In [30]:

    

import pandas as pd
import numpy as np

%pylab inline

figsize(5, 5)


    

    




Populating the interactive namespace from numpy and matplotlib

In [31]:

    

x = np.random.normal(0, 10, 10000)
y = np.random.normal(0, 10, 10000)


    

In [32]:

    

df = pd.DataFrame( { 'x' : x, 'y' : y } )


    

In [33]:

    

df['y'].hist(bins=30)


    

    
Out[33]:





<matplotlib.axes.AxesSubplot at 0x106c18d10>






    

In [34]:

    

df.head(10)


    

    
Out[34]:






  

    

      

      
x
      
y
    
  
  

    

      
0
      
 11.255542
      
-10.895887
    
    

      
1
      
-18.348279
      
  2.776466
    
    

      
2
      
  0.714115
      
  2.774420
    
    

      
3
      
 -5.617024
      
 -6.166744
    
    

      
4
      
 18.045067
      
 21.617985
    
    

      
5
      
 21.826769
      
  1.260872
    
    

      
6
      
 -6.976635
      
-10.330302
    
    

      
7
      
  4.163109
      
 -3.359381
    
    

      
8
      
  4.103767
      
-16.370349
    
    

      
9
      
 11.980980
      
  5.356135
    
  

In [35]:

    

df.plot(x='x', y='y', style='o', alpha=.02)


    

    
Out[35]:





<matplotlib.axes.AxesSubplot at 0x10966cd90>






    

In [36]:

    

plt.hexbin(df['x'], df['y'], bins='log', gridsize=50, cmap=plt.cm.hot)


    

    
Out[36]:





<matplotlib.collections.PolyCollection at 0x109716f10>






    

In [37]:

    

df = pd.read_csv('taxirides.csv')


    

In [38]:

    

df.head(5)


    

    
Out[38]:






  

    

      

      
ID
      
PICKUP_TIME
      
PICKUP_ADDRESS
      
PICKUP_LONG
      
PICKUP_LAT
    
  
  

    

      
0
      
 230216
      
 2012-05-11 00:00:00
      
            317 Washington St Boston Ma 02135
      
-71.152022
      
 42.349030
    
    

      
1
      
 230217
      
 2012-05-11 00:00:00
      
                       Unnamed Road Boston Ma
      
-71.018663
      
 42.369197
    
    

      
2
      
 230218
      
 2012-05-11 00:00:00
      
       Beacon St @ Commonwealth Ave Boston Ma
      
-71.097962
      
 42.348598
    
    

      
3
      
 230219
      
 2012-05-11 00:00:00
      
 Commonwealth Ave @ Beacon St Boston Ma 02215
      
-71.096017
      
 42.348735
    
    

      
4
      
 230228
      
 2012-05-11 00:00:00
      
              400 Boylston St Boston Ma 02116
      
-71.072253
      
 42.351457
    
  

In [40]:

    

figsize(15, 15)


    

In [42]:

    

df.plot(x='PICKUP_LONG', y='PICKUP_LAT', style='o', alpha=.02)


    

    
Out[42]:





<matplotlib.axes.AxesSubplot at 0x108e47d10>






    

In [41]:

    

plt.hexbin(df['PICKUP_LONG'], df['PICKUP_LAT'], bins='log', gridsize=400, cmap=plt.cm.hot)


    

    
Out[41]:





<matplotlib.collections.PolyCollection at 0x108e5e450>






    

In [ ]: