diff --git "a/Flask Web\345\274\200\345\217\221\357\274\232\345\237\272\344\272\216Python\347\232\204Web\345\272\224\347\224\250\345\274\200\345\217\221\345\256\236\346\210\230.pdf" "b/Flask Web\345\274\200\345\217\221\357\274\232\345\237\272\344\272\216Python\347\232\204Web\345\272\224\347\224\250\345\274\200\345\217\221\345\256\236\346\210\230.pdf"
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Binary files /dev/null and "b/Flask Web\345\274\200\345\217\221\357\274\232\345\237\272\344\272\216Python\347\232\204Web\345\272\224\347\224\250\345\274\200\345\217\221\345\256\236\346\210\230.pdf" differ
diff --git a/NumPy/Code/ch10code/README b/NumPy/Code/ch10code/README
new file mode 100644
index 0000000..0360b53
--- /dev/null
+++ b/NumPy/Code/ch10code/README
@@ -0,0 +1,19 @@
+NumPy Beginner's Guide
+
+Chapter 10 When Numpy is not enough: Scipy and beyond
+
+The example code requires SciPy and Matplotlib.
+
+Run the code examples with
+
+python <name of script>
+
+frequencies.py Demonstrates FFT transforms.
+gaussquad.py Demonstrates numerical integration.
+images.py Demonstrates image manipulation.
+optfit.py Demonstrates optimization.
+pair.py Demonstrates two samples statistical tests.
+scipyio.py Demonstrates Matlab/Octave interoperability.
+sincinterp.py Demonstrates interpolation.
+statistics.py Demonstrates statistical functionality.
+trend.py Demonstrates the detrend function.
diff --git a/NumPy/Code/ch10code/a.mat b/NumPy/Code/ch10code/a.mat
new file mode 100644
index 0000000..7d0b84a
Binary files /dev/null and b/NumPy/Code/ch10code/a.mat differ
diff --git a/NumPy/Code/ch10code/algebra.py b/NumPy/Code/ch10code/algebra.py
new file mode 100644
index 0000000..f1ae452
--- /dev/null
+++ b/NumPy/Code/ch10code/algebra.py
@@ -0,0 +1,61 @@
+from matplotlib.finance import quotes_historical_yahoo
+from datetime import date
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy import fftpack
+from scipy import signal
+from matplotlib.dates import DateFormatter, DayLocator, MonthLocator
+from scipy import optimize
+
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+quotes = quotes_historical_yahoo("QQQ", start, today)
+quotes = np.array(quotes)
+
+dates = quotes.T[0]
+qqq = quotes.T[4]
+
+
+y = signal.detrend(qqq)
+
+
+alldays = DayLocator()              
+months = MonthLocator()
+month_formatter = DateFormatter("%b %Y")
+
+fig = plt.figure()
+ax = fig.add_subplot(211)
+
+ax.xaxis.set_minor_locator(alldays)
+ax.xaxis.set_major_locator(months)
+ax.xaxis.set_major_formatter(month_formatter)
+
+amps = np.abs(fftpack.fftshift(fftpack.rfft(y)))
+amps[amps < amps.max()] = 0
+
+def residuals(p, y, x):
+   A,k,theta = p
+   err = y-A * np.sin(2* np.pi* k * x + theta)
+
+   return err
+
+filtered = -fftpack.irfft(fftpack.ifftshift(amps))
+N = len(qqq)
+f = np.linspace(-N/2, N/2, N)
+p0 = [filtered.max(), f[amps.argmax()]/N, np.pi/3]
+plsq = optimize.leastsq(residuals, p0, args=(filtered, dates))
+p = plsq[0]
+print p
+plt.plot(dates, y, 'o', label="detrended")
+plt.plot(dates, filtered, label="filtered")
+plt.plot(dates, p[0] * np.sin(2 * np.pi * dates * p[1] + p[2]), '^', label="fit")
+fig.autofmt_xdate()
+plt.legend()
+
+ax2 = fig.add_subplot(212)
+plt.plot(f, amps, label="transformed")
+
+plt.legend()
+plt.show()
diff --git a/NumPy/Code/ch10code/frequencies.py b/NumPy/Code/ch10code/frequencies.py
new file mode 100644
index 0000000..a8cd07e
--- /dev/null
+++ b/NumPy/Code/ch10code/frequencies.py
@@ -0,0 +1,54 @@
+from matplotlib.finance import quotes_historical_yahoo
+from datetime import date
+import numpy as np
+from scipy import signal
+import matplotlib.pyplot as plt
+from scipy import fftpack
+from matplotlib.dates import DateFormatter
+from matplotlib.dates import DayLocator
+from matplotlib.dates import MonthLocator
+
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+quotes = quotes_historical_yahoo("QQQ", start, today)
+quotes = np.array(quotes)
+
+dates = quotes.T[0]
+qqq = quotes.T[4]
+
+
+y = signal.detrend(qqq)
+
+
+alldays = DayLocator()              
+months = MonthLocator()
+month_formatter = DateFormatter("%b %Y")
+
+fig = plt.figure()
+fig.subplots_adjust(hspace=.3)
+ax = fig.add_subplot(211)
+
+ax.xaxis.set_minor_locator(alldays)
+ax.xaxis.set_major_locator(months)
+ax.xaxis.set_major_formatter(month_formatter)
+
+# make font size bigger
+ax.tick_params(axis='both', which='major', labelsize='x-large')
+
+amps = np.abs(fftpack.fftshift(fftpack.rfft(y)))
+amps[amps < 0.1 * amps.max()] = 0
+
+plt.plot(dates, y, 'o', label="detrended")
+plt.plot(dates, -fftpack.irfft(fftpack.ifftshift(amps)), label="filtered")
+fig.autofmt_xdate()
+plt.legend(prop={'size':'x-large'})
+
+ax2 = fig.add_subplot(212)
+ax2.tick_params(axis='both', which='major', labelsize='x-large')
+N = len(qqq)
+plt.plot(np.linspace(-N/2, N/2, N), amps, label="transformed")
+
+plt.legend(prop={'size':'x-large'})
+plt.show()
diff --git a/NumPy/Code/ch10code/gaussquad.py b/NumPy/Code/ch10code/gaussquad.py
new file mode 100644
index 0000000..d9ebaff
--- /dev/null
+++ b/NumPy/Code/ch10code/gaussquad.py
@@ -0,0 +1,4 @@
+from scipy import integrate
+import numpy as np
+
+print "Gaussian integral", np.sqrt(np.pi), integrate.quad(lambda x: np.exp(-x**2), -np.inf, np.inf)
diff --git a/NumPy/Code/ch10code/images.py b/NumPy/Code/ch10code/images.py
new file mode 100644
index 0000000..b5c41e8
--- /dev/null
+++ b/NumPy/Code/ch10code/images.py
@@ -0,0 +1,31 @@
+from scipy import misc
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy import ndimage
+
+
+image = misc.lena().astype(np.float32)
+
+plt.subplot(221)
+plt.title("Original Image") 
+img = plt.imshow(image, cmap=plt.cm.gray) 
+plt.axis("off")
+
+plt.subplot(222) 
+plt.title("Median Filter") 
+filtered = ndimage.median_filter(image, size=(42,42))
+plt.imshow(filtered, cmap=plt.cm.gray) 
+plt.axis("off")
+
+plt.subplot(223) 
+plt.title("Rotated") 
+rotated = ndimage.rotate(image, 90)
+plt.imshow(rotated, cmap=plt.cm.gray) 
+plt.axis("off")
+
+plt.subplot(224) 
+plt.title("Prewitt Filter") 
+filtered = ndimage.prewitt(image)
+plt.imshow(filtered, cmap=plt.cm.gray) 
+plt.axis("off")
+plt.show()
diff --git a/NumPy/Code/ch10code/optfit.py b/NumPy/Code/ch10code/optfit.py
new file mode 100644
index 0000000..de80aa3
--- /dev/null
+++ b/NumPy/Code/ch10code/optfit.py
@@ -0,0 +1,67 @@
+from matplotlib.finance import quotes_historical_yahoo
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy import fftpack
+from scipy import signal
+from matplotlib.dates import DateFormatter
+from matplotlib.dates import DayLocator
+from matplotlib.dates import MonthLocator
+from scipy import optimize
+
+
+start = (2010, 7, 25)
+end = (2011, 7, 25)
+
+quotes = quotes_historical_yahoo("QQQ", start, end)
+quotes = np.array(quotes)
+
+dates = quotes.T[0]
+qqq = quotes.T[4]
+
+
+y = signal.detrend(qqq)
+
+
+alldays = DayLocator()              
+months = MonthLocator()
+month_formatter = DateFormatter("%b %Y")
+
+fig = plt.figure()
+fig.subplots_adjust(hspace=.3)
+ax = fig.add_subplot(211)
+
+ax.xaxis.set_minor_locator(alldays)
+ax.xaxis.set_major_locator(months)
+ax.xaxis.set_major_formatter(month_formatter)
+ax.tick_params(axis='both', which='major', labelsize='x-large')
+
+amps = np.abs(fftpack.fftshift(fftpack.rfft(y)))
+amps[amps < amps.max()] = 0
+
+def residuals(p, y, x):
+   A,k,theta,b = p
+   err = y-A * np.sin(2* np.pi* k * x + theta) + b
+
+   return err
+
+filtered = -fftpack.irfft(fftpack.ifftshift(amps))
+N = len(qqq)
+f = np.linspace(-N/2, N/2, N)
+p0 = [filtered.max(), f[amps.argmax()]/(2*N), 0, 0]
+print "P0", p0
+
+plsq = optimize.leastsq(residuals, p0, args=(filtered, dates))
+p = plsq[0]
+print "P", p
+plt.plot(dates, y, 'o', label="detrended")
+plt.plot(dates, filtered, label="filtered")
+plt.plot(dates, p[0] * np.sin(2 * np.pi * dates * p[1] + p[2]) + p[3], '^', label="fit")
+fig.autofmt_xdate()
+plt.legend(prop={'size':'x-large'})
+
+ax2 = fig.add_subplot(212)
+ax2.tick_params(axis='both', which='major', labelsize='x-large')
+plt.plot(f, amps, label="transformed")
+
+plt.legend(prop={'size':'x-large'})
+plt.show()
diff --git a/NumPy/Code/ch10code/pair.py b/NumPy/Code/ch10code/pair.py
new file mode 100644
index 0000000..6b1dde5
--- /dev/null
+++ b/NumPy/Code/ch10code/pair.py
@@ -0,0 +1,30 @@
+from matplotlib.finance import quotes_historical_yahoo
+from datetime import date
+import numpy as np
+from scipy import stats
+from statsmodels.stats.stattools import jarque_bera
+import matplotlib.pyplot as plt
+
+
+def get_close(symbol):
+   today = date.today()
+   start = (today.year - 1, today.month, today.day)
+
+   quotes = quotes_historical_yahoo(symbol, start, today)
+   quotes = np.array(quotes)
+
+   return quotes.T[4]
+
+spy =  np.diff(np.log(get_close("SPY")))
+dia =  np.diff(np.log(get_close("DIA")))
+
+print "Means comparison", stats.ttest_ind(spy, dia)
+print "Kolmogorov smirnov test", stats.ks_2samp(spy, dia)
+
+print "Jarque Bera test", jarque_bera(spy - dia)[1]
+
+plt.hist(spy, histtype="step", lw=1, label="SPY")
+plt.hist(dia, histtype="step", lw=2, label="DIA") 
+plt.hist(spy - dia, histtype="step", lw=3, label="Delta")
+plt.legend()
+plt.show()
diff --git a/NumPy/Code/ch10code/repeat_audio.py b/NumPy/Code/ch10code/repeat_audio.py
new file mode 100644
index 0000000..47899fc
--- /dev/null
+++ b/NumPy/Code/ch10code/repeat_audio.py
@@ -0,0 +1,31 @@
+from scipy.io import wavfile
+import matplotlib.pyplot as plt
+import urllib2
+import numpy as np
+import sys
+
+response = urllib2.urlopen('http://www.thesoundarchive.com/austinpowers/smashingbaby.wav')
+print response.info()
+WAV_FILE = 'smashingbaby.wav'
+filehandle = open(WAV_FILE, 'w')
+filehandle.write(response.read())
+filehandle.close()
+sample_rate, data = wavfile.read(WAV_FILE)
+print "Data type", data.dtype, "Shape", data.shape
+
+plt.subplot(2, 1, 1)
+plt.title("Original")
+plt.plot(data)
+
+plt.subplot(2, 1, 2)
+
+# Repeat the audio fragment
+repeated = np.tile(data, int(sys.argv[1]))
+
+# Plot the audio data
+plt.title("Repeated")
+plt.plot(repeated)
+wavfile.write("repeated_yababy.wav",
+    sample_rate, repeated)
+
+plt.show()
diff --git a/NumPy/Code/ch10code/scipyio.py b/NumPy/Code/ch10code/scipyio.py
new file mode 100644
index 0000000..c2ab9f9
--- /dev/null
+++ b/NumPy/Code/ch10code/scipyio.py
@@ -0,0 +1,6 @@
+import numpy as np
+from scipy import io
+
+a = np.arange(7)
+
+io.savemat("a.mat", {"array": a})
diff --git a/NumPy/Code/ch10code/sincinterp.py b/NumPy/Code/ch10code/sincinterp.py
new file mode 100644
index 0000000..3ef4671
--- /dev/null
+++ b/NumPy/Code/ch10code/sincinterp.py
@@ -0,0 +1,21 @@
+import numpy as np
+from scipy import interpolate
+import matplotlib.pyplot as plt
+
+x = np.linspace(-18, 18, 36)
+noise = 0.1 * np.random.random(len(x))
+signal = np.sinc(x) + noise
+
+interpreted = interpolate.interp1d(x, signal)
+x2 = np.linspace(-18, 18, 180)
+y = interpreted(x2)
+
+cubic = interpolate.interp1d(x, signal, kind="cubic")
+y2 = cubic(x2)
+
+plt.plot(x, signal, 'o', label="data")
+plt.plot(x2, y, '-', label="linear")
+plt.plot(x2, y2, '-', lw=2, label="cubic")
+
+plt.legend()
+plt.show()
diff --git a/NumPy/Code/ch10code/statistics.py b/NumPy/Code/ch10code/statistics.py
new file mode 100644
index 0000000..8a87d0c
--- /dev/null
+++ b/NumPy/Code/ch10code/statistics.py
@@ -0,0 +1,12 @@
+from scipy import stats
+import matplotlib.pyplot as plt
+
+generated = stats.norm.rvs(size=900)
+print "Mean", "Std", stats.norm.fit(generated)
+print "Skewtest", "pvalue", stats.skewtest(generated)
+print "Kurtosistest", "pvalue", stats.kurtosistest(generated)
+print "Normaltest", "pvalue", stats.normaltest(generated)
+print "95 percentile", stats.scoreatpercentile(generated, 95)
+print "Percentile at 1", stats.percentileofscore(generated, 1)
+plt.hist(generated)
+plt.show()
diff --git a/NumPy/Code/ch10code/trend.py b/NumPy/Code/ch10code/trend.py
new file mode 100644
index 0000000..1dc5e19
--- /dev/null
+++ b/NumPy/Code/ch10code/trend.py
@@ -0,0 +1,35 @@
+from matplotlib.finance import quotes_historical_yahoo
+from datetime import date
+import numpy as np
+from scipy import signal
+import matplotlib.pyplot as plt
+from matplotlib.dates import DateFormatter
+from matplotlib.dates import DayLocator
+from matplotlib.dates import MonthLocator
+
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+quotes = quotes_historical_yahoo("QQQ", start, today)
+quotes = np.array(quotes)
+
+dates = quotes.T[0]
+qqq = quotes.T[4]
+
+
+y = signal.detrend(qqq)
+
+alldays = DayLocator()              
+months = MonthLocator()
+month_formatter = DateFormatter("%b %Y")
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+
+plt.plot(dates, qqq, 'o', dates, qqq - y, '-')
+ax.xaxis.set_minor_locator(alldays)
+ax.xaxis.set_major_locator(months)
+ax.xaxis.set_major_formatter(month_formatter)
+fig.autofmt_xdate()
+plt.show()
diff --git a/NumPy/Code/ch11code/.life_demo.py.swp b/NumPy/Code/ch11code/.life_demo.py.swp
new file mode 100644
index 0000000..99266a5
Binary files /dev/null and b/NumPy/Code/ch11code/.life_demo.py.swp differ
diff --git a/NumPy/Code/ch11code/animation.py b/NumPy/Code/ch11code/animation.py
new file mode 100644
index 0000000..d0b6d9a
--- /dev/null
+++ b/NumPy/Code/ch11code/animation.py
@@ -0,0 +1,49 @@
+import pygame, sys
+from pygame.locals import *
+import numpy as np
+
+pygame.init()
+clock = pygame.time.Clock()
+screen = pygame.display.set_mode((400, 400))
+
+pygame.display.set_caption('Animating Objects')
+img = pygame.image.load('head.jpg')
+
+steps = np.linspace(20, 360, 40).astype(int)
+right = np.zeros((2, len(steps)))
+down = np.zeros((2, len(steps)))
+left = np.zeros((2, len(steps)))
+up = np.zeros((2, len(steps)))
+
+right[0] = steps
+right[1] = 20
+
+down[0] = 360
+down[1] = steps
+
+left[0] = steps[::-1]
+left[1] = 360
+
+up[0] = 20
+up[1] = steps[::-1]
+
+pos = np.concatenate((right.T, down.T, left.T, up.T))
+i = 0
+
+while True: 
+   # Erase screen
+   screen.fill((255, 255, 255))
+
+   if i >= len(pos):
+      i = 0
+
+   screen.blit(img, pos[i])
+   i += 1
+
+   for event in pygame.event.get():
+      if event.type == QUIT:
+         pygame.quit()
+         sys.exit()
+
+   pygame.display.update()
+   clock.tick(30)
diff --git a/NumPy/Code/ch11code/clustering.py b/NumPy/Code/ch11code/clustering.py
new file mode 100644
index 0000000..e360bd7
--- /dev/null
+++ b/NumPy/Code/ch11code/clustering.py
@@ -0,0 +1,38 @@
+import numpy as np
+import sklearn.cluster
