diff --git a/examples/plot_logistic_l1_l2_coef.py b/examples/plot_logistic_l1_l2_coef.py
new file mode 100644
index 0000000000000000000000000000000000000000..2016debd7ee2a3c2e8d41b05ca7b9692db1b7cea
--- /dev/null
+++ b/examples/plot_logistic_l1_l2_coef.py
@@ -0,0 +1,33 @@
+# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
+# License: BSD Style.
+
+# $Id$
+
+import numpy as np
+
+from scikits.learn.logistic import LogisticRegression
+from scikits.learn import datasets
+
+iris = datasets.load_iris()
+X = iris.data
+y = iris.target
+
+# Set regularization parameter
+C = 0.1
+
+classifier_l1_LR = LogisticRegression(C=C, penalty='l1')
+classifier_l2_LR = LogisticRegression(C=C, penalty='l2')
+classifier_l1_LR.fit(X, y)
+classifier_l2_LR.fit(X, y)
+
+hyperplane_coefficients_l1_LR = classifier_l1_LR.coef_[:]
+hyperplane_coefficients_l2_LR = classifier_l2_LR.coef_[:]
+
+# hyperplane_coefficients_l1_LR contains zeros due to the
+# L1 sparsity inducing norm
+
+pct_non_zeros_l1_LR = np.mean(hyperplane_coefficients_l1_LR != 0) * 100
+pct_non_zeros_l2_LR = np.mean(hyperplane_coefficients_l2_LR != 0) * 100
+
+print "Percentage of non zeros coefficients (L1) : %f" % pct_non_zeros_l1_LR
+print "Percentage of non zeros coefficients (L2) : %f" % pct_non_zeros_l2_LR