back to the matplotlib-gallery at https://github.com/rasbt/matplotlib-gallery



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%load_ext watermark



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%watermark -u -v -d -p matplotlib,numpy









    



Last updated: 07/10/2015 

CPython 3.4.3
IPython 3.2.0

matplotlib 1.4.3
numpy 1.9.2

[More info](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/ipython_magic/watermark.ipynb) about the `%watermark` extension



In [3]:

    
%matplotlib inline

Matplotlib Formatting III: What it takes to become a legend

I won't be a rock star. I will be a legend.

-- Freddie Mercury

Sections

Back to square one
Let's get fancy
Thinking outside the box
I love when things are transparent, free and clear
Markers -- All good things come in threes!

Back to square one

⬆



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import matplotlib.pyplot as plt
import numpy as np

x = np.arange(10)

for i in range(1, 4):
    plt.plot(x, i * x**2, label='Group %d' % i)

plt.legend(loc='best')
plt.show()

Let's get fancy

⬆



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x = np.arange(10)

for i in range(1, 4):
    plt.plot(x, i * x**2, label='Group %d' % i)

plt.legend(loc='best', fancybox=True, shadow=True)
plt.show()

Thinking outside the box

⬆



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fig = plt.figure()
ax = plt.subplot(111)

x = np.arange(10)

for i in range(1, 4):
    ax.plot(x, i * x**2, label='Group %d' % i)

ax.legend(loc='upper center', 
          bbox_to_anchor=(0.5,  # horizontal
                          1.15),# vertical 
          ncol=3, fancybox=True)
plt.show()



In [22]:

    
fig = plt.figure()
ax = plt.subplot(111)

x = np.arange(10)

for i in range(1, 4):
    ax.plot(x, i * x**2, label='Group %d' % i)

ax.legend(loc='upper center', 
          bbox_to_anchor=(1.15, 1.02),
          ncol=1, fancybox=True)
plt.show()

I love when things are transparent, free and clear

⬆



In [27]:

    
x = np.arange(10)

for i in range(1, 4):
    plt.plot(x, i * x**2, label='Group %d' % i)

plt.legend(loc='upper right', framealpha=0.1)
plt.show()

Markers -- All good things come in threes!

⬆



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from itertools import cycle
x = np.arange(10)

colors = ['blue', 'red', 'green']
color_gen = cycle(colors)

for i in range(1, 4):
    plt.scatter(x, i * x**2, label='Group %d' % i, color=next(color_gen))

plt.legend(loc='upper left')
plt.show()



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from itertools import cycle
x = np.arange(10)

colors = ['blue', 'red', 'green']
color_gen = cycle(colors)

for i in range(1, 4):
    plt.scatter(x, i * x**2, label='Group %d' % i, color=next(color_gen))

plt.legend(loc='upper left', scatterpoints=1)
plt.show()



In [37]:

    
from itertools import cycle
x = np.arange(10)

colors = ['blue', 'red', 'green']
color_gen = cycle(colors)

for i in range(1, 4):
    plt.plot(x, i * x**2, label='Group %d' % i, marker='o')

plt.legend(loc='upper left')
plt.show()



In [38]:

    
from itertools import cycle
x = np.arange(10)

colors = ['blue', 'red', 'green']
color_gen = cycle(colors)

for i in range(1, 4):
    plt.plot(x, i * x**2, label='Group %d' % i, marker='o')

plt.legend(loc='upper left', numpoints=1)
plt.show()



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