+import pygame, sys
+from pygame.locals import *
+
+
+positions = np.random.randint(0, 400, size=(30, 2))
+
+positions_norms = np.sum(positions ** 2, axis=1)
+S = - positions_norms[:, np.newaxis] - positions_norms[np.newaxis, :] + 2 * np.dot(positions, positions.T)
+
+aff_pro = sklearn.cluster.AffinityPropagation().fit(S)
+labels = aff_pro.labels_
+
+polygon_points = []
+
+for i in xrange(max(labels) + 1):
+   polygon_points.append([])
+
+
+# Sorting points by cluster
+for i in xrange(len(labels)):
+   polygon_points[labels[i]].append(positions[i])
+
+pygame.init()
+screen = pygame.display.set_mode((400, 400))
+
+
+while True: 
+   for i in xrange(len(polygon_points)):
+      pygame.draw.polygon(screen, (255, 0, 0), polygon_points[i])
+
+   for event in pygame.event.get():
+      if event.type == QUIT:
+         pygame.quit()
+         sys.exit()
+
+   pygame.display.update()
diff --git a/NumPy/Code/ch11code/head.jpg b/NumPy/Code/ch11code/head.jpg
new file mode 100644
index 0000000..09e3ea8
Binary files /dev/null and b/NumPy/Code/ch11code/head.jpg differ
diff --git a/NumPy/Code/ch11code/life_demo.py b/NumPy/Code/ch11code/life_demo.py
new file mode 100644
index 0000000..6a890ef
--- /dev/null
+++ b/NumPy/Code/ch11code/life_demo.py
@@ -0,0 +1,88 @@
+import os, pygame
+from pygame.locals import *
+import numpy as np
+from scipy import ndimage
+
+def get_pixar(arr, weights):
+  states = ndimage.convolve(arr, weights, mode='wrap')
+
+  bools = (states == 13) | (states == 12 ) | (states == 3)
+
+  return bools.astype(int)
+
+def draw_cross(pixar):
+   (posx, posy) = pygame.mouse.get_pos()
+   pixar[posx, :] = 1
+   pixar[:, posy] = 1
+
+def random_init(n):
+   return np.random.random_integers(0, 1, (n, n))
+
+def draw_pattern(pixar, pattern):
+     print pattern
+
+     if pattern == 'glider':
+      coords = [(0,1), (1,2), (2,0), (2,1), (2,2)]
+     elif pattern == 'block':
+      coords = [(3,3), (3,2), (2,3), (2,2)]
+     elif pattern == 'exploder':
+      coords = [(0,1), (1,2), (2,0), (2,1), (2,2), (3,3)]
+     elif pattern == 'fpentomino':
+      coords = [(2,3),(3,2),(4,2),(3,3),(3,4)]
+
+
+     pos = pygame.mouse.get_pos()
+
+     xs = np.arange(0, pos[0], 10)
+     ys = np.arange(0, pos[1], 10)
+
+     for x in xs:
+        for y in ys:
+           for i, j in coords:
+               pixar[x + i, y + j] = 1
+
+
+def main():
+    pygame.init ()
+
+    N = 400
+    pygame.display.set_mode((N, N))
+    pygame.display.set_caption("Life Demo")
+
+    screen = pygame.display.get_surface()
+
+    pixar = random_init(N)
+    weights = np.array([[1,1,1], [1,10,1], [1,1,1]])
+
+    cross_on = False
+
+    while True:
+       pixar = get_pixar(pixar, weights)
+
+       if cross_on:
+          draw_cross(pixar)
+
+       pygame.surfarray.blit_array(screen, pixar * 255 ** 3)
+       pygame.display.flip()
+
+       for event in pygame.event.get():
+         if event.type == QUIT:
+             return
+         if event.type == MOUSEBUTTONDOWN:
+            cross_on = not cross_on
+         if event.type == KEYDOWN:
+            if event.key == ord('r'):
+               pixar = random_init(N)
+               print "Random init"
+            if event.key == ord('g'):
+               draw_pattern(pixar, 'glider')
+            if event.key == ord('b'):
+               draw_pattern(pixar, 'block')
+            if event.key == ord('e'):
+               draw_pattern(pixar, 'exploder')
+            if event.key == ord('f'):
+               draw_pattern(pixar, 'fpentomino')
+
+
+if __name__ == '__main__':
+    main()
diff --git a/NumPy/Code/ch11code/matplotlib_demo.py b/NumPy/Code/ch11code/matplotlib_demo.py
new file mode 100644
index 0000000..64289f4
--- /dev/null
+++ b/NumPy/Code/ch11code/matplotlib_demo.py
@@ -0,0 +1,76 @@
+import pygame, sys
+from pygame.locals import *
+import numpy as np
+import matplotlib as mpl
+
+mpl.use("Agg")
+
+import matplotlib.pyplot as plt
+import matplotlib.backends.backend_agg as agg
+
+fig = plt.figure(figsize=[3, 3])
+ax = fig.add_subplot(111)
+canvas = agg.FigureCanvasAgg(fig)
+
+def plot(data):
+   ax.plot(data)
+   canvas.draw()
+   renderer = canvas.get_renderer()
+
+   raw_data = renderer.tostring_rgb()
+   size = canvas.get_width_height()
+
+   return pygame.image.fromstring(raw_data, size, "RGB")
+
+pygame.init()
+clock = pygame.time.Clock()
+screen = pygame.display.set_mode((400, 400))
+
+pygame.display.set_caption('Animating Objects')
+img = pygame.image.load('head.jpg')
+
+steps = np.linspace(20, 360, 40).astype(int)
+right = np.zeros((2, len(steps)))
+down = np.zeros((2, len(steps)))
+left = np.zeros((2, len(steps)))
+up = np.zeros((2, len(steps)))
+
+right[0] = steps
+right[1] = 20
+
+down[0] = 360
+down[1] = steps
+
+left[0] = steps[::-1]
+left[1] = 360
+
+up[0] = 20
+up[1] = steps[::-1]
+
+pos = np.concatenate((right.T, down.T, left.T, up.T))
+i = 0
+history = np.array([])
+surf = plot(history)
+
+while True: 
+   # Erase screen
+   screen.fill((255, 255, 255))
+
+   if i >= len(pos):
+      i = 0
+      surf = plot(history)
+
+
+   screen.blit(img, pos[i])
+   history = np.append(history, pos[i])
+   screen.blit(surf, (100, 100))
+
+   i += 1
+
+   for event in pygame.event.get():
+      if event.type == QUIT:
+         pygame.quit()
+         sys.exit()
+
+   pygame.display.update()
+   clock.tick(30)
diff --git a/NumPy/Code/ch11code/opengl_demo.py b/NumPy/Code/ch11code/opengl_demo.py
new file mode 100644
index 0000000..28df416
--- /dev/null
+++ b/NumPy/Code/ch11code/opengl_demo.py
@@ -0,0 +1,44 @@
+import pygame
+from pygame.locals import *
+import numpy as np
+     
+from OpenGL.GL import *
+from OpenGL.GLU import *
+
+def display_openGL(w, h):
+  pygame.display.set_mode((w,h), pygame.OPENGL|pygame.DOUBLEBUF)
+
+  glClearColor(0.0, 0.0, 0.0, 1.0)
+  glClear(GL_COLOR_BUFFER_BIT|GL_DEPTH_BUFFER_BIT)
+
+  gluOrtho2D(0, w, 0, h)
+
+
+def main():
+    pygame.init()
+    pygame.display.set_caption('OpenGL Demo')
+    DIM = 400
+    display_openGL(DIM, DIM)
+    glColor3f(1.0, 0, 0)
+    vertices = np.array([[0, 0], [DIM/2, DIM], [DIM, 0]])
+    NPOINTS = 9000
+    indices = np.random.random_integers(0, 2, NPOINTS)
+    point = [175.0, 150.0]
+
+    for i in xrange(NPOINTS):
+       glBegin(GL_POINTS)
+       point = (point + vertices[indices[i]])/2.0
+       glVertex2fv(point)
+       glEnd()
+
+    glFlush()
+    pygame.display.flip()
+     
+    while True:
+        for event in pygame.event.get():
+            if event.type == QUIT:
+                return
+
+    
+if __name__ == '__main__':
+  main()
diff --git a/NumPy/Code/ch11code/simplegame.py b/NumPy/Code/ch11code/simplegame.py
new file mode 100644
index 0000000..e1bc280
--- /dev/null
+++ b/NumPy/Code/ch11code/simplegame.py
@@ -0,0 +1,19 @@
+import pygame, sys
+from pygame.locals import *
+
+pygame.init()
+screen = pygame.display.set_mode((400, 300))
+
+pygame.display.set_caption('Hello World!')
+
+while True: 
+   sysFont = pygame.font.SysFont("None", 19)
+   rendered = sysFont.render('Hello World', 0, (255, 100, 100))
+   screen.blit(rendered, (100, 100))
+
+   for event in pygame.event.get():
+      if event.type == QUIT:
+         pygame.quit()
+         sys.exit()
+
+   pygame.display.update()
diff --git a/NumPy/Code/ch11code/surfarray_demo.py b/NumPy/Code/ch11code/surfarray_demo.py
new file mode 100644
index 0000000..6c4aa5a
--- /dev/null
+++ b/NumPy/Code/ch11code/surfarray_demo.py
@@ -0,0 +1,24 @@
+import pygame, sys
+from pygame.locals import *
+import numpy as np
+
+pygame.init()
+img = pygame.image.load('head.jpg')
+pixels = pygame.surfarray.array2d(img)
+X = pixels.shape[0] * 7
+Y = pixels.shape[1] * 7
+screen = pygame.display.set_mode((X, Y))
+pygame.display.set_caption('Surfarray Demo')
+new_pixels = np.tile(pixels, (7, 7)).astype(int)
+
+
+while True: 
+   screen.fill((255, 255, 255))
+   pygame.surfarray.blit_array(screen, new_pixels)
+
+   for event in pygame.event.get():
+      if event.type == QUIT:
+         pygame.quit()
+         sys.exit()
+
+   pygame.display.update()
diff --git a/NumPy/Code/ch1code/README b/NumPy/Code/ch1code/README
new file mode 100644
index 0000000..b7f27bd
--- /dev/null
+++ b/NumPy/Code/ch1code/README
@@ -0,0 +1,17 @@
+Chapter 1 of NumPy Beginners Guide.
+
+Prerequisites:
+   You should have Python and NumPy installed on your system.
+
+There is one program in this chapter that demonstrates vector addition the Python way.
+Run from the command line as follows
+  
+python vectorsum.py n
+
+where n is an integer that specifies the size of the vectors. For example,
+
+python vectorsum.py 1000
+
+The first vector to be added contains the squares of 0 up to n. 
+The second vector contains the cubes of 0 up to n.
+The program prints the last 2 elements of the sum and the elapsed time.
diff --git a/NumPy/Code/ch1code/vectorsum.py b/NumPy/Code/ch1code/vectorsum.py
new file mode 100644
index 0000000..0a99bd7
--- /dev/null
+++ b/NumPy/Code/ch1code/vectorsum.py
@@ -0,0 +1,53 @@
+#!/usr/bin/env/python
+
+import sys
+from datetime import datetime
+import numpy as np
+
+"""
+ Chapter 1 of NumPy Beginners Guide.
+ This program demonstrates vector addition the Python way.
+ Run from the command line as follows
+     
+  python vectorsum.py n
+ 
+ where n is an integer that specifies the size of the vectors.
+
+ The first vector to be added contains the squares of 0 up to n. 
+ The second vector contains the cubes of 0 up to n.
+ The program prints the last 2 elements of the sum and the elapsed time.
+"""
+
+def numpysum(n):
+   a = np.arange(n) ** 2
+   b = np.arange(n) ** 3
+   c = a + b
+
+   return c
+
+def pythonsum(n):
+   a = range(n)
+   b = range(n)
+   c = []
+
+   for i in range(len(a)):
+       a[i] = i ** 2
+       b[i] = i ** 3
+       c.append(a[i] + b[i])
+
+   return c
+   
+
+size = int(sys.argv[1])
+
+start = datetime.now()
+c = pythonsum(size)
+delta = datetime.now() - start
+print "The last 2 elements of the sum", c[-2:]
+print "PythonSum elapsed time in microseconds", delta.microseconds
+
+start = datetime.now()
+c = numpysum(size)
+delta = datetime.now() - start
+print "The last 2 elements of the sum", c[-2:]
+print "NumPySum elapsed time in microseconds", delta.microseconds
diff --git a/NumPy/Code/ch2code/README b/NumPy/Code/ch2code/README
new file mode 100644
index 0000000..30e666d
--- /dev/null
+++ b/NumPy/Code/ch2code/README
@@ -0,0 +1,27 @@
+Chapter 2 Beginning with NumPy fundamentals
+
+The scripts below demonstrate various aspects of
+NumPy arrays and data types.
+
+Run from the commandline with 
+
+python <name of script>
+
+where name of script is one of the following:
+
+arrayattributes.py
+arrayattributes2.py
+arrayconversion.py
+charcodes.py
+dtypeattributes.py
+dtypeattributes2.py
+dtypeconstructors.py
+elementselection.py
+numericaltypes.py
+record.py
+shapemanipulation.py
+slicing.py
+slicing1d.py
+splitting.py
+stacking.py
+
diff --git a/NumPy/Code/ch2code/arrayattributes.py b/NumPy/Code/ch2code/arrayattributes.py
new file mode 100644
index 0000000..03a26d8
--- /dev/null
+++ b/NumPy/Code/ch2code/arrayattributes.py
@@ -0,0 +1,45 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates the dtype and shape attributes
+# of ndarray.
+#
+# Run from the commandline with 
+#
+#  python arrayattributes.py
+a = np.arange(5)
+print "In: a = arange(5)"
+
+print "In: a.dtype"
+print a.dtype
+#Out: dtype('int64')
+print
+
+print "In: a.shape"
+print a.shape
+#Out: (5,)
+print
+
+print "In: a"
+print a
+#Out[4]: array([0, 1, 2, 3, 4])
+print
+
+m = np.array([np.arange(2), np.arange(2)])
+
+print "In: m"
+print m
+#Out: 
+#array([[0, 1],
+#       [0, 1]])
+print
+
+print "In: m.shape"
+print m.shape
+#Out: (2, 2)
+
+print "In: m.dtype"
+print m.dtype
+#Out: dtype('int64')
+print
diff --git a/NumPy/Code/ch2code/arrayattributes2.py b/NumPy/Code/ch2code/arrayattributes2.py
new file mode 100644
index 0000000..e944dbd
--- /dev/null
+++ b/NumPy/Code/ch2code/arrayattributes2.py
@@ -0,0 +1,139 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates ndarray attributes.
+#
+# Run from the commandline with 
+#
+#  python arrayattributes2.py
+b = np.arange(24).reshape(2, 12)
+print "In: b"
+print b
+#Out: 
+#array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11],
+#       [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]])
+
+print "In: b.ndim"
+print b.ndim
+#Out: 2
+
+print "In: b.size"
+print b.size
+#Out: 24
+
+print "In: b.itemsize"
+print b.itemsize
+#Out: 8
+
+print "In: b.nbytes"
+print b.nbytes
+#Out: 192
+
+print "In: b.size * b.itemsize"
+print b.size * b.itemsize
+#Out: 192
+
+print "In: b.resize(6,4)"
+print b.resize(6,4)
+
+print "In: b"
+print b
+#Out: 
+#array([[ 0,  1,  2,  3],
+#       [ 4,  5,  6,  7],
+#       [ 8,  9, 10, 11],
+#       [12, 13, 14, 15],
+#       [16, 17, 18, 19],
+#       [20, 21, 22, 23]])
+
+print "In: b.T"
+print b.T
+#Out: 
+#array([[ 0,  4,  8, 12, 16, 20],
+#       [ 1,  5,  9, 13, 17, 21],
+#       [ 2,  6, 10, 14, 18, 22],
+#       [ 3,  7, 11, 15, 19, 23]])
+
+print "In: b.ndim"
+print b.ndim
+#Out: 1
+
+print "In: b.T"
+print b.T
+#Out: array([0, 1, 2, 3, 4])
+
+
+print "In: b = array([1.j + 1, 2.j + 3])"
+b = np.array([1.j + 1, 2.j + 3])
+
+print "In: b"
+print b
+#Out: array([ 1.+1.j,  3.+2.j])
+
+print "In: b.real"
+print b.real
+#Out: array([ 1.,  3.])
+
+print "In: b.imag"
+print b.imag
+#Out: array([ 1.,  2.])
+
+print "In: b.dtype"
+print b.dtype
+#Out: dtype('complex128')
+
+print "In: b.dtype.str"
+print b.dtype.str
+#Out: '<c16'
+
+
+print "In: b = arange(4).reshape(2,2)"
+b = np.arange(4).reshape(2,2)
+
+print "In: b"
+print b
+#Out: 
+#array([[0, 1],
+#       [2, 3]])
+
+print "In: f = b.flat"
+f = b.flat
+
+print "In: f"
+print f
+#Out: <numpy.flatiter object at 0x103013e00>
+
+print "In: for it in f: print it"
+for it in f: 
+   print it
+#0
+#1
+#2
+#3
+
+print "In: b.flat[2]"
+print b.flat[2]
+#Out: 2
+
+
+print "In: b.flat[[1,3]]"
+print b.flat[[1,3]]
+#Out: array([1, 3])
+
+
+print "In: b"
+print b
+#Out: 
+#array([[7, 7],
+#       [7, 7]])
+
+print "In: b.flat[[1,3]] = 1"
+b.flat[[1,3]] = 1
+
+print "In: b"
+print b
+#Out: 
+#array([[7, 1],
+#       [7, 1]])
+
diff --git a/NumPy/Code/ch2code/arrayconversion.py b/NumPy/Code/ch2code/arrayconversion.py
new file mode 100644
index 0000000..5b1cd48
--- /dev/null
+++ b/NumPy/Code/ch2code/arrayconversion.py
@@ -0,0 +1,44 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates the NumPy record data type.
