In [6]:

    

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%pylab inline

#use a nicer plotting style
plt.style.use(u'seaborn-notebook')
print(plt.style.available)


    

    




Populating the interactive namespace from numpy and matplotlib
[u'seaborn-darkgrid', u'seaborn-notebook', u'classic', u'seaborn-ticks', u'grayscale', u'bmh', u'seaborn-talk', u'dark_background', u'ggplot', u'fivethirtyeight', u'seaborn-colorblind', u'seaborn-deep', u'seaborn-whitegrid', u'seaborn-bright', u'seaborn-poster', u'seaborn-muted', u'seaborn-paper', u'seaborn-white', u'seaborn-pastel', u'seaborn-dark', u'seaborn-dark-palette']

In [7]:

    

y = [3, 10, 7, 5, 3, 4.5, 6, 8.1]
N = len(y)
x = range(N)
width = 1/1.5
bar(x, y, width, color="blue")


    

    
Out[7]:





<Container object of 8 artists>






    

In [8]:

    

plt.barh(x, y, width, color="blue")


    

    
Out[8]:





<Container object of 8 artists>






    

In [9]:

    

plot(y)


    

    
Out[9]:





[<matplotlib.lines.Line2D at 0x10a5a0410>]






    

In [10]:

    

data = pd.read_csv('./data/assembly.dat',delimiter='\t',skiprows=11,names=['s','usec','ax','ay','az','gx','gy','gz','mx','my','mz','label'])


    

In [13]:

    

fig= figure()
plot(data['ax'], label='acceleration x')
plot(data['gx'], label='gyrscope x')
ylabel("raw sensor value")
xlabel("time")
legend(loc='upper right')


    

    
Out[13]:





<matplotlib.legend.Legend at 0x10b33bb90>






    

In [21]:

    

import matplotlib.pyplot as plt

# The slices will be ordered and plotted counter-clockwise.
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0, 0, 0)  # don't "explode"

plt.pie(sizes, explode=explode, labels=labels, colors=colors,
        autopct='%1.1f%%', shadow=True, startangle=90)
# Set aspect ratio to be equal so that pie is drawn as a circle.
plt.axis('equal')


    

    
Out[21]:





(-1.0123741244270577,
 1.027940084990864,
 -1.0246160299958926,
 1.0000000049123423)






    

In [22]:

    

# The slices will be ordered and plotted counter-clockwise.
labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'
sizes = [15, 30, 45, 10]
colors = ['yellowgreen', 'gold', 'lightskyblue', 'lightcoral']
explode = (0, 0.1, 0, 0)  # only "explode" the 2nd slice (i.e. 'Hogs')

plt.pie(sizes, explode=explode, labels=labels, colors=colors,
        autopct='%1.1f%%', shadow=True, startangle=90)
# Set aspect ratio to be equal so that pie is drawn as a circle.
plt.axis('equal')


    

    
Out[22]:





(-1.1074797737419919,
 1.027940084990864,
 -1.0246160299958926,
 1.0000000049123423)






    

In [14]:

    

#!/usr/bin/env python
import numpy as np
import matplotlib.mlab as mlab
import matplotlib.pyplot as plt

mu, sigma = 100, 15
x = mu + sigma*np.random.randn(10000)

# the histogram of the data
n, bins, patches = plt.hist(x, 50, normed=1, facecolor='green', alpha=0.75)

# add a 'best fit' line
y = mlab.normpdf( bins, mu, sigma)
l = plt.plot(bins, y, 'r--', linewidth=1)

plt.xlabel('Smarts')
plt.ylabel('Probability')
plt.title(r'$\mathrm{Histogram\ of\ IQ:}\ \mu=100,\ \sigma=15$')
plt.axis([40, 160, 0, 0.03])
plt.grid(True)


    

In [17]:

    

n, bins, patches = plt.hist(x, 500, normed=1, facecolor='green', alpha=0.75)


    

In [ ]: