diff --git a/README.rst b/README.rst
index b38389c..920d9b2 100644
--- a/README.rst
+++ b/README.rst
@@ -33,8 +33,8 @@ Dependencies
 Other Python versions were not tested, but are likely to work.
 
 
-Example
--------
+Examples
+--------
 
 .. code:: python
 
@@ -53,22 +53,24 @@ Example
 	
 	
 .. code:: python
-    # generate several time series of independent indentically distributed variables 
-    # repeat the simulation of each variable multiple times
+
+	# generate several time series of independent indentically distributed variables 
+	# repeat the simulation of each variable multiple times
 	import colorednoise as cn
-    n_repeats   = 10   # repeat simulatons
-    n_variables = 5    # independent variables in each simulation
-    timesteps   = 1000 # number of timesteps for each variable
-    y = cn.powerlaw_psd_gaussian(1, (n_repeats, n_variables, timesteps))
-    
-    # the expected variance of for each variable is 1, but each realisation is different
-    print(y.std(axis=-1))
-    
+	n_repeats   = 10   # repeat simulatons
+	n_variables = 5    # independent variables in each simulation
+	timesteps   = 1000 # number of timesteps for each variable
+	y = cn.powerlaw_psd_gaussian(1, (n_repeats, n_variables, timesteps))
+	
+	# the expected variance of for each variable is 1, but each realisation is different
+	print(y.std(axis=-1))
+	
 .. code:: python
-    # generate a broken power law spectrum: white below a frequency of 
+
+	# generate a broken power law spectrum: white below a frequency of 
 	import colorednoise as cn
-    y = cn.powerlaw_psd_gaussian(1, 10**5, fmin=.05)
-    s, f = mlab.psd(y, NFFT=2**9)
-    #plt.loglog(f,s)
-    #plt.grid(True)
-    #plt.show()
+	y = cn.powerlaw_psd_gaussian(1, 10**5, fmin=.05)
+	s, f = mlab.psd(y, NFFT=2**9)
+	#plt.loglog(f,s)
+	#plt.grid(True)
+	#plt.show()