+#
+# Run from the commandline with 
+#
+#  python arrayconversion.py
+b = np.array([ 1.+1.j,  3.+2.j])
+print "In: b"
+print b
+#Out: array([ 1.+1.j,  3.+2.j])
+
+print "In: b.tolist()"
+print b.tolist()
+#Out: [(1+1j), (3+2j)]
+
+print "In: b.tostring()"
+print b.tostring()
+#Out: '\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x08@\x00\x00\x00\x00\x00\x00\x00@'
+
+print "In: fromstring('\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x08@\x00\x00\x00\x00\x00\x00\x00@', dtype=complex)"
+print np.fromstring('\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\xf0?\x00\x00\x00\x00\x00\x00\x08@\x00\x00\x00\x00\x00\x00\x00@', dtype=complex)
+#Out: array([ 1.+1.j,  3.+2.j]
+
+print "In: fromstring('20:42:52',sep=':', dtype=int)"
+print np.fromstring('20:42:52',sep=':', dtype=int)
+#Out: array([20, 42, 52])
+
+print "In: b"
+print b
+#Out: array([ 1.+1.j,  3.+2.j])
+
+print "In: b.astype(int)"
+print b.astype(int)
+#/usr/local/bin/ipython:1: ComplexWarning: Casting complex values to real discards the imaginary part
+#  #!/usr/bin/python
+#Out: array([1, 3])
+
+print "In: b.astype('complex')"
+print b.astype('complex')
+#Out: array([ 1.+1.j,  3.+2.j])
+
diff --git a/NumPy/Code/ch2code/charcodes.py b/NumPy/Code/ch2code/charcodes.py
new file mode 100644
index 0000000..ce75d71
--- /dev/null
+++ b/NumPy/Code/ch2code/charcodes.py
@@ -0,0 +1,19 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates the NumPy dtype character codes.
+#
+# Run from the commandline with 
+#
+#  python charcodes.py
+
+print "In: arange(7, dtype='f')"
+print np.arange(7, dtype='f')
+#Out: array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.], dtype=float32)
+
+print "In: arange(7, dtype='D')"
+print np.arange(7, dtype='D')
+#Out: array([ 0.+0.j,  1.+0.j,  2.+0.j,  3.+0.j,  4.+0.j,  5.+0.j,  6.+0.j])
+
+
diff --git a/NumPy/Code/ch2code/dtypeattributes.py b/NumPy/Code/ch2code/dtypeattributes.py
new file mode 100644
index 0000000..02ee135
--- /dev/null
+++ b/NumPy/Code/ch2code/dtypeattributes.py
@@ -0,0 +1,24 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates the NumPy 
+# dtype.byteorder and dtype.itemsize
+#
+# Run from the commandline with 
+#
+#  python dtypeattributes.py
+
+
+print "In: a = array([[1,2],[3,4]])"
+a = np.array([[1,2],[3,4]])
+
+print "In: a.dtype.byteorder"
+print a.dtype.byteorder
+#Out: '='
+
+print "In: a.dtype.itemsize"
+print a.dtype.itemsize
+#Out: 8
+
+
diff --git a/NumPy/Code/ch2code/dtypeattributes2.py b/NumPy/Code/ch2code/dtypeattributes2.py
new file mode 100644
index 0000000..81b7329
--- /dev/null
+++ b/NumPy/Code/ch2code/dtypeattributes2.py
@@ -0,0 +1,27 @@
+import numpy as np
+
+# Chapter2 Beginning with NumPy fundamentals
+#
+# Demonstrates the NumPy 
+# dtype attributes
+#
+# Run from the commandline with 
+#
+#  python dtypeattributes2.py
+print "In: t = dtype('Float64')"
+t = np.dtype('Float64')
+
+print "In: t.char"
+print t.char
+#Out: 'd'
+
+print "In: t.type"
+print t.type
+#Out: <type 'numpy.float64'>
+
+print "In: t.str"
+print t.str
+#Out: '<f8'
+
+
+
diff --git a/NumPy/Code/ch2code/dtypeconstructors.py b/NumPy/Code/ch2code/dtypeconstructors.py
new file mode 100644
index 0000000..ba5f901
--- /dev/null
+++ b/NumPy/Code/ch2code/dtypeconstructors.py
@@ -0,0 +1,31 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates the NumPy dtype constructors.
+#
+# Run from the commandline with 
+#
+#  python dtypeconstructors.py
+print "In: dtype(float)"
+print np.dtype(float)
+#Out: dtype('float64')
+
+print "In: dtype('f')"
+print np.dtype('f')
+#Out: dtype('float32')
+
+
+print "In: dtype('d')"
+print np.dtype('d')
+#Out: dtype('float64')
+
+print "In: dtype('f8')"
+print np.dtype('f8')
+#Out: dtype('float64')
+
+
+print "In: dtype('Float64')"
+print np.dtype('Float64')
+#Out: dtype('float64')
+
diff --git a/NumPy/Code/ch2code/elementselection.py b/NumPy/Code/ch2code/elementselection.py
new file mode 100644
index 0000000..2de8176
--- /dev/null
+++ b/NumPy/Code/ch2code/elementselection.py
@@ -0,0 +1,34 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates the selection
+# of ndarray elements.
+#
+# Run from the commandline with 
+#
+#  python elementselection.py
+a = np.array([[1,2],[3,4]])
+
+print "In: a"
+print a
+#Out: 
+#array([[1, 2],
+#       [3, 4]])
+
+print "In: a[0,0]"
+print a[0,0]
+#Out: 1
+
+print "In: a[0,1]"
+print a[0,1]
+#Out: 2
+
+print "In: a[1,0]"
+print a[1,0]
+#Out: 3
+
+print "In: a[1,1]"
+print a[1,1]
+#Out: 4 
+
diff --git a/NumPy/Code/ch2code/numericaltypes.py b/NumPy/Code/ch2code/numericaltypes.py
new file mode 100644
index 0000000..a5ef097
--- /dev/null
+++ b/NumPy/Code/ch2code/numericaltypes.py
@@ -0,0 +1,48 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates the NumPy numerical types
+#  and conversion between them.
+#
+# Run from the commandline with 
+#
+#  python numericaltypes.py
+
+print "In: float64(42)"
+print np.float64(42)
+#Out: 42.0
+
+print "In: int8(42.0)"
+print np.int8(42.0)
+#Out: 42
+
+print "In: bool(42)"
+print np.bool(42)
+#Out: True
+print np.bool(0)
+
+print "In: bool(42.0)"
+print np.bool(42.0)
+#Out: True
+
+print "In: float(True)"
+print np.float(True)
+#Out: 1.0
+print np.float(False)
+
+print "In: arange(7, dtype=uint16)"
+print np.arange(7, dtype=np.uint16)
+#Out: array([0, 1, 2, 3, 4, 5, 6], dtype=uint16)
+
+
+print "In: int(42.0 + 1.j)"
+try:
+   print np.int(42.0 + 1.j)
+except TypeError:
+   print "TypeError"
+#Type error
+
+print "In: float(42.0 + 1.j)"
+print float(42.0 + 1.j)
+#Type error
diff --git a/NumPy/Code/ch2code/record.py b/NumPy/Code/ch2code/record.py
new file mode 100644
index 0000000..42d86b8
--- /dev/null
+++ b/NumPy/Code/ch2code/record.py
@@ -0,0 +1,27 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates the NumPy record data type.
+#
+# Run from the commandline with 
+#
+#  python record.py
+print "In: t = dtype([('name', numpy.str_, 40), ('numitems', numpy.int32), ('price', numpy.float32)])"
+t = np.dtype([('name', np.str_, 40), ('numitems', np.int32), ('price', np.float32)])
+print t
+#Out: dtype([('name', '|S40'), ('numitems', '<i4'), ('price', '<f4')])
+
+print "In: t['name']"
+print t['name']
+#Out: dtype('|S40')
+
+
+print "In: itemz = array([('Meaning of life DVD', 42, 3.14), ('Butter', 13, 2.72)], dtype=t)"
+itemz = np.array([('Meaning of life DVD', 42, 3.14), ('Butter', 13, 2.72)], dtype=t)
+
+
+print "In: itemz[1]"
+print itemz[1]
+#Out: ('Butter', 13, 2.7200000286102295)
+
diff --git a/NumPy/Code/ch2code/shapemanipulation.py b/NumPy/Code/ch2code/shapemanipulation.py
new file mode 100644
index 0000000..36730f6
--- /dev/null
+++ b/NumPy/Code/ch2code/shapemanipulation.py
@@ -0,0 +1,66 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates multi dimensional arrays slicing.
+#
+# Run from the commandline with 
+#
+#  python shapemanipulation.py
+print "In: b = arange(24).reshape(2,3,4)"
+b = np.arange(24).reshape(2,3,4)
+
+print "In: b"
+print b
+#Out: 
+#array([[[ 0,  1,  2,  3],
+#        [ 4,  5,  6,  7],
+#        [ 8,  9, 10, 11]],
+#
+#       [[12, 13, 14, 15],
+#        [16, 17, 18, 19],
+#        [20, 21, 22, 23]]])
+
+print "In: b.ravel()"
+print b.ravel()
+#Out: 
+#array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
+#       17, 18, 19, 20, 21, 22, 23])
+
+print "In: b.flatten()"
+print b.flatten()
+#Out: 
+#array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16,
+#       17, 18, 19, 20, 21, 22, 23])
+
+print "In: b.shape = (6,4)"
+b.shape = (6,4)
+
+print "In: b"
+print b
+#Out: 
+#array([[ 0,  1,  2,  3],
+#       [ 4,  5,  6,  7],
+#       [ 8,  9, 10, 11],
+#       [12, 13, 14, 15],
+#       [16, 17, 18, 19],
+#       [20, 21, 22, 23]])
+
+print "In: b.transpose()"
+print b.transpose()
+#Out: 
+#array([[ 0,  4,  8, 12, 16, 20],
+#       [ 1,  5,  9, 13, 17, 21],
+#       [ 2,  6, 10, 14, 18, 22],
+#       [ 3,  7, 11, 15, 19, 23]])
+
+
+print "In: b.resize((2,12))"
+b.resize((2,12))
+
+print "In: b"
+print b
+#Out: 
+#array([[ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11],
+#       [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]])
+
diff --git a/NumPy/Code/ch2code/slicing.py b/NumPy/Code/ch2code/slicing.py
new file mode 100644
index 0000000..f4d4966
--- /dev/null
+++ b/NumPy/Code/ch2code/slicing.py
@@ -0,0 +1,123 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates multi dimensional arrays slicing.
+#
+# Run from the commandline with 
+#
+#  python slicing.py
+print "In: b = arange(24).reshape(2,3,4)"
+b = np.arange(24).reshape(2,3,4)
+
+print "In: b.shape"
+print b.shape
+#Out: (2, 3, 4)
+
+print "In: b"
+print b
+#Out: 
+#array([[[ 0,  1,  2,  3],
+#        [ 4,  5,  6,  7],
+#        [ 8,  9, 10, 11]],
+#
+#       [[12, 13, 14, 15],
+#        [16, 17, 18, 19],
+#        [20, 21, 22, 23]]])
+
+
+print "In: b[0,0,0]"
+print b[0,0,0]
+#Out: 0
+
+
+print "In: b[:,0,0]"
+print b[:,0,0]
+#Out: array([ 0, 12])
+
+print "In: b[0]"
+print b[0]
+#Out: 
+#array([[ 0,  1,  2,  3],
+#       [ 4,  5,  6,  7],
+#       [ 8,  9, 10, 11]])
+
+
+print "In: b[0, :, :]"
+print b[0, :, :]
+#Out: 
+#array([[ 0,  1,  2,  3],
+#       [ 4,  5,  6,  7],
+#       [ 8,  9, 10, 11]])
+
+print "In: b[0, ...]"
+print b[0, ...]
+#Out: 
+#array([[ 0,  1,  2,  3],
+#       [ 4,  5,  6,  7],
+#       [ 8,  9, 10, 11]])
+
+
+print "In: b[0,1]"
+print b[0,1]
+#Out: array([4, 5, 6, 7])
+
+
+print "In: b[0,1,::2]"
+print b[0,1,::2]
+#Out: array([4, 6])
+
+
+print "In: b[...,1]"
+print b[...,1]
+#Out: 
+#array([[ 1,  5,  9],
+#       [13, 17, 21]])
+
+print "In: b[:,1]"
+print b[:,1]
+#Out: 
+#array([[ 4,  5,  6,  7],
+#       [16, 17, 18, 19]])
+
+print "In: b[0,:,1]"
+print b[0,:,1]
+#Out: array([1, 5, 9])
+
+print "In: b[0,:,-1]"
+print b[0,:,-1]
+#Out: array([ 3,  7, 11])
+
+print "In: b[0,::-1, -1]"
+print b[0,::-1, -1]
+#Out: array([11,  7,  3])
+
+print "In: b[0,::2,-1]"
+print b[0,::2,-1]
+#Out: array([ 3, 11])
+
+print "In: b[::-1]"
+print b[::-1]
+#Out: 
+#array([[[12, 13, 14, 15],
+#        [16, 17, 18, 19],
+#        [20, 21, 22, 23]],
+#
+#       [[ 0,  1,  2,  3],
+#        [ 4,  5,  6,  7],
+#        [ 8,  9, 10, 11]]])
+
+
+print "In: s = slice(None, None, -1)"
+s = slice(None, None, -1)
+print "In: b[(s, s, s)]"
+print b[(s, s, s)]
+#Out: 
+#array([[[23, 22, 21, 20],
+#        [19, 18, 17, 16],
+#        [15, 14, 13, 12]],
+#
+#       [[11, 10,  9,  8],
+#        [ 7,  6,  5,  4],
+#        [ 3,  2,  1,  0]]])
+
diff --git a/NumPy/Code/ch2code/slicing1d.py b/NumPy/Code/ch2code/slicing1d.py
new file mode 100644
index 0000000..f7e1a7d
--- /dev/null
+++ b/NumPy/Code/ch2code/slicing1d.py
@@ -0,0 +1,39 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates one dimensional arrays slicing.
+#
+# Run from the commandline with 
+#
+#  python slicing1d.py
+
+print "In: a = arange(9)"
+a = np.arange(9)
+
+print "In: a[3:7]"
+print a[3:7]
+#Out: array([3, 4, 5, 6])
+
+print "In: a[:7:2]"
+print a[:7:2]
+#Out: array([0, 2, 4, 6])
+
+print "In: a[::-1]"
+print a[::-1]
+#Out: array([8, 7, 6, 5, 4, 3, 2, 1, 0])
+
+print "In: s = slice(3,7,2)"
+s = slice(3,7,2)
+print "In: a[s]"
+print a[s]
+#Out: array([3, 5])
+
+
+print "In: s = slice(None, None, -1)"
+s = slice(None, None, -1)
+
+print "In: a[s]"
+print a[s]
+#Out: array([8, 7, 6, 5, 4, 3, 2, 1, 0])
+
diff --git a/NumPy/Code/ch2code/splitting.py b/NumPy/Code/ch2code/splitting.py
new file mode 100644
index 0000000..b06f04e
--- /dev/null
+++ b/NumPy/Code/ch2code/splitting.py
@@ -0,0 +1,108 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates array splitting.
+#
+# Run from the commandline with 
+#
+#  python splitting.py
+print "In: a = arange(9).reshape(3, 3)"
+a = np.arange(9).reshape(3, 3)
+
+print "In: a"
+print a
+#Out: 
+#array([[0, 1, 2],
+#       [3, 4, 5],
+#       [6, 7, 8]])
+
+print "In: hsplit(a, 3)"
+print np.hsplit(a, 3)
+#Out: 
+#[array([[0],
+#       [3],
+#       [6]]),
+# array([[1],
+#       [4],
+#       [7]]),
+# array([[2],
+#       [5],
+#       [8]])]
+
+print "In: split(a, 3, axis=1)"
+print np.split(a, 3, axis=1)
+#Out: 
+#[array([[0],
+#       [3],
+#       [6]]),
+# array([[1],
+#       [4],
+#       [7]]),
+# array([[2],
+#       [5],
+#       [8]])]
+
+print "In: vsplit(a, 3)"
+print np.vsplit(a, 3)
+#Out: [array([[0, 1, 2]]), array([[3, 4, 5]]), array([[6, 7, 8]])]
+
+print "In: split(a, 3, axis=0)"
+print np.split(a, 3, axis=0)
+#Out: [array([[0, 1, 2]]), array([[3, 4, 5]]), array([[6, 7, 8]])]
+
+print "In: c = arange(27).reshape(3, 3, 3)"
+c = np.arange(27).reshape(3, 3, 3)
+
+print "In: c"
+print c
+#Out: 
+#array([[[ 0,  1,  2],
+#        [ 3,  4,  5],
+#        [ 6,  7,  8]],
+#
+#       [[ 9, 10, 11],
+#        [12, 13, 14],
+#        [15, 16, 17]],
+#
+#       [[18, 19, 20],
+#        [21, 22, 23],
+#        [24, 25, 26]]])
+
+print "In: dsplit(c, 3)"
+print np.dsplit(c, 3)
+#Out: 
+#[array([[[ 0],
+#        [ 3],
+#        [ 6]],
+#
+#       [[ 9],
+#        [12],
+#        [15]],
+#
+#       [[18],
+#        [21],
+#        [24]]]),
+# array([[[ 1],
+#        [ 4],
+#        [ 7]],
+#
+#       [[10],
+#        [13],
+#        [16]],
+#
+#       [[19],
+#        [22],
+#        [25]]]),
+# array([[[ 2],
+#        [ 5],
+#        [ 8]],
+#
+#       [[11],
+#        [14],
+#        [17]],
+#
+#       [[20],
+#        [23],
+#        [26]]])]
+
diff --git a/NumPy/Code/ch2code/stacking.py b/NumPy/Code/ch2code/stacking.py
new file mode 100644
index 0000000..87f23cc
--- /dev/null
+++ b/NumPy/Code/ch2code/stacking.py
@@ -0,0 +1,138 @@
+import numpy as np
+
+# Chapter 2 Beginning with NumPy fundamentals
+#
+# Demonstrates array stacking.
