}" cy="{0:d}" r="{0:d}" fill="{1:s}" />
</svg>""".format(self.size, self.color)
Disc(65, "blue")
from sympy import *
%load_ext sympy.interactive.ipythonprinting
x = Symbol('x')
/usr/lib/pymodules/python2.7/mpl_toolkits/__init__.py:2: UserWarning: Module mpl_toolkits was already imported from /usr/lib/pymodules/python2.7/mpl_toolkits/__init__.pyc, but /usr/local/lib/python2.7/dist-packages is being added to sys.path __import__('pkg_resources').declare_namespace(__name__)
pi.evalf(100)
(pi+x*2)**3
((pi+x*2)**3).expand()
%load_ext sql
rm -rf foo.db
%sql sqlite:///foo.db
u'Connected: None@foo.db'
%%sql sqlite:///foo.db
CREATE TABLE writer (first_name, last_name, year_of_death);
INSERT INTO writer VALUES ('William', 'Shakespeare', 1616);
INSERT INTO writer VALUES ('Bertold', 'Brecht', 1956);
%%sql select * from writer
first_name | last_name | year_of_death |
---|---|---|
William | Shakespeare | 1616 |
Bertold | Brecht | 1956 |