Twitter geo heatmap

gistfile1.py

import simplejson, urllib           # To get posts from Twitter
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm           # Colormap
import scipy.stats                  # For kernel density estimation

# Get geo-tagged posts from Twitter
url = 'http://search.twitter.com/search?q=geotag&format=json&rpp=100'
resp = simplejson.load(urllib.urlopen(url))
coords = np.asarray([ t['geo']['coordinates'][::-1] 
                      for t in resp['results'] if t['geo'] ])
users = [ t['from_user'] for t in resp['results'] if t['geo'] ]

X, Y = np.mgrid[-180:180:100j, -90:90:100j]
positions = np.c_[X.ravel(), Y.ravel()]
kernel = scipy.stats.kde.gaussian_kde(coords.T) 
Z = np.reshape(kernel(positions.T), X.shape)

plt.figure(), plt.hold(True)
plt.imshow(np.rot90(Z), cmap=cm.hot, extent=(-180, 180, -90, 90))
for user, c in zip(users, coords): 
   plt.plot(c[0], c[1], 'ko', markeredgewidth=3, markersize=20,
                              markeredgecolor=(0.3, 0.3, 0.3))
   dummy = plt.text(c[0], c[1], user, color=(.1, .7, 0.1),
             horizontalalignment='center', verticalalignment='center')

plt.axis((-180, 180, -90, 90)); plt.grid(color=(0.5, 0.5, 0.5))
plt.xlabel('Longitude'); plt.ylabel('Latitude') 
plt.show()