+#
+# Run from the commandline with 
+#
+#  python stacking.py
+print "In: a = arange(9).reshape(3,3)"
+a = np.arange(9).reshape(3,3)
+
+print "In: a"
+print a
+#Out: 
+#array([[0, 1, 2],
+#       [3, 4, 5],
+#       [6, 7, 8]])
+
+print "In: b = 2 * a"
+b = 2 * a
+
+print "In: b"
+print b
+#Out: 
+#array([[ 0,  2,  4],
+#       [ 6,  8, 10],
+#       [12, 14, 16]])
+
+print "In: hstack((a, b))"
+print np.hstack((a, b))
+#Out: 
+#array([[ 0,  1,  2,  0,  2,  4],
+#       [ 3,  4,  5,  6,  8, 10],
+#       [ 6,  7,  8, 12, 14, 16]])
+
+print "In: concatenate((a, b), axis=1)"
+print np.concatenate((a, b), axis=1)
+#Out: 
+#array([[ 0,  1,  2,  0,  2,  4],
+#       [ 3,  4,  5,  6,  8, 10],
+#       [ 6,  7,  8, 12, 14, 16]])
+
+print "In: vstack((a, b))"
+print np.vstack((a, b))
+#Out: 
+#array([[ 0,  1,  2],
+#       [ 3,  4,  5],
+#       [ 6,  7,  8],
+#       [ 0,  2,  4],
+#       [ 6,  8, 10],
+#       [12, 14, 16]])
+
+print "In: concatenate((a, b), axis=0)"
+print np.concatenate((a, b), axis=0)
+#Out: 
+#array([[ 0,  1,  2],
+#       [ 3,  4,  5],
+#       [ 6,  7,  8],
+#       [ 0,  2,  4],
+#       [ 6,  8, 10],
+#       [12, 14, 16]])
+
+print "In: dstack((a, b))"
+print np.dstack((a, b))
+#Out: 
+#array([[[ 0,  0],
+#        [ 1,  2],
+#        [ 2,  4]],
+#
+#       [[ 3,  6],
+#        [ 4,  8],
+#        [ 5, 10]],
+#
+#       [[ 6, 12],
+#        [ 7, 14],
+#        [ 8, 16]]])
+
+print "In: oned = arange(2)"
+oned = np.arange(2)
+
+print "In: oned"
+print oned
+#Out: array([0, 1])
+
+print "In: twice_oned = 2 * oned"
+twice_oned = 2 * oned
+
+print "In: twice_oned"
+print twice_oned
+#Out: array([0, 2])
+
+print "In: column_stack((oned, twice_oned))"
+print np.column_stack((oned, twice_oned)) 
+#Out: 
+#array([[0, 0],
+#       [1, 2]])
+
+print "In: column_stack((a, b))"
+print np.column_stack((a, b))
+#Out: 
+#array([[ 0,  1,  2,  0,  2,  4],
+#       [ 3,  4,  5,  6,  8, 10],
+#       [ 6,  7,  8, 12, 14, 16]])
+
+print "In: column_stack((a, b)) == hstack((a, b))"
+print np.column_stack((a, b)) == np.hstack((a, b))
+#Out: 
+#array([[ True,  True,  True,  True,  True,  True],
+#       [ True,  True,  True,  True,  True,  True],
+#       [ True,  True,  True,  True,  True,  True]], dtype=bool)
+
+print "In: row_stack((oned, twice_oned))"
+print np.row_stack((oned, twice_oned))
+#Out: 
+#array([[0, 1],
+#       [0, 2]])
+ 
+print "In: row_stack((a, b))"
+print np.row_stack((a, b))
+#Out: 
+#array([[ 0,  1,  2],
+#       [ 3,  4,  5],
+#       [ 6,  7,  8],
+#       [ 0,  2,  4],
+#       [ 6,  8, 10],
+#       [12, 14, 16]])
+
+print "In: row_stack((a,b)) == vstack((a, b))"
+print np.row_stack((a,b)) == np.vstack((a, b))
+#Out: 
+#array([[ True,  True,  True],
+#       [ True,  True,  True],
+#       [ True,  True,  True],
+#       [ True,  True,  True],
+#       [ True,  True,  True],
+#       [ True,  True,  True]], dtype=bool)
+
diff --git a/NumPy/Code/ch3code/README b/NumPy/Code/ch3code/README
new file mode 100644
index 0000000..ad805d3
--- /dev/null
+++ b/NumPy/Code/ch3code/README
@@ -0,0 +1,43 @@
+Chapter 3 Get into terms with commonly used functions
+
+atr.py Calculates the average true range. Run with for instance
+   python atr.py 5, where 5 is the number of days.
+
+bollingerbands.py Calculates and plots Bollinger bands. Run with for instance
+   python bollingerbands.py 5, where 5 is the number of days.
+
+ema.py Calculates and plots the exponential moving average. Run with for instance
+   python ema.py 5
+
+save.py Demonstrates the savetxt function. Run with 
+   python save.py
+   
+linearmodel.py Computes a linear model. Run with for instance
+   python linearmodel.py 5
+
+ndarraymethods.py Demonstrates the methods of ndarray. Run with 
+   python ndarraymethods.py
+
+range.py Calculates price ranges. Run with
+   python range.py
+
+returns.py Calculates simple returns and logarithmic returns. Run with
+   python returns.py
+
+simplestats.py Computes simple statistics. Run with
+   python simplestats.py
+
+sma.py Calculates and plots the simple moving average. Run with for instance
+   python sma.py 5
+
+trendline.py Calculates and plots trendlines. Run with for instance
+   python trendlines.py 5
+
+vwap.py Computes the VWAP. Run with
+   python vwap.py
+
+weekdays.py Analyzes prices based on weekdays. Run with
+   python weekdays.py
+
+weeksummary.py Summarizes historical data per week. Run with
+   python weeksummary.py
diff --git a/NumPy/Code/ch3code/atr.py b/NumPy/Code/ch3code/atr.py
new file mode 100644
index 0000000..8058676
--- /dev/null
+++ b/NumPy/Code/ch3code/atr.py
@@ -0,0 +1,28 @@
+import numpy as np
+import sys
+
+h, l, c = np.loadtxt('data.csv', delimiter=',', usecols=(4, 5, 6), unpack=True)
+
+N = int(sys.argv[1])
+h = h[-N:]
+l = l[-N:]
+
+print "len(h)", len(h), "len(l)", len(l)
+print "Close", c
+previousclose = c[-N -1: -1]
+
+print "len(previousclose)", len(previousclose)
+print "Previous close", previousclose
+truerange = np.maximum(h - l, h - previousclose, previousclose - l) 
+
+print "True range", truerange
+
+atr = np.zeros(N)
+
+atr[0] = np.mean(truerange)
+
+for i in range(1, N):
+   atr[i] = (N - 1) * atr[i - 1] + truerange[i]
+   atr[i] /= N
+
+print "ATR", atr
diff --git a/NumPy/Code/ch3code/bollingerbands.py b/NumPy/Code/ch3code/bollingerbands.py
new file mode 100644
index 0000000..8fb2e8c
--- /dev/null
+++ b/NumPy/Code/ch3code/bollingerbands.py
@@ -0,0 +1,48 @@
+import numpy as np
+import sys
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+
+N = int(sys.argv[1])
+
+weights = np.ones(N) / N
+print "Weights", weights
+
+c = np.loadtxt('data.csv', delimiter=',', usecols=(6,), unpack=True)
+sma = np.convolve(weights, c)[N-1:-N+1]
+deviation = []
+C = len(c)
+
+for i in range(N - 1, C):
+   if i + N < C:
+      dev = c[i: i + N]
+   else:
+      dev = c[-N:]
+   
+   averages = np.zeros(N)
+   averages.fill(sma[i - N - 1])
+   dev = dev - averages 
+   dev = dev ** 2
+   dev = np.sqrt(np.mean(dev))
+   deviation.append(dev)
+
+deviation = 2 * np.array(deviation)
+print len(deviation), len(sma)
+upperBB = sma + deviation
+lowerBB = sma - deviation
+
+c_slice = c[N-1:]
+between_bands = np.where((c_slice < upperBB) & (c_slice > lowerBB))
+
+print lowerBB[between_bands]
+print c[between_bands]
+print upperBB[between_bands]
+between_bands = len(np.ravel(between_bands))
+print "Ratio between bands", float(between_bands)/len(c_slice)
+
+t = np.arange(N - 1, C)
+plot(t, c_slice, lw=1.0)
+plot(t, sma, lw=2.0)
+plot(t, upperBB, lw=3.0)
+plot(t, lowerBB, lw=4.0)
+show()
diff --git a/NumPy/Code/ch3code/data.csv b/NumPy/Code/ch3code/data.csv
new file mode 100644
index 0000000..a8d1222
--- /dev/null
+++ b/NumPy/Code/ch3code/data.csv
@@ -0,0 +1,30 @@
+AAPL,28-01-2011, ,344.17,344.4,333.53,336.1,21144800
+AAPL,31-01-2011, ,335.8,340.04,334.3,339.32,13473000
+AAPL,01-02-2011, ,341.3,345.65,340.98,345.03,15236800
+AAPL,02-02-2011, ,344.45,345.25,343.55,344.32,9242600
+AAPL,03-02-2011, ,343.8,344.24,338.55,343.44,14064100
+AAPL,04-02-2011, ,343.61,346.7,343.51,346.5,11494200
+AAPL,07-02-2011, ,347.89,353.25,347.64,351.88,17322100
+AAPL,08-02-2011, ,353.68,355.52,352.15,355.2,13608500
+AAPL,09-02-2011, ,355.19,359,354.87,358.16,17240800
+AAPL,10-02-2011, ,357.39,360,348,354.54,33162400
+AAPL,11-02-2011, ,354.75,357.8,353.54,356.85,13127500
+AAPL,14-02-2011, ,356.79,359.48,356.71,359.18,11086200
+AAPL,15-02-2011, ,359.19,359.97,357.55,359.9,10149000
+AAPL,16-02-2011, ,360.8,364.9,360.5,363.13,17184100
+AAPL,17-02-2011, ,357.1,360.27,356.52,358.3,18949000
+AAPL,18-02-2011, ,358.21,359.5,349.52,350.56,29144500
+AAPL,22-02-2011, ,342.05,345.4,337.72,338.61,31162200
+AAPL,23-02-2011, ,338.77,344.64,338.61,342.62,23994700
+AAPL,24-02-2011, ,344.02,345.15,338.37,342.88,17853500
+AAPL,25-02-2011, ,345.29,348.43,344.8,348.16,13572000
+AAPL,28-02-2011, ,351.21,355.05,351.12,353.21,14395400
+AAPL,01-03-2011, ,355.47,355.72,347.68,349.31,16290300
+AAPL,02-03-2011, ,349.96,354.35,348.4,352.12,21521000
+AAPL,03-03-2011, ,357.2,359.79,355.92,359.56,17885200
+AAPL,04-03-2011, ,360.07,360.29,357.75,360,16188000
+AAPL,07-03-2011, ,361.11,361.67,351.31,355.36,19504300
+AAPL,08-03-2011, ,354.91,357.4,352.25,355.76,12718000
+AAPL,09-03-2011, ,354.69,354.76,350.6,352.47,16192700
+AAPL,10-03-2011, ,349.69,349.77,344.9,346.67,18138800
+AAPL,11-03-2011, ,345.4,352.32,345,351.99,16824200
diff --git a/NumPy/Code/ch3code/ema.py b/NumPy/Code/ch3code/ema.py
new file mode 100644
index 0000000..0930a58
--- /dev/null
+++ b/NumPy/Code/ch3code/ema.py
@@ -0,0 +1,22 @@
+import numpy as np
+import sys
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+
+x = np.arange(5)
+print "Exp", np.exp(x)
+print "Linspace", np.linspace(-1, 0, 5)
+
+N = int(sys.argv[1])
+
+
+weights = np.exp(np.linspace(-1., 0., N))
+weights /= weights.sum()
+print "Weights", weights
+
+c = np.loadtxt('data.csv', delimiter=',', usecols=(6,), unpack=True)
+ema = np.convolve(weights, c)[N-1:-N+1]
+t = np.arange(N - 1, len(c))
+plot(t, c[N-1:], lw=1.0)
+plot(t, ema, lw=2.0)
+show()
diff --git a/NumPy/Code/ch3code/eye.txt b/NumPy/Code/ch3code/eye.txt
new file mode 100644
index 0000000..0f504d7
--- /dev/null
+++ b/NumPy/Code/ch3code/eye.txt
@@ -0,0 +1,2 @@
+1.000000000000000000e+00 0.000000000000000000e+00
+0.000000000000000000e+00 1.000000000000000000e+00
diff --git a/NumPy/Code/ch3code/genfromtxt.py b/NumPy/Code/ch3code/genfromtxt.py
new file mode 100644
index 0000000..211706b
--- /dev/null
+++ b/NumPy/Code/ch3code/genfromtxt.py
@@ -0,0 +1,5 @@
+import numpy as np
+
+data = np.eye(2)
+np.savetxt("eye.txt", data)
+print np.genfromtxt("eye.txt")
diff --git a/NumPy/Code/ch3code/linearmodel.py b/NumPy/Code/ch3code/linearmodel.py
new file mode 100644
index 0000000..0993857
--- /dev/null
+++ b/NumPy/Code/ch3code/linearmodel.py
@@ -0,0 +1,27 @@
+import numpy as np
+import sys
+
+N = int(sys.argv[1])
+
+c = np.loadtxt('data.csv', delimiter=',', usecols=(6,), unpack=True)
+
+b = c[-N:]
+b = b[::-1]
+print "b", b
+
+A = np.zeros((N, N), float)
+print "Zeros N by N", A
+
+for i in range(N):
+   A[i, ] = c[-N - 1 - i: - 1 - i]
+
+print "A", A
+
+
+(x, residuals, rank, s) = np.linalg.lstsq(A, b)
+
+print x, residuals, rank, s
+
+print np.dot(b, x)
+#352.51614809
+#actual close 353.56 
diff --git a/NumPy/Code/ch3code/ndarraymethods.py b/NumPy/Code/ch3code/ndarraymethods.py
new file mode 100644
index 0000000..2f0d3c1
--- /dev/null
+++ b/NumPy/Code/ch3code/ndarraymethods.py
@@ -0,0 +1,15 @@
+import numpy as np
+
+a = np.arange(5)
+print "a =", a
+print "Clipped", a.clip(1, 2)
+
+a = np.arange(4)
+print a
+print "Compressed", a.compress(a > 2)
+
+b = np.arange(1, 9)
+print "b =", b
+print "Factorial", b.prod()
+
+print "Factorials", b.cumprod()
diff --git a/NumPy/Code/ch3code/range.py b/NumPy/Code/ch3code/range.py
new file mode 100644
index 0000000..4e282fc
--- /dev/null
+++ b/NumPy/Code/ch3code/range.py
@@ -0,0 +1,9 @@
+import numpy as np
+
+h,l=np.loadtxt('data.csv', delimiter=',', usecols=(4,5), unpack=True)
+print "highest =", np.max(h)
+print "lowest =", np.min(l)
+print (np.max(h) + np.min(l)) /2
+
+print "Spread high price", np.ptp(h)
+print "Spread low price", np.ptp(l)
diff --git a/NumPy/Code/ch3code/returns.py b/NumPy/Code/ch3code/returns.py
new file mode 100644
index 0000000..7732693
--- /dev/null
+++ b/NumPy/Code/ch3code/returns.py
@@ -0,0 +1,17 @@
+import numpy as np
+
+c=np.loadtxt('data.csv', delimiter=',', usecols=(6,), unpack=True)
+
+returns = np.diff( c ) / c[ : -1]
+print "Standard deviation =", np.std(returns)
+
+logreturns = np.diff( np.log(c) )
+
+posretindices = np.where(returns > 0)
+print "Indices with positive returns", posretindices
+
+annual_volatility = np.std(logreturns)/np.mean(logreturns)
+annual_volatility = annual_volatility / np.sqrt(1./252.)
