back to the matplotlib-gallery at https://github.com/rasbt/matplotlib-gallery
In [1]:
%load_ext watermark
In [2]:
%watermark -u -v -d -p matplotlib,numpy
[More info](http://nbviewer.ipython.org/github/rasbt/python_reference/blob/master/ipython_magic/watermark.ipynb) about the `%watermark` extension
In [3]:
%matplotlib inline
In [5]:
from matplotlib import pyplot as plt
import numpy as np
plt.pie(
(10,5),
labels=('spam','ham'),
shadow=True,
colors=('yellowgreen', 'lightskyblue'),
explode=(0,0.15), # space between slices
startangle=90, # rotate conter-clockwise by 90 degrees
autopct='%1.1f%%',# display fraction as percentage
)
plt.legend(fancybox=True)
plt.axis('equal') # plot pyplot as circle
plt.tight_layout()
plt.show()
In [5]:
from matplotlib import pyplot as plt
import matplotlib.tri as tri
import numpy as np
rand_data = np.random.randn(50, 2)
triangulation = tri.Triangulation(rand_data[:,0], rand_data[:,1])
plt.triplot(triangulation)
plt.show()
In [7]:
import matplotlib.pyplot as plt
x = [1, 2, 3]
y_1 = [50, 60, 70]
y_2 = [20, 30, 40]
with plt.xkcd():
plt.plot(x, y_1, marker='x')
plt.plot(x, y_2, marker='^')
plt.xlim([0, len(x)+1])
plt.ylim([0, max(y_1+y_2) + 10])
plt.xlabel('x-axis label')
plt.ylabel('y-axis label')
plt.title('Simple line plot')
plt.legend(['sample 1', 'sample2'], loc='upper left')
plt.show()
In [8]:
import numpy as np
import random
from matplotlib import pyplot as plt
data = np.random.normal(0, 20, 1000)
bins = np.arange(-100, 100, 5) # fixed bin size
with plt.xkcd():
plt.xlim([min(data)-5, max(data)+5])
plt.hist(data, bins=bins, alpha=0.5)
plt.title('Random Gaussian data (fixed bin size)')
plt.xlabel('variable X (bin size = 5)')
plt.ylabel('count')
plt.show()
In [9]:
from matplotlib import pyplot as plt
import numpy as np
with plt.xkcd():
X = np.random.random_integers(1,5,5) # 5 random integers within 1-5
cols = ['b', 'g', 'r', 'y', 'm']
plt.pie(X, colors=cols)
plt.legend(X)
plt.show()