In [1]:

    

from pylab import *
import numpy as np
import pandas as pd


    

In [2]:

    

x = np.linspace(0, 5, 10)
xx = np.linspace(-0.75, 1., 100)
n = np.array([0,1,2,3,4,5])
dates = pd.date_range('20130101', periods=6)
df = pd.DataFrame(np.random.randn(6,4), index=dates, columns=list('ABCD'))
df


    

    
Out[2]:






  

    

      

      
A
      
B
      
C
      
D
    
  
  

    

      
2013-01-01
      
2.278744
      
-0.652785
      
0.574983
      
-0.408235
    
    

      
2013-01-02
      
0.886904
      
-1.415350
      
0.487806
      
-0.117535
    
    

      
2013-01-03
      
1.280152
      
0.451589
      
2.450064
      
-0.159981
    
    

      
2013-01-04
      
-0.163132
      
0.141542
      
1.810313
      
2.263799
    
    

      
2013-01-05
      
-0.488827
      
0.263963
      
0.598489
      
0.933941
    
    

      
2013-01-06
      
-1.589058
      
0.054630
      
1.425882
      
0.133386
    
  

In [3]:

    

fig, axes = plt.subplots(1, 4, figsize=(12,3))

axes[0].scatter(xx, xx + 0.25*np.random.randn(len(xx)))
axes[0].set_title("scatter")

axes[1].step(n, n**2, lw=2)
axes[1].set_title("step")

axes[2].bar(n, n**2, align="center", width=0.5, alpha=0.5)
axes[2].set_title("bar")

axes[3].fill_between(x, x**2, x**3, color="green", alpha=0.5);
axes[3].set_title("fill_between");
show(fig)


    

In [4]:

    

# polar plot using add_axes and polar projection
fig = plt.figure()
ax = fig.add_axes([0.0, 0.0, .6, .6], polar=True)
t = np.linspace(0, 2 * np.pi, 100)
ax.plot(t, t, color='blue', lw=3);
show(fig)