+print "Annual volatility", annual_volatility
+
+print "Monthly volatility", annual_volatility * np.sqrt(1./12.)
diff --git a/NumPy/Code/ch3code/save.py b/NumPy/Code/ch3code/save.py
new file mode 100644
index 0000000..7526926
--- /dev/null
+++ b/NumPy/Code/ch3code/save.py
@@ -0,0 +1,5 @@
+import numpy as np
+
+i2 = np.eye(2)
+print i2
+np.savetxt("eye.txt", i2)
diff --git a/NumPy/Code/ch3code/simplestats.py b/NumPy/Code/ch3code/simplestats.py
new file mode 100644
index 0000000..1bdb7b3
--- /dev/null
+++ b/NumPy/Code/ch3code/simplestats.py
@@ -0,0 +1,13 @@
+import numpy as np
+
+c=np.loadtxt('data.csv', delimiter=',', usecols=(6,), unpack=True)
+print "median =", np.median(c)
+sorted = np.msort(c)
+print "sorted =", sorted
+
+N = len(c)
+print "middle =", sorted[(N - 1)/2]
+print "average middle =", (sorted[N /2] + sorted[(N - 1) / 2]) / 2
+
+print "variance =", np.var(c)
+print "variance from definition =", np.mean((c - c.mean())**2)
diff --git a/NumPy/Code/ch3code/sma.py b/NumPy/Code/ch3code/sma.py
new file mode 100644
index 0000000..e8092bb
--- /dev/null
+++ b/NumPy/Code/ch3code/sma.py
@@ -0,0 +1,16 @@
+import numpy as np
+import sys
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+
+N = int(sys.argv[1])
+
+weights = np.ones(N) / N
+print "Weights", weights
+
+c = np.loadtxt('data.csv', delimiter=',', usecols=(6,), unpack=True)
+sma = np.convolve(weights, c)[N-1:-N+1]
+t = np.arange(N - 1, len(c))
+plot(t, c[N-1:], lw=1.0)
+plot(t, sma, lw=2.0)
+show()
diff --git a/NumPy/Code/ch3code/trendline.py b/NumPy/Code/ch3code/trendline.py
new file mode 100644
index 0000000..2e9954b
--- /dev/null
+++ b/NumPy/Code/ch3code/trendline.py
@@ -0,0 +1,41 @@
+import numpy as np
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+
+def fit_line(t, y):
+   A = np.vstack([t, np.ones_like(t)]).T
+
+   return np.linalg.lstsq(A, y)[0]
+
+h, l, c = np.loadtxt('data.csv', delimiter=',', usecols=(4, 5, 6), unpack=True)
+
+pivots = (h + l + c) / 3
+print "Pivots", pivots
+
+t = np.arange(len(c))
+sa, sb = fit_line(t, pivots - (h - l)) 
+ra, rb = fit_line(t, pivots + (h - l))
+
+support = sa * t + sb
+resistance = ra * t + rb 
+condition = (c > support) & (c < resistance)
+print "Condition", condition
+between_bands = np.where(condition) 
+print support[between_bands]
+print c[between_bands]
+print resistance[between_bands]
+between_bands = len(np.ravel(between_bands))
+print "Number points between bands", between_bands
+print "Ratio between bands", float(between_bands)/len(c) 
+
+print "Tomorrows support", sa * (t[-1] + 1) + sb
+print "Tomorrows resistance", ra * (t[-1] + 1) + rb
+
+a1 = c[c > support]
+a2 = c[c < resistance]
+print "Number of points between bands 2nd approach" ,len(np.intersect1d(a1, a2))
+
+plot(t, c)
+plot(t, support)
+plot(t, resistance)
+show()
diff --git a/NumPy/Code/ch3code/vwap.py b/NumPy/Code/ch3code/vwap.py
new file mode 100644
index 0000000..96ec4ac
--- /dev/null
+++ b/NumPy/Code/ch3code/vwap.py
@@ -0,0 +1,10 @@
+import numpy as np
+
+c,v=np.loadtxt('data.csv', delimiter=',', usecols=(6,7), unpack=True)
+vwap = np.average(c, weights=v)
+print "VWAP =", vwap
+
+print "mean =", np.mean(c)
+
+t = np.arange(len(c))
+print "twap =", np.average(c, weights=t)
diff --git a/NumPy/Code/ch3code/weekdays.py b/NumPy/Code/ch3code/weekdays.py
new file mode 100644
index 0000000..bcbfdf0
--- /dev/null
+++ b/NumPy/Code/ch3code/weekdays.py
@@ -0,0 +1,34 @@
+import numpy as np
+from datetime import datetime
+
+# Monday 0
+# Tuesday 1
+# Wednesday 2
+# Thursday 3
+# Friday 4
+# Saturday 5
+# Sunday 6
+def datestr2num(s):
+   return datetime.strptime(s, "%d-%m-%Y").date().weekday()
+
+dates, close=np.loadtxt('data.csv', delimiter=',', usecols=(1,6), converters={1: datestr2num}, unpack=True)
+print "Dates =", dates
+
+averages = np.zeros(5)
+
+for i in range(5):
+   indices = np.where(dates == i) 
+   prices = np.take(close, indices)
+   avg = np.mean(prices)
+   print "Day", i, "prices", prices, "Average", avg
+   averages[i] = avg
+
+
+top = np.max(averages)
+print "Highest average", top
+print "Top day of the week", np.argmax(averages)
+
+bottom = np.min(averages)
+print "Lowest average", bottom
+print "Bottom day of the week", np.argmin(averages)
+
diff --git a/NumPy/Code/ch3code/weeksummary.csv b/NumPy/Code/ch3code/weeksummary.csv
new file mode 100644
index 0000000..e3dcf2b
--- /dev/null
+++ b/NumPy/Code/ch3code/weeksummary.csv
@@ -0,0 +1,3 @@
+APPL,335.8,346.7,334.3,346.5
+APPL,347.8,360.0,347.6,356.8
+APPL,356.7,364.9,349.5,350.5
diff --git a/NumPy/Code/ch3code/weeksummary.py b/NumPy/Code/ch3code/weeksummary.py
new file mode 100644
index 0000000..3336e95
--- /dev/null
+++ b/NumPy/Code/ch3code/weeksummary.py
@@ -0,0 +1,43 @@
+import numpy as np
+from datetime import datetime
+
+# Monday 0
+# Tuesday 1
+# Wednesday 2
+# Thursday 3
+# Friday 4
+# Saturday 5
+# Sunday 6
+def datestr2num(s):
+   return datetime.strptime(s, "%d-%m-%Y").date().weekday()
+
+dates, open, high, low, close=np.loadtxt('data.csv', delimiter=',', usecols=(1, 3, 4, 5, 6), converters={1: datestr2num}, unpack=True)
+close = close[:16]
+dates = dates[:16]
+
+# get first Monday
+first_monday = np.ravel(np.where(dates == 0))[0]
+print "The first Monday index is", first_monday
+
+# get last Friday
+last_friday = np.ravel(np.where(dates == 4))[-1]
+print "The last Friday index is", last_friday
+
+weeks_indices = np.arange(first_monday, last_friday + 1)
+print "Weeks indices initial", weeks_indices
+
+weeks_indices = np.split(weeks_indices, 3)
+print "Weeks indices after split", weeks_indices
+
+def summarize(a, o, h, l, c):
+    monday_open = o[a[0]]
+    week_high = np.max( np.take(h, a) )
+    week_low = np.min( np.take(l, a) )
+    friday_close = c[a[-1]]
+
+    return("APPL", monday_open, week_high, week_low, friday_close)
+
+weeksummary = np.apply_along_axis(summarize, 1, weeks_indices, open, high, low, close)
+print "Week summary", weeksummary
+
+np.savetxt("weeksummary.csv", weeksummary, delimiter=",", fmt="%s")
diff --git a/NumPy/Code/ch4code/__MACOSX/ch4code/._.DS_Store b/NumPy/Code/ch4code/__MACOSX/ch4code/._.DS_Store
new file mode 100644
index 0000000..a9dcab0
Binary files /dev/null and b/NumPy/Code/ch4code/__MACOSX/ch4code/._.DS_Store differ
diff --git a/NumPy/Code/ch4code/ch4code/.DS_Store b/NumPy/Code/ch4code/ch4code/.DS_Store
new file mode 100644
index 0000000..5008ddf
Binary files /dev/null and b/NumPy/Code/ch4code/ch4code/.DS_Store differ
diff --git a/NumPy/Code/ch4code/ch4code/BHP.csv b/NumPy/Code/ch4code/ch4code/BHP.csv
new file mode 100644
index 0000000..5207c3c
--- /dev/null
+++ b/NumPy/Code/ch4code/ch4code/BHP.csv
@@ -0,0 +1,30 @@
+BHP,11-02-2011, ,93.11,94.26,92.9,93.72,1741900
+BHP,14-02-2011, ,94.57,96.23,94.39,95.64,2620800
+BHP,15-02-2011, ,94.45,95.47,93.91,94.56,2461300
+BHP,16-02-2011, ,92.67,93.58,92.56,93.3,3270900
+BHP,17-02-2011, ,92.65,93.98,92.58,93.93,2650200
+BHP,18-02-2011, ,92.34,93,92,92.39,4667300
+BHP,22-02-2011, ,93.14,93.98,91.75,92.11,5359800
+BHP,23-02-2011, ,91.93,92.46,91.05,92.36,7768400
+BHP,24-02-2011, ,92.42,92.71,90.93,91.76,4799100
+BHP,25-02-2011, ,93.48,94.04,92.44,93.91,3448300
+BHP,28-02-2011, ,94.81,95.11,94.1,94.6,4719800
+BHP,01-03-2011, ,95.05,95.2,93.13,93.27,3898900
+BHP,02-03-2011, ,93.89,94.89,93.54,94.43,3727700
+BHP,03-03-2011, ,95.9,96.11,95.18,96.02,3379400
+BHP,04-03-2011, ,96.12,96.44,95.08,95.76,2463900
+BHP,07-03-2011, ,96.51,96.66,94.03,94.47,3590900
+BHP,08-03-2011, ,93.72,94.47,92.9,94.34,3805000
+BHP,09-03-2011, ,92.94,93.13,91.86,92.22,3271700
+BHP,10-03-2011, ,89,89.17,87.93,88.31,5507800
+BHP,11-03-2011, ,88.24,89.8,88.16,89.59,2996800
+BHP,14-03-2011, ,88.17,89.06,87.82,89.02,3434800
+BHP,15-03-2011, ,84.58,87.32,84.35,86.95,5008300
+BHP,16-03-2011, ,86.31,87.28,83.85,84.88,7809799
+BHP,17-03-2011, ,87.32,88.29,86.89,87.38,3947100
+BHP,18-03-2011, ,89.53,89.58,88.05,88.56,3809700
+BHP,21-03-2011, ,90.13,90.16,88.88,89.59,3098200
+BHP,22-03-2011, ,89.5,89.59,88.42,88.71,3500200
+BHP,23-03-2011, ,89.57,90.32,88.85,90.02,4285600
+BHP,24-03-2011, ,90.86,91.35,89.7,91.26,3918800
+BHP,25-03-2011, ,90.42,91.09,90.07,90.67,3632200
diff --git a/NumPy/Code/ch4code/ch4code/README b/NumPy/Code/ch4code/ch4code/README
new file mode 100644
index 0000000..aa16395
--- /dev/null
+++ b/NumPy/Code/ch4code/ch4code/README
@@ -0,0 +1,21 @@
+Chapter 4 Convenience functions for your convenience
+
+The following scripts are part of the chapter 4 code:
+
+correlation.py 
+   Run with python correlation.py
+
+mode.py
+   Run with python mode.py
+
+obv.py
+   Run with python obv.py
+
+polynomials.py
+   Run with python polynomials.py 3
+
+simulation.py
+   Run with python simulation.py 0.999
+
+smoothing.py
+   Run with python smoothing.py 8
diff --git a/NumPy/Code/ch4code/ch4code/VALE.csv b/NumPy/Code/ch4code/ch4code/VALE.csv
new file mode 100644
index 0000000..d0e1d25
--- /dev/null
+++ b/NumPy/Code/ch4code/ch4code/VALE.csv
@@ -0,0 +1,30 @@
+VALE,11-02-2011, ,33.88,34.54,33.63,34.37,18433500
+VALE,14-02-2011, ,34.53,35.29,34.52,35.13,20780700
+VALE,15-02-2011, ,34.89,35.31,34.82,35.14,17756700
+VALE,16-02-2011, ,35.16,35.4,34.81,35.31,16792800
+VALE,17-02-2011, ,35.18,35.6,35.04,35.57,24088300
+VALE,18-02-2011, ,35.31,35.37,34.89,35.03,21286600
+VALE,22-02-2011, ,33.94,34.57,33.36,33.44,28364700
+VALE,23-02-2011, ,33.43,34.12,33.1,33.94,22559300
+VALE,24-02-2011, ,34.3,34.3,33.56,34.21,20591900
+VALE,25-02-2011, ,34.67,34.95,34.05,34.27,20151500
+VALE,28-02-2011, ,34.34,34.51,33.7,34.23,16126000
+VALE,01-03-2011, ,34.39,34.44,33.68,33.76,17282400
+VALE,02-03-2011, ,33.61,34.5,33.57,34.32,15870900
+VALE,03-03-2011, ,34.77,34.89,34.53,34.87,14648200
+VALE,04-03-2011, ,34.67,34.83,34.04,34.5,15330800
+VALE,07-03-2011, ,34.43,34.53,32.97,33.23,25040500
+VALE,08-03-2011, ,33.22,33.7,32.55,33.29,17093000
+VALE,09-03-2011, ,33.23,33.44,32.68,32.88,20026300
+VALE,10-03-2011, ,32.17,32.4,31.68,31.91,30803900
+VALE,11-03-2011, ,31.53,32.42,31.49,32.17,24429900
+VALE,14-03-2011, ,32.03,32.45,31.74,32.44,15525500
+VALE,15-03-2011, ,30.99,31.93,30.79,31.91,24767700
+VALE,16-03-2011, ,31.99,32.03,30.68,31.04,30394153
+VALE,17-03-2011, ,31.44,31.82,31.32,31.51,24035000
+VALE,18-03-2011, ,32.17,32.39,31.98,32.14,19740600
+VALE,21-03-2011, ,32.81,32.85,32.26,32.42,18923700
+VALE,22-03-2011, ,32.13,32.32,31.74,32.25,18934200
+VALE,23-03-2011, ,32.39,32.91,32.22,32.7,18359900
+VALE,24-03-2011, ,32.82,32.94,32.12,32.36,25894100
+VALE,25-03-2011, ,32.26,32.74,31.93,32.34,16688900
diff --git a/NumPy/Code/ch4code/ch4code/correlation.py b/NumPy/Code/ch4code/ch4code/correlation.py
new file mode 100644
index 0000000..a8cb19e
--- /dev/null
+++ b/NumPy/Code/ch4code/ch4code/correlation.py
@@ -0,0 +1,32 @@
+import numpy as np
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+
+bhp = np.loadtxt('BHP.csv', delimiter=',', usecols=(6,), unpack=True)
+
+bhp_returns = np.diff(bhp) / bhp[ : -1]
+
+vale = np.loadtxt('VALE.csv', delimiter=',', usecols=(6,), unpack=True)
+
+vale_returns = np.diff(vale) / vale[ : -1]
+
+covariance = np.cov(bhp_returns, vale_returns) 
+print "Covariance", covariance
+
+print "Covariance diagonal", covariance.diagonal()
+print "Covariance trace", covariance.trace()
+
+print covariance/ (bhp_returns.std() * vale_returns.std())
+
+print "Correlation coefficient", np.corrcoef(bhp_returns, vale_returns)
+
+difference = bhp - vale
+avg = np.mean(difference)
+dev = np.std(difference)
+
+print "Out of sync", np.abs(difference[-1] - avg) > 2 * dev
+
+t = np.arange(len(bhp_returns))
+plot(t, bhp_returns, lw=1)
+plot(t, vale_returns, lw=2)
+show()
diff --git a/NumPy/Code/ch4code/ch4code/obv.py b/NumPy/Code/ch4code/ch4code/obv.py
new file mode 100644
index 0000000..29de42e
--- /dev/null
+++ b/NumPy/Code/ch4code/ch4code/obv.py
@@ -0,0 +1,17 @@
+import numpy as np
+
+c, v=np.loadtxt('BHP.csv', delimiter=',', usecols=(6, 7), unpack=True)
+
+change = np.diff(c)
+print "Change", change
+
+signs = np.sign(change)
+print "Signs", signs
+
+pieces = np.piecewise(change, [change < 0, change > 0], [-1, 1])
+print "Pieces", pieces
+
+print "Arrays equal?", np.array_equal(signs, pieces)
+
+print "On balance volume", v[1:] * signs
+
diff --git a/NumPy/Code/ch4code/ch4code/polynomials.py b/NumPy/Code/ch4code/ch4code/polynomials.py
new file mode 100644
index 0000000..7231671
--- /dev/null
+++ b/NumPy/Code/ch4code/ch4code/polynomials.py
@@ -0,0 +1,28 @@
+import numpy as np
+import sys
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+
+bhp=np.loadtxt('BHP.csv', delimiter=',', usecols=(6,), unpack=True)
+
+vale=np.loadtxt('VALE.csv', delimiter=',', usecols=(6,), unpack=True)
+
+t = np.arange(len(bhp))
+poly = np.polyfit(t, bhp - vale, int(sys.argv[1]))
+print "Polynomial fit", poly
+
+print "Next value", np.polyval(poly, t[-1] + 1)
+
+print "Roots", np.roots(poly)
+
+der = np.polyder(poly)
+print "Derivative", der
+
+print "Extremas", np.roots(der)
+vals = np.polyval(poly, t)
+print np.argmax(vals)
+print np.argmin(vals)
+
+plot(t, bhp - vale)
+plot(t, vals)
+show()
diff --git a/NumPy/Code/ch4code/ch4code/simulation.py b/NumPy/Code/ch4code/ch4code/simulation.py
new file mode 100644
index 0000000..a84cd2e
--- /dev/null
+++ b/NumPy/Code/ch4code/ch4code/simulation.py
@@ -0,0 +1,30 @@
+import numpy as np
+import sys
+
+o, h, l, c = np.loadtxt('BHP.csv', delimiter=',', usecols=(3, 4, 5, 6), unpack=True)
+
+def calc_profit(open, high, low, close):
+   #buy just below the open
+   buy = open * float(sys.argv[1])
+
+   # daily range
+   if low <  buy < high:
+      return (close - buy)/buy
+   else:
+      return 0
+
+func = np.vectorize(calc_profit)
+profits = func(o, h, l, c)
+print "Profits", profits
+
+real_trades = profits[profits != 0]
+print "Number of trades", len(real_trades), round(100.0 * len(real_trades)/len(c), 2), "%"
+print "Average profit/loss %", round(np.mean(real_trades) * 100, 2)
+
+winning_trades = profits[profits > 0]
+print "Number of winning trades", len(winning_trades), round(100.0 * len(winning_trades)/len(c), 2), "%"
+print "Average profit %", round(np.mean(winning_trades) * 100, 2)
+
+losing_trades = profits[profits < 0]
+print "Number of losing trades", len(losing_trades), round(100.0 * len(losing_trades)/len(c), 2), "%"
+print "Average loss %", round(np.mean(losing_trades) * 100, 2)
diff --git a/NumPy/Code/ch4code/ch4code/smoothing.py b/NumPy/Code/ch4code/ch4code/smoothing.py
new file mode 100644
index 0000000..1d1c24e
--- /dev/null
+++ b/NumPy/Code/ch4code/ch4code/smoothing.py
@@ -0,0 +1,42 @@
+import numpy as np
+import sys
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+
+N = int(sys.argv[1])
+
+weights = np.hanning(N)
+print "Weights", weights
+
+bhp = np.loadtxt('BHP.csv', delimiter=',', usecols=(6,), unpack=True)
+bhp_returns = np.diff(bhp) / bhp[ : -1]
+smooth_bhp = np.convolve(weights/weights.sum(), bhp_returns)[N-1:-N+1]
+
+vale = np.loadtxt('VALE.csv', delimiter=',', usecols=(6,), unpack=True)
+vale_returns = np.diff(vale) / vale[ : -1]
+smooth_vale = np.convolve(weights/weights.sum(), vale_returns)[N-1:-N+1]
+
+K = int(sys.argv[1])
+t = np.arange(N - 1, len(bhp_returns))
+poly_bhp = np.polyfit(t, smooth_bhp, K)
+poly_vale = np.polyfit(t, smooth_vale, K)
+
+poly_sub = np.polysub(poly_bhp, poly_vale)
+xpoints = np.roots(poly_sub)
+print "Intersection points", xpoints
+
+reals = np.isreal(xpoints)
+print "Real number?", reals
+
+xpoints = np.select([reals], [xpoints])
+xpoints = xpoints.real
+print "Real intersection points", xpoints
+
+print "Sans 0s", np.trim_zeros(xpoints)
+
+plot(t, bhp_returns[N-1:], lw=1.0)
+plot(t, smooth_bhp, lw=2.0)
+
+plot(t, vale_returns[N-1:], lw=1.0)
+plot(t, smooth_vale, lw=2.0)
+show()
diff --git a/NumPy/Code/ch5code/README b/NumPy/Code/ch5code/README
new file mode 100644
index 0000000..fdd488b
--- /dev/null
+++ b/NumPy/Code/ch5code/README
@@ -0,0 +1,40 @@
+Chapter 5 Working with matrices and ufuncs
+
+The accompanying code demonstrates NumPy matrices and universal functions.
