@@ -62,7 +62,7 @@ def __init__(self, disp, pad, field):
     def _reset(self,pad):
         self.x = pad.x + pad.xoffset
         if pad.y < 0:
-            self.y = pad.y +  pad.yoffset
+            self.y = pad.y + pad.yoffset
         else:
             self.y = pad.y - pad.yoffset
         self.vx = pad.x - self.x
 
@@ -30,7 +30,7 @@
     coded[name] = ccode
     glyphd[name] = glyphind
 
-code =  coded['A']
+code = coded['A']
 glyph = font.load_char(code)
 #print glyph.bbox
 print(glyphd['A'], glyphd['V'], coded['A'], coded['V'])
 
@@ -83,7 +83,7 @@ def hex_to_rgba(ob, name, val):
 
 def colorname_to_rgba(ob, name, val):
     hex = colors[val.lower()]
-    r,g,b =  hex2color(hex)
+    r,g,b = hex2color(hex)
     return RGBA(r,g,b,1.0)
 colorname_to_rgba.info = 'a named color'
 
 
@@ -98,7 +98,7 @@ def __init__(self, width, height, xdescent, ydescent,
 
     # draw a horizontal bar with length of 0.1 in Data coordinate
     # (ax.transData) with a label underneath.
-    asb =  AnchoredSizeBar(ax.transData,
+    asb = AnchoredSizeBar(ax.transData,
                           0.1,
                           r"1$^{\prime}$",
                           loc=8,
 
@@ -11,7 +11,7 @@
 
 from pylab import *
 
-x =  array([10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5])
+x = array([10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5])
 y1 = array([8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68])
 y2 = array([9.14, 8.14, 8.74, 8.77, 9.26, 8.10, 6.13, 3.10, 9.13, 7.26, 4.74])
 y3 = array([7.46, 6.77, 12.74, 7.11, 7.81, 8.84, 6.08, 5.39, 8.15, 6.42, 5.73])
 
@@ -8,8 +8,8 @@
 def millions(x):
     return '$%1.1fM' % (x*1e-6)
 
-x =     rand(20)
-y =     1e7*rand(20)
+x = rand(20)
+y = 1e7*rand(20)
 
 fig, ax = subplots()
 ax.fmt_ydata = millions
 
@@ -14,7 +14,7 @@
 import matplotlib.pyplot as plt
 import numpy as np
 
-x =     np.arange(4)
+x = np.arange(4)
 money = [1.5e5, 2.5e6, 5.5e6, 2.0e7]
 
 
 
@@ -36,7 +36,7 @@ def moving_average(x, n, type='simple'):
 
     weights /= weights.sum()
 
-    a =  np.convolve(x, weights, mode='full')[:len(x)]
+    a = np.convolve(x, weights, mode='full')[:len(x)]
     a[:n] = a[n]
     return a
 
 
@@ -6,7 +6,7 @@
 
 N = 5
 menMeans = (150*cm, 160*cm, 146*cm, 172*cm, 155*cm)
-menStd =   ( 20*cm,  30*cm,  32*cm,  10*cm,  20*cm)
+menStd = ( 20*cm,  30*cm,  32*cm,  10*cm,  20*cm)
 
 fig, ax = plt.subplots()
 
@@ -16,7 +16,7 @@
 
 
 womenMeans = (145*cm, 149*cm, 172*cm, 165*cm, 200*cm)
-womenStd =   (30*cm, 25*cm, 20*cm, 31*cm, 22*cm)
+womenStd = (30*cm, 25*cm, 20*cm, 31*cm, 22*cm)
 p2 = ax.bar(ind+width, womenMeans, width, color='y', bottom=0*cm, yerr=womenStd)
 
 ax.set_title('Scores by group and gender')