+These are the Python scripts:
+
+answer42.py Returns 42.
+   Run with python answer42.py
+
+bittwiddling.py Demonstrates bitwise and comparison functions.
+   Run with python bittwiddling.py
+
+bmatcreation.py Demonstrates matrix creation with the bmat function.
+   Run with python bmatcreation.py
+
+dividing.py Demonstrates the NumPy division functions.
+   Run with python dividing.py
+
+fibonacci.py Shows calculation of Fibonacci numbers.
+   Run with python fibonacci.py
+
+lissajous.py Draws Lissajous figuresa and requires Matplotlib.
+   Run with python lissajous.py 9 8
+
+matrixcreation.py Demonstrates matrix creation.
+   Run with python matrixcreation.py
+
+modulo.py Demonstrates the modulo operation.
+   Run with python modulo.py
+
+sawtooth.py Draws a sawtooth wave and requires Matplotlib.
+   Run with python sawtooth.py 99
+
+squarewave.py Draws a square wave and requires Matplotlib.
+   Run with python squarewave.py 99
+
+ufuncattributes.py Demonstrates the attributes of universal functions.
+   Run with python ufuncattributes.py
+
+ufuncmethods.py Demonstrates universal functions methods.
+   Run with python ufuncmethods.py
diff --git a/NumPy/Code/ch5code/answer42.py b/NumPy/Code/ch5code/answer42.py
new file mode 100644
index 0000000..1ce1a2d
--- /dev/null
+++ b/NumPy/Code/ch5code/answer42.py
@@ -0,0 +1,12 @@
+import numpy as np
+
+def ultimate_answer(a):
+   result = np.zeros_like(a)
+   result.flat = 42
+
+   return result
+
+ufunc = np.frompyfunc(ultimate_answer, 1, 1) 
+print "The answer", ufunc(np.arange(4))
+
+print "The answer", ufunc(np.arange(4).reshape(2, 2))
diff --git a/NumPy/Code/ch5code/bittwiddling.py b/NumPy/Code/ch5code/bittwiddling.py
new file mode 100644
index 0000000..0ac8c44
--- /dev/null
+++ b/NumPy/Code/ch5code/bittwiddling.py
@@ -0,0 +1,10 @@
+import numpy as np
+
+x = np.arange(-9, 9)
+y = -x
+print "Sign different?", (x ^ y) < 0
+print "Sign different?", np.less(np.bitwise_xor(x, y), 0)
+print "Power of 2?\n", x, "\n", (x & (x - 1)) == 0
+print "Power of 2?\n", x, "\n", np.equal(np.bitwise_and(x,  (x - 1)), 0)
+print "Modulus 4\n", x, "\n", x & ((1 << 2) - 1)
+print "Modulus 4\n", x, "\n", np.bitwise_and(x, np.left_shift(1, 2) - 1)
diff --git a/NumPy/Code/ch5code/bmatcreation.py b/NumPy/Code/ch5code/bmatcreation.py
new file mode 100644
index 0000000..b32b719
--- /dev/null
+++ b/NumPy/Code/ch5code/bmatcreation.py
@@ -0,0 +1,8 @@
+import numpy as np
+
+A = np.eye(2)
+print "A", A
+B = 2 * A
+print "B", B
+print "Compound matrix\n", np.bmat("A B; A B")
+
diff --git a/NumPy/Code/ch5code/dividing.py b/NumPy/Code/ch5code/dividing.py
new file mode 100644
index 0000000..bd03836
--- /dev/null
+++ b/NumPy/Code/ch5code/dividing.py
@@ -0,0 +1,14 @@
+from __future__ import division
+import numpy as np
+
+a = np.array([2, 6, 5])
+b = np.array([1, 2, 3])
+
+print "Divide", np.divide(a, b), np.divide(b, a)
+print "True Divide", np.true_divide(a, b), np.true_divide(b, a)
+print "Floor Divide", np.floor_divide(a, b), np.floor_divide(b, a)
+c = 3.14 * b
+print "Floor Divide 2", np.floor_divide(c, b), np.floor_divide(b, c)
+print "/ operator", a/b, b/a
+print "// operator", a//b, b//a
+print "// operator 2", c//b, b//c
diff --git a/NumPy/Code/ch5code/fibonacci.py b/NumPy/Code/ch5code/fibonacci.py
new file mode 100644
index 0000000..344474b
--- /dev/null
+++ b/NumPy/Code/ch5code/fibonacci.py
@@ -0,0 +1,13 @@
+import numpy as np
+
+F = np.matrix([[1, 1], [1, 0]])
+print "F", F
+print "8th Fibonacci", (F ** 7)[0, 0]
+n = np.arange(1, 9)
+
+sqrt5 = np.sqrt(5)
+phi = (1 + sqrt5)/2
+fibonacci = np.rint((phi**n - (-1/phi)**n)/sqrt5)
+print "Fibonacci", fibonacci
+
+
diff --git a/NumPy/Code/ch5code/lissajous.py b/NumPy/Code/ch5code/lissajous.py
new file mode 100644
index 0000000..09e69c2
--- /dev/null
+++ b/NumPy/Code/ch5code/lissajous.py
@@ -0,0 +1,13 @@
+import numpy as np
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+import sys
+
+a = float(sys.argv[1])
+b = float(sys.argv[2])
+t = np.linspace(-np.pi, np.pi, 201)
+x = np.sin(a * t + np.pi/2)
+y = np.sin(b * t)
+plot(x, y)
+show()
+
diff --git a/NumPy/Code/ch5code/matrixcreation.py b/NumPy/Code/ch5code/matrixcreation.py
new file mode 100644
index 0000000..51a3168
--- /dev/null
+++ b/NumPy/Code/ch5code/matrixcreation.py
@@ -0,0 +1,9 @@
+import numpy as np
+
+A = np.mat('1 2 3; 4 5 6; 7 8 9')
+print "Creation from string", A
+print "transpose A", A.T
+print "Inverse A", A.I
+print "Check Inverse", A * A.I 
+
+print "Creation from array", np.mat(np.arange(9).reshape(3, 3))
diff --git a/NumPy/Code/ch5code/modulo.py b/NumPy/Code/ch5code/modulo.py
new file mode 100644
index 0000000..05e09b2
--- /dev/null
+++ b/NumPy/Code/ch5code/modulo.py
@@ -0,0 +1,8 @@
+import numpy as np
+
+a = np.arange(-4, 4)
+
+print "Remainder", np.remainder(a, 2)
+print "Mod", np.mod(a, 2)
+print "% operator", a % 2
+print "Fmod", np.fmod(a, 2)
diff --git a/NumPy/Code/ch5code/sawtooth.py b/NumPy/Code/ch5code/sawtooth.py
new file mode 100644
index 0000000..a6c5758
--- /dev/null
+++ b/NumPy/Code/ch5code/sawtooth.py
@@ -0,0 +1,16 @@
+import numpy as np
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+import sys
+
+t = np.linspace(-np.pi, np.pi, 201)
+k = np.arange(1, float(sys.argv[1]))
+f = np.zeros_like(t)
+
+for i in range(len(t)):
+   f[i] = np.sum(np.sin(2 * np.pi * k * t[i])/k)
+
+f = (-2 / np.pi) * f
+plot(t, f, lw=1.0)
+plot(t, np.abs(f), lw=2.0)
+show()
diff --git a/NumPy/Code/ch5code/squarewave.py b/NumPy/Code/ch5code/squarewave.py
new file mode 100644
index 0000000..0c58e4a
--- /dev/null
+++ b/NumPy/Code/ch5code/squarewave.py
@@ -0,0 +1,16 @@
+import numpy as np
+from matplotlib.pyplot import plot
+from matplotlib.pyplot import show
+import sys
+
+t = np.linspace(-np.pi, np.pi, 201)
+k = np.arange(1, float(sys.argv[1]))
+k = 2 * k - 1
+f = np.zeros_like(t)
+
+for i in range(len(t)):
+   f[i] = np.sum(np.sin(k * t[i])/k)
+
+f = (4 / np.pi) * f
+plot(t, f)
+show()
diff --git a/NumPy/Code/ch5code/trigonometry.py b/NumPy/Code/ch5code/trigonometry.py
new file mode 100644
index 0000000..f29cf8c
--- /dev/null
+++ b/NumPy/Code/ch5code/trigonometry.py
@@ -0,0 +1,7 @@
+import numpy as np
+from pylab import *
+
+x = np.linspace(-np.pi, np.pi, 2001)
+sines = np.sin(x)
+hist(np.arctanh(np.clip(sines, -0.999, 0.999)), bins=40)
+show()
diff --git a/NumPy/Code/ch5code/ufuncattributes.py b/NumPy/Code/ch5code/ufuncattributes.py
new file mode 100644
index 0000000..a7489e7
--- /dev/null
+++ b/NumPy/Code/ch5code/ufuncattributes.py
@@ -0,0 +1,9 @@
+import numpy as np
+
+print "Docstring", np.add.__doc__
+print "Name", np.add.__name__
+print "Nin", np.add.nin
+print "Nout", np.add.nout
+print "Nargs", np.add.nargs
+print "Ntypes", np.add.ntypes
+print "Types", np.add.types
diff --git a/NumPy/Code/ch5code/ufuncmethods.py b/NumPy/Code/ch5code/ufuncmethods.py
new file mode 100644
index 0000000..e83dcfb
--- /dev/null
+++ b/NumPy/Code/ch5code/ufuncmethods.py
@@ -0,0 +1,12 @@
+import numpy as np
+
+a = np.arange(9)
+
+print "Reduce", np.add.reduce(a)
+print "Accumulate", np.add.accumulate(a)
+print "Reduceat", np.add.reduceat(a, [0, 5, 2, 7])
+print "Reduceat step I", np.add.reduce(a[0:5])
+print "Reduceat step II", a[5]
+print "Reduceat step III", np.add.reduce(a[2:7])
+print "Reduceat step IV", np.add.reduce(a[7:])
+print "Outer", np.add.outer(np.arange(3), a)
diff --git a/NumPy/Code/ch6code/README b/NumPy/Code/ch6code/README
new file mode 100644
index 0000000..9a00df5
--- /dev/null
+++ b/NumPy/Code/ch6code/README
@@ -0,0 +1,47 @@
+NumPy Beginner's Guide
+Chapter 6 Move further with NumPy Modules
+
+The following scripts below are part of the example code. 
+Python and NumPy is required for most of the scripts,
+for some Matplotlib is also needed.
+
+
+Every script can be run with the command
+
+python <name of script>
+
+decomposition.py  
+   Demonstrates the svd function.
+
+determinant.py 
+   Demonstrates the det function.
+
+eigenvalues.py 
+   Demonstrates the eig and eigvals functions.
+
+fourier.py  
+   Demonstrates the fft and ifft functions.
+
+fouriershift.py   
+   Demonstrates the fftshift and ifftshift functions.
+
+headortail.py 
+   Demonstrates the binomial function.
+   
+inversion.py 
+   Demonstrates the inv function.
+
+lognormaldist.py 
+   Demonstrates the lognormal function.
+
+normaldist.py 
+   Demonstrates the normal function.
+
+pseudoinversion.py 
+   Demonstrates the pinv function.
+
+solution.py 
+   Demonstrates the solve function.
+
+urn.py 
+   Demonstrates the hypergeometric function.
diff --git a/NumPy/Code/ch6code/decomposition.py b/NumPy/Code/ch6code/decomposition.py
new file mode 100644
index 0000000..0c5c224
--- /dev/null
+++ b/NumPy/Code/ch6code/decomposition.py
@@ -0,0 +1,17 @@
+import numpy as np
+
+A = np.mat("4 11 14;8 7 -2")
+print "A\n", A
+
+U, Sigma, V = np.linalg.svd(A, full_matrices=False)
+
+print "U"
+print U
+
+print "Sigma"
+print Sigma
+
+print "V"
+print V
+
+print "Product\n", U * np.diag(Sigma) * V
diff --git a/NumPy/Code/ch6code/determinant.py b/NumPy/Code/ch6code/determinant.py
new file mode 100644
index 0000000..761131b
--- /dev/null
+++ b/NumPy/Code/ch6code/determinant.py
@@ -0,0 +1,6 @@
+import numpy as np
+
+A = np.mat("3 4;5 6")
+print "A\n", A
+
+print "Determinant", np.linalg.det(A)
diff --git a/NumPy/Code/ch6code/dice.py b/NumPy/Code/ch6code/dice.py
new file mode 100644
index 0000000..b10ce64
--- /dev/null
+++ b/NumPy/Code/ch6code/dice.py
@@ -0,0 +1,17 @@
+import numpy as np
+from pylab import *
+
+N = 10000
+outcome = np.random.geometric(1.0/6.0, size=N)
+enemy = np.zeros(N) 
+enemy[0] = outcome[0]
+
+for i in range(1, len(outcome)):
+   enemy[i] = outcome[i] + enemy[i - 1]
+
+us = 6 * np.arange(1, len(enemy) + 1)
+t = np.arange(N)
+
+plot(t, enemy, lw=1)
+plot(t, us, lw=2)
+show()
diff --git a/NumPy/Code/ch6code/eigenvalues.py b/NumPy/Code/ch6code/eigenvalues.py
new file mode 100644
index 0000000..f298ab0
--- /dev/null
+++ b/NumPy/Code/ch6code/eigenvalues.py
@@ -0,0 +1,15 @@
+import numpy as np
+
+A = np.mat("3 -2;1 0")
+print "A\n", A
+
+print "Eigenvalues", np.linalg.eigvals(A) 
+
+eigenvalues, eigenvectors = np.linalg.eig(A)
+print "First tuple of eig", eigenvalues
+print "Second tuple of eig\n", eigenvectors
+
+for i in range(len(eigenvalues)):
+      print "Left", np.dot(A, eigenvectors[:,i])
+      print "Right", eigenvalues[i] * eigenvectors[:,i]
+      print
diff --git a/NumPy/Code/ch6code/fourier.py b/NumPy/Code/ch6code/fourier.py
new file mode 100644
index 0000000..1c11813
--- /dev/null
+++ b/NumPy/Code/ch6code/fourier.py
@@ -0,0 +1,10 @@
+import numpy as np
+from matplotlib.pyplot import plot, show
+
+x =  np.linspace(0, 2 * np.pi, 30)
+wave = np.cos(x)
+transformed = np.fft.fft(wave)
+print np.all(np.abs(np.fft.ifft(transformed) - wave) < 10 ** -9)
+
+plot(transformed)
+show()
diff --git a/NumPy/Code/ch6code/fouriershift.py b/NumPy/Code/ch6code/fouriershift.py
new file mode 100644
index 0000000..4adaef1
--- /dev/null
+++ b/NumPy/Code/ch6code/fouriershift.py
@@ -0,0 +1,12 @@
+import numpy as np
+from matplotlib.pyplot import plot, show
+
+x =  np.linspace(0, 2 * np.pi, 30)
+wave = np.cos(x)
+transformed = np.fft.fft(wave)
+shifted = np.fft.fftshift(transformed)
+print np.all(np.abs(np.fft.ifftshift(shifted) - transformed) < 10 ** -9)
+
+plot(transformed, lw=2)
+plot(shifted, lw=3)
+show()
diff --git a/NumPy/Code/ch6code/headortail.py b/NumPy/Code/ch6code/headortail.py
new file mode 100644
index 0000000..4a81017
--- /dev/null
+++ b/NumPy/Code/ch6code/headortail.py
@@ -0,0 +1,20 @@
+import numpy as np
+from matplotlib.pyplot import plot, show 
+
+cash = np.zeros(10000)
+cash[0] = 1000
+outcome = np.random.binomial(9, 0.5, size=len(cash))
+
+for i in range(1, len(cash)):
+
+   if outcome[i] < 5:
+      cash[i] = cash[i - 1] - 1
+   elif outcome[i] < 10:
+      cash[i] = cash[i - 1] + 1
+   else:
+      raise AssertionError("Unexpected outcome " + outcome)
+
+print outcome.min(), outcome.max() 
+
+plot(np.arange(len(cash)), cash)
+show()
diff --git a/NumPy/Code/ch6code/inversion.py b/NumPy/Code/ch6code/inversion.py
new file mode 100644
index 0000000..8b7edc5
--- /dev/null
+++ b/NumPy/Code/ch6code/inversion.py
@@ -0,0 +1,9 @@
+import numpy as np
+
+A = np.mat("0 1 2;1 0 3;4 -3 8")
+print "A\n", A
+
+inverse = np.linalg.inv(A)
+print "inverse of A\n", inverse
+
+print "Check\n", A * inverse
diff --git a/NumPy/Code/ch6code/lognormaldist.py b/NumPy/Code/ch6code/lognormaldist.py
new file mode 100644
index 0000000..b643ee9
--- /dev/null
+++ b/NumPy/Code/ch6code/lognormaldist.py
@@ -0,0 +1,12 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+N=10000
+lognormal_values = np.random.lognormal(size=N)
+dummy, bins, dummy = plt.hist(lognormal_values, np.sqrt(N), normed=True, lw=1)
+sigma = 1
+mu = 0
+x = np.linspace(min(bins), max(bins), len(bins))
+pdf = np.exp(-(np.log(x) - mu)**2 / (2 * sigma**2))/ (x * sigma * np.sqrt(2 * np.pi))
+plt.plot(x, pdf,lw=3)
+plt.show()
diff --git a/NumPy/Code/ch6code/normaldist.py b/NumPy/Code/ch6code/normaldist.py
new file mode 100644
index 0000000..ed5ce32
--- /dev/null
+++ b/NumPy/Code/ch6code/normaldist.py
@@ -0,0 +1,11 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+N=10000
+
+normal_values = np.random.normal(size=N)
+dummy, bins, dummy = plt.hist(normal_values, np.sqrt(N), normed=True, lw=1)
+sigma = 1
+mu = 0
+plt.plot(bins, 1/(sigma * np.sqrt(2 * np.pi)) * np.exp( - (bins - mu)**2 / (2 * sigma**2) ),lw=2)
+plt.show()
diff --git a/NumPy/Code/ch6code/pseudoinversion.py b/NumPy/Code/ch6code/pseudoinversion.py
new file mode 100644
index 0000000..1726d25
--- /dev/null
+++ b/NumPy/Code/ch6code/pseudoinversion.py
@@ -0,0 +1,9 @@
+import numpy as np
+
+A = np.mat("4 11 14;8 7 -2")
+print "A\n", A
+
+pseudoinv = np.linalg.pinv(A)
+print "Pseudo inverse\n", pseudoinv
+
+print "Check", A * pseudoinv
diff --git a/NumPy/Code/ch6code/solution.py b/NumPy/Code/ch6code/solution.py
new file mode 100644
index 0000000..c09e443
--- /dev/null
+++ b/NumPy/Code/ch6code/solution.py
@@ -0,0 +1,12 @@
+import numpy as np
+
+A = np.mat("1 -2 1;0 2 -8;-4 5 9")
+print "A\n", A
+
+b = np.array([0, 8, -9])
+print "b\n", b
+
+x = np.linalg.solve(A, b)
+print "Solution", x
+
+print "Check\n", np.dot(A , x)
diff --git a/NumPy/Code/ch6code/urn.py b/NumPy/Code/ch6code/urn.py
new file mode 100644
index 0000000..e4b4c25
--- /dev/null
+++ b/NumPy/Code/ch6code/urn.py
@@ -0,0 +1,16 @@
+import numpy as np
+from matplotlib.pyplot import plot, show
+
+points = np.zeros(100)
+outcomes = np.random.hypergeometric(25, 1, 3, size=len(points))
+
+for i in range(len(points)):
+   if outcomes[i] == 3:
+      points[i] = points[i - 1] + 1
+   elif outcomes[i] == 2:
+      points[i] = points[i - 1] - 6
+   else:
+      print outcomes[i]
+
+plot(np.arange(len(points)), points)
+show()
diff --git a/NumPy/Code/ch7code/.DS_Store b/NumPy/Code/ch7code/.DS_Store
new file mode 100644
index 0000000..5008ddf
Binary files /dev/null and b/NumPy/Code/ch7code/.DS_Store differ
diff --git a/NumPy/Code/ch7code/AAPL.csv b/NumPy/Code/ch7code/AAPL.csv
new file mode 100644
index 0000000..a8d1222
--- /dev/null
+++ b/NumPy/Code/ch7code/AAPL.csv
@@ -0,0 +1,30 @@
+AAPL,28-01-2011, ,344.17,344.4,333.53,336.1,21144800
+AAPL,31-01-2011, ,335.8,340.04,334.3,339.32,13473000
+AAPL,01-02-2011, ,341.3,345.65,340.98,345.03,15236800
+AAPL,02-02-2011, ,344.45,345.25,343.55,344.32,9242600
+AAPL,03-02-2011, ,343.8,344.24,338.55,343.44,14064100
+AAPL,04-02-2011, ,343.61,346.7,343.51,346.5,11494200
+AAPL,07-02-2011, ,347.89,353.25,347.64,351.88,17322100
+AAPL,08-02-2011, ,353.68,355.52,352.15,355.2,13608500
+AAPL,09-02-2011, ,355.19,359,354.87,358.16,17240800
+AAPL,10-02-2011, ,357.39,360,348,354.54,33162400
+AAPL,11-02-2011, ,354.75,357.8,353.54,356.85,13127500
+AAPL,14-02-2011, ,356.79,359.48,356.71,359.18,11086200
+AAPL,15-02-2011, ,359.19,359.97,357.55,359.9,10149000
+AAPL,16-02-2011, ,360.8,364.9,360.5,363.13,17184100
+AAPL,17-02-2011, ,357.1,360.27,356.52,358.3,18949000
+AAPL,18-02-2011, ,358.21,359.5,349.52,350.56,29144500
+AAPL,22-02-2011, ,342.05,345.4,337.72,338.61,31162200
+AAPL,23-02-2011, ,338.77,344.64,338.61,342.62,23994700
+AAPL,24-02-2011, ,344.02,345.15,338.37,342.88,17853500
+AAPL,25-02-2011, ,345.29,348.43,344.8,348.16,13572000
+AAPL,28-02-2011, ,351.21,355.05,351.12,353.21,14395400
+AAPL,01-03-2011, ,355.47,355.72,347.68,349.31,16290300
+AAPL,02-03-2011, ,349.96,354.35,348.4,352.12,21521000
+AAPL,03-03-2011, ,357.2,359.79,355.92,359.56,17885200
+AAPL,04-03-2011, ,360.07,360.29,357.75,360,16188000
+AAPL,07-03-2011, ,361.11,361.67,351.31,355.36,19504300
+AAPL,08-03-2011, ,354.91,357.4,352.25,355.76,12718000
+AAPL,09-03-2011, ,354.69,354.76,350.6,352.47,16192700
+AAPL,10-03-2011, ,349.69,349.77,344.9,346.67,18138800
+AAPL,11-03-2011, ,345.4,352.32,345,351.99,16824200
diff --git a/NumPy/Code/ch7code/README b/NumPy/Code/ch7code/README
new file mode 100644
index 0000000..e4b7b1a
--- /dev/null
+++ b/NumPy/Code/ch7code/README
@@ -0,0 +1,27 @@
+NumPy Beginner's Guide
+
+Chapter 7 Peeking into special functions
+
+Execute the Python example scripts of this chapter
+with
+
+   python <name script>
+
+bessel0.py Demonstrates the i0 function.
+extracted.py Demonstrates the extract function.
+futurevalue.py Demonstrates the fv function.
+interestrate.py Demonstrates the rate function.
+internalratereturn.py Demonstrates the irr function.
+lex.py Demonstrates the lexsort function.
+netpresentvalue.py Demonstrates npv function.
+numberpayments.py Demonstrates the nper function.
+payment.py Demonstrates the pmt function.
+plot_bartlett.py Demonstrates the bartlett function.
+plot_blackman.py Demonstrates the blackman function.
+plot_hamming.py Demonstrates the hamming function.
+plot_kaiser.py Demonstrates the kaiser function.
+plot_sinc.py Demonstrates the sinc function.
+presentvalue.py Demonstrates the pv function.
+sinc2d.py Demonstrates the sinc function in 2D.
+sortcomplex.py Demonstrates the sort_complex function.
+sortedsearch.py Demonstrates the searchsorted function.
diff --git a/NumPy/Code/ch7code/bessel0.py b/NumPy/Code/ch7code/bessel0.py
new file mode 100644
index 0000000..bbcad3f
--- /dev/null
+++ b/NumPy/Code/ch7code/bessel0.py
@@ -0,0 +1,8 @@
+import numpy as np
+from pylab import *
+
+x = np.linspace(0, 4, 100)
+vals = np.i0(x)
+
+plot(x, vals)
+show()
diff --git a/NumPy/Code/ch7code/extracted.py b/NumPy/Code/ch7code/extracted.py
new file mode 100644
index 0000000..8602e8d
--- /dev/null
+++ b/NumPy/Code/ch7code/extracted.py
@@ -0,0 +1,6 @@
+import numpy as np
+
+a = np.arange(7)
+condition = (a % 2) == 0
+print "Even numbers", np.extract(condition, a)
+print "Non zero", np.nonzero(a)
diff --git a/NumPy/Code/ch7code/futurevalue.py b/NumPy/Code/ch7code/futurevalue.py
new file mode 100644
index 0000000..5470822
--- /dev/null
+++ b/NumPy/Code/ch7code/futurevalue.py
@@ -0,0 +1,12 @@
+import numpy as np
+from matplotlib.pyplot import plot, show
+
+print "Future value", np.fv(0.03/4, 5 * 4, -10, -1000)
+
+fvals = []
+
+for i in xrange(1, 10):
+   fvals.append(np.fv(.03/4, i * 4, -10, -1000))
+
+plot(fvals, 'bo')
+show()
diff --git a/NumPy/Code/ch7code/interestrate.py b/NumPy/Code/ch7code/interestrate.py
new file mode 100644
index 0000000..4beacc4
--- /dev/null
+++ b/NumPy/Code/ch7code/interestrate.py
@@ -0,0 +1,3 @@
+import numpy as np
+
+print "Interest rate", 12 * np.rate(167, -100, 9000, 0)
diff --git a/NumPy/Code/ch7code/internalratereturn.py b/NumPy/Code/ch7code/internalratereturn.py
new file mode 100644
index 0000000..ebd4725
--- /dev/null
+++ b/NumPy/Code/ch7code/internalratereturn.py
@@ -0,0 +1,3 @@
+import numpy as np
+
+print "Internal rate of return", np.irr([-100, 38, 48, 90, 17, 36])
diff --git a/NumPy/Code/ch7code/lex.py b/NumPy/Code/ch7code/lex.py
new file mode 100644
index 0000000..07eb56e
--- /dev/null
+++ b/NumPy/Code/ch7code/lex.py
@@ -0,0 +1,11 @@
+import numpy as np
+import datetime
+
+def datestr2num(s):
+   return datetime.datetime.strptime(s, "%d-%m-%Y").toordinal()
+
+dates,closes=np.loadtxt('AAPL.csv', delimiter=',', usecols=(1, 6), converters={1:datestr2num}, unpack=True)
+indices = np.lexsort((dates, closes))
+
+print "Indices", indices
+print ["%s %s" % (datetime.date.fromordinal(int(dates[i])),  closes[i]) for i in indices]
diff --git a/NumPy/Code/ch7code/modifiedratereturn.py b/NumPy/Code/ch7code/modifiedratereturn.py
new file mode 100644
index 0000000..9838c9a
--- /dev/null
+++ b/NumPy/Code/ch7code/modifiedratereturn.py
@@ -0,0 +1,3 @@
+import numpy as np
+
+print "Modified internal rate of return", np.mirr([-100, 38, 48, 90, 17, 36], 0.03, 0.03)
diff --git a/NumPy/Code/ch7code/netpresentvalue.py b/NumPy/Code/ch7code/netpresentvalue.py
new file mode 100644
index 0000000..b9797ed
--- /dev/null
+++ b/NumPy/Code/ch7code/netpresentvalue.py
@@ -0,0 +1,7 @@
+import numpy as np
+
+cashflows = np.random.randint(100, size=5)
+cashflows = np.insert(cashflows, 0, -100)
+print "Cashflows", cashflows
+
+print "Net present value", np.npv(0.03, cashflows)
diff --git a/NumPy/Code/ch7code/numberpayments.py b/NumPy/Code/ch7code/numberpayments.py
new file mode 100644
index 0000000..6eadaae
--- /dev/null
+++ b/NumPy/Code/ch7code/numberpayments.py
@@ -0,0 +1,3 @@
+import numpy as np
+
+print "Number of payments", np.nper(0.10/12, -100, 9000)
diff --git a/NumPy/Code/ch7code/payment.py b/NumPy/Code/ch7code/payment.py
new file mode 100644
index 0000000..b53f366
--- /dev/null
+++ b/NumPy/Code/ch7code/payment.py
@@ -0,0 +1,3 @@
+import numpy as np
+
+print "Payment", np.pmt(0.01/12, 12 * 30, 10000000) 
diff --git a/NumPy/Code/ch7code/plot_bartlett.py b/NumPy/Code/ch7code/plot_bartlett.py
new file mode 100644
index 0000000..badf5ac
--- /dev/null
+++ b/NumPy/Code/ch7code/plot_bartlett.py
@@ -0,0 +1,6 @@
+import numpy as np
+from matplotlib.pyplot import plot, show
+
+window = np.bartlett(42)
+plot(window)
+show()
diff --git a/NumPy/Code/ch7code/plot_blackman.py b/NumPy/Code/ch7code/plot_blackman.py
new file mode 100644
index 0000000..11f6004
--- /dev/null
+++ b/NumPy/Code/ch7code/plot_blackman.py
@@ -0,0 +1,14 @@
+import numpy as np
+from matplotlib.pyplot import plot, show, legend
+from matplotlib.dates import datestr2num
+import sys
+
+
+closes=np.loadtxt('AAPL.csv', delimiter=',', usecols=(6,), converters={1:datestr2num}, unpack=True)
+N = int(sys.argv[1])
+window = np.blackman(N)
+smoothed = np.convolve(window/window.sum(), closes, mode='same')
+plot(smoothed[N:-N], lw=2, label="smoothed")
+plot(closes[N:-N], label="closes")
+legend(loc='best')
+show()
diff --git a/NumPy/Code/ch7code/plot_hamming.py b/NumPy/Code/ch7code/plot_hamming.py
new file mode 100644
index 0000000..9bc3cdb
--- /dev/null
+++ b/NumPy/Code/ch7code/plot_hamming.py
@@ -0,0 +1,7 @@
+import numpy as np
+from pylab import *
+
+window = np.hamming(42)
+plot(window)
+show()
+
diff --git a/NumPy/Code/ch7code/plot_kaiser.py b/NumPy/Code/ch7code/plot_kaiser.py
new file mode 100644
index 0000000..130a001
--- /dev/null
+++ b/NumPy/Code/ch7code/plot_kaiser.py
@@ -0,0 +1,6 @@
+import numpy as np
+from pylab import *
+
+window = np.kaiser(42, 0)
+plot(window)
+show()
diff --git a/NumPy/Code/ch7code/plot_sinc.py b/NumPy/Code/ch7code/plot_sinc.py
new file mode 100644
index 0000000..6549777
--- /dev/null
+++ b/NumPy/Code/ch7code/plot_sinc.py
@@ -0,0 +1,8 @@
+import numpy as np
+from matplotlib.pyplot import plot, show
+
+x = np.linspace(0, 4, 100)
+vals = np.sinc(x)
+
+plot(x, vals)
+show()
diff --git a/NumPy/Code/ch7code/presentvalue.py b/NumPy/Code/ch7code/presentvalue.py
new file mode 100644
index 0000000..b076bf0
--- /dev/null
+++ b/NumPy/Code/ch7code/presentvalue.py
@@ -0,0 +1,3 @@
+import numpy as np
+
+print "Present value", np.pv(0.03/4, 5 * 4, -10, 1376.09633204)
diff --git a/NumPy/Code/ch7code/sinc2d.py b/NumPy/Code/ch7code/sinc2d.py
new file mode 100644
index 0000000..6bc8787
--- /dev/null
+++ b/NumPy/Code/ch7code/sinc2d.py
@@ -0,0 +1,9 @@
+import numpy as np
+from matplotlib.pyplot import imshow, show
+
+x = np.linspace(0, 4, 100)
+xx = np.outer(x, x)
+vals = np.sinc(xx)
+
+imshow(vals)
+show()
diff --git a/NumPy/Code/ch7code/sortcomplex.py b/NumPy/Code/ch7code/sortcomplex.py
new file mode 100644
index 0000000..878a883
--- /dev/null
+++ b/NumPy/Code/ch7code/sortcomplex.py
@@ -0,0 +1,7 @@
+import numpy as np
+
+np.random.seed(42)
+complex_numbers = np.random.random(5) + 1j * np.random.random(5)
+print "Complex numbers\n", complex_numbers
+
+print "Sorted\n", np.sort_complex(complex_numbers)
diff --git a/NumPy/Code/ch7code/sortedsearch.py b/NumPy/Code/ch7code/sortedsearch.py
new file mode 100644
index 0000000..fbd3152
--- /dev/null
+++ b/NumPy/Code/ch7code/sortedsearch.py
@@ -0,0 +1,7 @@
+import numpy as np
+
+a = np.arange(5)
+indices = np.searchsorted(a, [-2, 7])
+print "Indices", indices
+
+print "The full array", np.insert(a, indices, [-2, 7])
diff --git a/NumPy/Code/ch8code/README b/NumPy/Code/ch8code/README
new file mode 100644
index 0000000..3f20b2f
--- /dev/null
+++ b/NumPy/Code/ch8code/README
@@ -0,0 +1,17 @@
+NumPy Beginner's Guide
+
+Chapter 8 Assuring quality with testing
+
+NumPy 1.3+ required. Run the scripts with 
+
+python <name of script>
+
+almostequal.py Demonstrates the assert_almost_equal function.
+approxequal.py Demonstrates the assert_approx_equal function.
+arrayalmostequal.py Demonstrates the assert_array_almost_equal function.
+arrayequal.py Demonstrates the assert_array_equal function.
+arrayless.py Demonstrates the assert_array_less function.
+equal.py Demonstrates the assert_equal function.
+maxulp.py Demonstrates the assert_array_max_ulp function.
+nulp.py Demonstrates the assert_almost_equal_nulp function.
+stringequal.py Demonstrates the assert_string_equal function.
diff --git a/NumPy/Code/ch8code/almostequal.py b/NumPy/Code/ch8code/almostequal.py
new file mode 100644
index 0000000..a47bf81
--- /dev/null
+++ b/NumPy/Code/ch8code/almostequal.py
@@ -0,0 +1,4 @@
+import numpy as np
+
+print "Decimal 6", np.testing.assert_almost_equal(0.123456789, 0.123456780, decimal=7)
+print "Decimal 7", np.testing.assert_almost_equal(0.123456789, 0.123456780, decimal=8)
diff --git a/NumPy/Code/ch8code/approxequal.py b/NumPy/Code/ch8code/approxequal.py
new file mode 100644
index 0000000..cad07de
--- /dev/null
+++ b/NumPy/Code/ch8code/approxequal.py
@@ -0,0 +1,4 @@
+import numpy as np
+
+print "Significance 8", np.testing.assert_approx_equal(0.123456789, 0.123456780, significant=8)
+print "Significance 9", np.testing.assert_approx_equal(0.123456789, 0.123456780, significant=9)
diff --git a/NumPy/Code/ch8code/arrayalmostequal.py b/NumPy/Code/ch8code/arrayalmostequal.py
new file mode 100644
index 0000000..2249624
--- /dev/null
+++ b/NumPy/Code/ch8code/arrayalmostequal.py
@@ -0,0 +1,4 @@
+import numpy as np
+
+print "Decimal 8", np.testing.assert_array_almost_equal([0, 0.123456789], [0, 0.123456780], decimal=8)
+print "Decimal 9", np.testing.assert_array_almost_equal([0, 0.123456789], [0, 0.123456780], decimal=9)
diff --git a/NumPy/Code/ch8code/arrayequal.py b/NumPy/Code/ch8code/arrayequal.py
new file mode 100644
index 0000000..1262a02
--- /dev/null
+++ b/NumPy/Code/ch8code/arrayequal.py
@@ -0,0 +1,4 @@
+import numpy as np
+
+print "Pass", np.testing.assert_allclose([0, 0.123456789, np.nan], [0, 0.123456780, np.nan], rtol=1e-7, atol=0)
+print "Fail", np.testing.assert_array_equal([0, 0.123456789, np.nan], [0, 0.123456780, np.nan])
diff --git a/NumPy/Code/ch8code/arrayless.py b/NumPy/Code/ch8code/arrayless.py
new file mode 100644
index 0000000..7e3ea36
--- /dev/null
+++ b/NumPy/Code/ch8code/arrayless.py
@@ -0,0 +1,4 @@
+import numpy as np
+
+print "Pass", np.testing.assert_array_less([0, 0.123456789, np.nan], [1, 0.23456780, np.nan])
+print "Fail", np.testing.assert_array_less([0, 0.123456789, np.nan], [0, 0.123456780, np.nan])
diff --git a/NumPy/Code/ch8code/decorator_test.py b/NumPy/Code/ch8code/decorator_test.py
new file mode 100644
index 0000000..f8839a4
--- /dev/null
+++ b/NumPy/Code/ch8code/decorator_test.py
@@ -0,0 +1,34 @@
+from numpy.testing.decorators import setastest
+from numpy.testing.decorators import skipif
+from numpy.testing.decorators import knownfailureif
+from numpy.testing import decorate_methods
+
+
+@setastest(False)
+def test_false():
+   pass
+
+@setastest(True)
+def test_true():
+   pass
+
+@skipif(True)
+def test_skip():
+   pass
+
+@knownfailureif(True)
+def test_alwaysfail():
+     pass
+
+
+class TestClass():
+   def test_true2(self):
+      pass
+
+
+class TestClass2():
+   def test_false2(self):
+      pass
+
+
+decorate_methods(TestClass2, setastest(False), 'test_false2')
diff --git a/NumPy/Code/ch8code/decorator_test.pyc b/NumPy/Code/ch8code/decorator_test.pyc
new file mode 100644
index 0000000..2bedb59
Binary files /dev/null and b/NumPy/Code/ch8code/decorator_test.pyc differ
diff --git a/NumPy/Code/ch8code/docstringtest.py b/NumPy/Code/ch8code/docstringtest.py
new file mode 100644
index 0000000..469c5ff
--- /dev/null
+++ b/NumPy/Code/ch8code/docstringtest.py
@@ -0,0 +1,13 @@
+import numpy as np
+
+def factorial(n):
+   """
+   Test for the factorial of 3 that should pass.
+   >>> factorial(3)
+   6
+
+   Test for the factorial of 0 that should fail.
+   >>> factorial(0)
+   1
+   """
+   return np.arange(1, n+1).cumprod()[-1]
diff --git a/NumPy/Code/ch8code/docstringtest.pyc b/NumPy/Code/ch8code/docstringtest.pyc
new file mode 100644
index 0000000..60a56c7
Binary files /dev/null and b/NumPy/Code/ch8code/docstringtest.pyc differ
diff --git a/NumPy/Code/ch8code/equal.py b/NumPy/Code/ch8code/equal.py
new file mode 100644
index 0000000..9ecbfb0
--- /dev/null
+++ b/NumPy/Code/ch8code/equal.py
@@ -0,0 +1,3 @@
+import numpy as np
+
+print "Equal?", np.testing.assert_equal((1, 2), (1, 3))
diff --git a/NumPy/Code/ch8code/maxulp.py b/NumPy/Code/ch8code/maxulp.py
new file mode 100644
index 0000000..a95f5dd
--- /dev/null
+++ b/NumPy/Code/ch8code/maxulp.py
@@ -0,0 +1,6 @@
+import numpy as np
+
+eps = np.finfo(float).eps
+print "EPS", eps
+print "1", np.testing.assert_array_max_ulp(1.0, 1.0 + eps)
+print "2", np.testing.assert_array_max_ulp(1.0, 1 + 2 * eps, maxulp=2)
diff --git a/NumPy/Code/ch8code/nulp.py b/NumPy/Code/ch8code/nulp.py
new file mode 100644
index 0000000..5dc8e4f
--- /dev/null
+++ b/NumPy/Code/ch8code/nulp.py
@@ -0,0 +1,6 @@
+import numpy as np
+
+eps = np.finfo(float).eps
+print "EPS", eps
+print "1", np.testing.assert_array_almost_equal_nulp(1.0, 1.0 + eps)
+print "2", np.testing.assert_array_almost_equal_nulp(1.0, 1.0 + 2 * eps)
diff --git a/NumPy/Code/ch8code/stringequal.py b/NumPy/Code/ch8code/stringequal.py
new file mode 100644
index 0000000..c7a1fae
--- /dev/null
+++ b/NumPy/Code/ch8code/stringequal.py
@@ -0,0 +1,4 @@
+import numpy as np
+
+print "Pass", np.testing.assert_string_equal("NumPy", "NumPy")
+print "Fail", np.testing.assert_string_equal("NumPy", "Numpy")
diff --git a/NumPy/Code/ch8code/unit_test.py b/NumPy/Code/ch8code/unit_test.py
new file mode 100644
index 0000000..2c1653b
--- /dev/null
+++ b/NumPy/Code/ch8code/unit_test.py
@@ -0,0 +1,32 @@
+import numpy as np
+import unittest
+
+
+def factorial(n):
+   if n == 0:
+      return 1
+
+   if n < 0:
+      raise ValueError, "Unexpected negative value"
+
+   return np.arange(1, n+1).cumprod()
+
+
+class FactorialTest(unittest.TestCase):
+   def test_factorial(self):
+      #Test for the factorial of 3 that should pass.
+      self.assertEqual(6, factorial(3)[-1])
+      np.testing.assert_equal(np.array([1, 2, 6]), factorial(3))
+
+   def test_zero(self):
+      #Test for the factorial of 0 that should pass.
+      self.assertEqual(1, factorial(0))
+
+   def test_negative(self):
+      #Test for the factorial of negative numbers that should fail.
+      # It should throw a ValueError, but we expect IndexError
+      self.assertRaises(IndexError, factorial(-10))
+
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/NumPy/Code/ch9code/README b/NumPy/Code/ch9code/README
new file mode 100644
index 0000000..1a5d699
--- /dev/null
+++ b/NumPy/Code/ch9code/README
@@ -0,0 +1,31 @@
+NumPy Beginner's Guide
+
+Chapter 9 Plotting with Matplotlib
+
+
+candlesticks.py Demonstrates candlesticks on stock charts.
+   Run with python candlesticks.py <symbol>
+
+emalegend.py Demonstrates plot legends.
+   Run with python emalegend.py <symbol>
+
+fillbetween.py Demonstrates region shading.
+   Run with python fillbetween.py <symbol>
+
+logy.py Demonstrates logplots.
+   Run with python logy.py <symbol>
+
+polyplot.py Demonstrates simple plots.
+   Run with python polyplot.py <coefficients>
+
+polyplot2.py Demonstrates simple plots.
+   Run with python polyplot2.py <coefficients>
+
+polyplot3.py Demonstrates simple plots.
+   Run with python polyplot3.py <coefficients>
+
+scatterprice.py Demonstrates scatter plots.
+   Run with python scatterprice.py <symbol>
+
+stockhistogram.py Demonstrates histograms.
+   Run with python stockhistogram.py <symbol>
diff --git a/NumPy/Code/ch9code/animation.py b/NumPy/Code/ch9code/animation.py
new file mode 100644
index 0000000..f77264a
--- /dev/null
+++ b/NumPy/Code/ch9code/animation.py
@@ -0,0 +1,24 @@
+import numpy as np
+import matplotlib.pyplot as plt
+import matplotlib.animation as animation
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+N = 10
+x = np.random.rand(N)
+y = np.random.rand(N)
+z = np.random.rand(N)
+circles, triangles, dots = ax.plot(x, 'ro', y, 'g^', z, 'b.')
+ax.set_ylim(0, 1)
+plt.axis('off')
+
+def update(data):
+    circles.set_ydata(data[0])
+    triangles.set_ydata(data[1])
+    return circles, triangles
+
+def generate():
+    while True: yield np.random.rand(2, N)
+
+anim = animation.FuncAnimation(fig, update, generate, interval=150)
+plt.show()
diff --git a/NumPy/Code/ch9code/candlesticks.py b/NumPy/Code/ch9code/candlesticks.py
new file mode 100644
index 0000000..439f44a
--- /dev/null
+++ b/NumPy/Code/ch9code/candlesticks.py
@@ -0,0 +1,34 @@
+from matplotlib.dates import DateFormatter
+from matplotlib.dates import DayLocator
+from matplotlib.dates import MonthLocator
+from matplotlib.finance import quotes_historical_yahoo
+from matplotlib.finance import candlestick
+import sys
+from datetime import date
+import matplotlib.pyplot as plt
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+alldays = DayLocator()              
+months = MonthLocator()
+month_formatter = DateFormatter("%b %Y")
+
+symbol = 'DISH'
+
+if len(sys.argv) == 2:
+   symbol = sys.argv[1]
+
+quotes = quotes_historical_yahoo(symbol, start, today)
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+ax.xaxis.set_major_locator(months)
+ax.xaxis.set_minor_locator(alldays)
+ax.xaxis.set_major_formatter(month_formatter)
+
+candlestick(ax, quotes)
+fig.autofmt_xdate()
+plt.show()
+
+
diff --git a/NumPy/Code/ch9code/contour.py b/NumPy/Code/ch9code/contour.py
new file mode 100644
index 0000000..bff12ef
--- /dev/null
+++ b/NumPy/Code/ch9code/contour.py
@@ -0,0 +1,14 @@
+import matplotlib.pyplot as plt
+import numpy as np
+from matplotlib import cm
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+
+u = np.linspace(-1, 1, 100)
+
+x, y = np.meshgrid(u, u)
+z = x ** 2 + y ** 2
+ax.contourf(x, y, z)
+
+plt.show()
diff --git a/NumPy/Code/ch9code/emalegend.py b/NumPy/Code/ch9code/emalegend.py
new file mode 100644
index 0000000..4c6f0c8
--- /dev/null
+++ b/NumPy/Code/ch9code/emalegend.py
@@ -0,0 +1,60 @@
+from matplotlib.finance import quotes_historical_yahoo
+from matplotlib.dates import DateFormatter
+from matplotlib.dates import DayLocator
+from matplotlib.dates import MonthLocator
+import sys
+from datetime import date
+import matplotlib.pyplot as plt
+import numpy as np
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+symbol = 'DISH'
+
+if len(sys.argv) == 2:
+   symbol = sys.argv[1]
+
+quotes = quotes_historical_yahoo(symbol, start, today)
+quotes = np.array(quotes)
+dates = quotes.T[0]
+close = quotes.T[4]
+
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+
+emas = []
+for i in range(9, 18, 3):
+   weights = np.exp(np.linspace(-1., 0., i))
+   weights /= weights.sum()
+
+   ema = np.convolve(weights, close)[i-1:-i+1]
+   idx = (i - 6)/3
+   ax.plot(dates[i-1:], ema, lw=idx, label="EMA(%s)" % (i))
+   data = np.column_stack((dates[i-1:], ema))
+   emas.append(np.rec.fromrecords(data, names=["dates", "ema"]))   
+
+first = emas[0]["ema"].flatten() 
+second = emas[1]["ema"].flatten()
+bools = np.abs(first[-len(second):] - second)/second < 0.0001
+xpoints = np.compress(bools, emas[1])
+
+for xpoint in xpoints:
+   ax.annotate('x', xy=xpoint, textcoords='offset points',
+                xytext=(-50, 30),
+                arrowprops=dict(arrowstyle="->"))
+   
+leg = ax.legend(loc='best', fancybox=True)
+leg.get_frame().set_alpha(0.5)
+
+alldays = DayLocator()              
+months = MonthLocator()
+month_formatter = DateFormatter("%b %Y")
+ax.plot(dates, close, lw=1.0, label="Close")
+ax.xaxis.set_major_locator(months)
+ax.xaxis.set_minor_locator(alldays)
+ax.xaxis.set_major_formatter(month_formatter)
+ax.grid(True)
+fig.autofmt_xdate()
+plt.show()
diff --git a/NumPy/Code/ch9code/fillbetween.py b/NumPy/Code/ch9code/fillbetween.py
new file mode 100644
index 0000000..81c82f7
--- /dev/null
+++ b/NumPy/Code/ch9code/fillbetween.py
@@ -0,0 +1,38 @@
+from matplotlib.finance import quotes_historical_yahoo
+from matplotlib.dates import DateFormatter 
+from matplotlib.dates import DayLocator 
+from matplotlib.dates import MonthLocator
+import sys
+from datetime import date
+import matplotlib.pyplot as plt
+import numpy as np
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+symbol = 'DISH'
+
+if len(sys.argv) == 2:
+   symbol = sys.argv[1]
+
+quotes = quotes_historical_yahoo(symbol, start, today)
+quotes = np.array(quotes)
+dates = quotes.T[0]
+close = quotes.T[4]
+
+
+alldays = DayLocator()              
+months = MonthLocator()
+month_formatter = DateFormatter("%b %Y")
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+ax.plot(dates, close) 
+plt.fill_between(dates, close.min(), close, where=close>close.mean(), facecolor="green", alpha=0.4)
+plt.fill_between(dates, close.min(), close, where=close<close.mean(), facecolor="red", alpha=0.4)
+ax.xaxis.set_major_locator(months)
+ax.xaxis.set_minor_locator(alldays)
+ax.xaxis.set_major_formatter(month_formatter)
+ax.grid(True)
+fig.autofmt_xdate()
+plt.show()
diff --git a/NumPy/Code/ch9code/logy.py b/NumPy/Code/ch9code/logy.py
new file mode 100644
index 0000000..daf8233
--- /dev/null
+++ b/NumPy/Code/ch9code/logy.py
@@ -0,0 +1,35 @@
+from matplotlib.finance import quotes_historical_yahoo
+from matplotlib.dates import DateFormatter
+from matplotlib.dates import DayLocator
+from matplotlib.dates import MonthLocator
+import sys
+from datetime import date
+import matplotlib.pyplot as plt
+import numpy as np
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+symbol = 'DISH'
+
+if len(sys.argv) == 2:
+   symbol = sys.argv[1]
+
+quotes = quotes_historical_yahoo(symbol, start, today)
+quotes = np.array(quotes)
+dates = quotes.T[0]
+volume = quotes.T[5]
+
+
+alldays = DayLocator()              
+months = MonthLocator()
+month_formatter = DateFormatter("%b %Y")
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+plt.semilogy(dates, volume)
+ax.xaxis.set_major_locator(months)
+ax.xaxis.set_minor_locator(alldays)
+ax.xaxis.set_major_formatter(month_formatter)
+fig.autofmt_xdate()
+plt.show()
diff --git a/NumPy/Code/ch9code/polyplot.py b/NumPy/Code/ch9code/polyplot.py
new file mode 100644
index 0000000..8414d02
--- /dev/null
+++ b/NumPy/Code/ch9code/polyplot.py
@@ -0,0 +1,11 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+func = np.poly1d(np.array([1, 2, 3, 4]).astype(float))
+x = np.linspace(-10, 10, 30)
+y = func(x)
+
+plt.plot(x, y)
+plt.xlabel('x')
+plt.ylabel('y(x)')
+plt.show()
diff --git a/NumPy/Code/ch9code/polyplot2.py b/NumPy/Code/ch9code/polyplot2.py
new file mode 100644
index 0000000..667565d
--- /dev/null
+++ b/NumPy/Code/ch9code/polyplot2.py
@@ -0,0 +1,14 @@
+import numpy as np
+import sys
+import matplotlib.pyplot as plt
+
+func = np.poly1d(np.array([1, 2, 3, 4]).astype(float))
+func1 = func.deriv(m=1)
+x = np.linspace(-10, 10, 30)
+y = func(x)
+y1 = func1(x)
+
+plt.plot(x, y, 'ro', x, y1, 'g--')
+plt.xlabel('x')
+plt.ylabel('y')
+plt.show()
diff --git a/NumPy/Code/ch9code/polyplot3.py b/NumPy/Code/ch9code/polyplot3.py
new file mode 100644
index 0000000..65ecd84
--- /dev/null
+++ b/NumPy/Code/ch9code/polyplot3.py
@@ -0,0 +1,23 @@
+import numpy as np
+import matplotlib.pyplot as plt
+
+func = np.poly1d(np.array([1, 2, 3, 4]).astype(float))
+x = np.linspace(-10, 10, 30)
+y = func(x)
+func1 = func.deriv(m=1)
+y1 = func1(x)
+func2 = func.deriv(m=2)
+y2 = func2(x)
+
+plt.subplot(311)
+plt.plot(x, y, 'r-')
+plt.title("Polynomial")
+plt.subplot(312)
+plt.plot(x, y1, 'b^')
+plt.title("First Derivative")
+plt.subplot(313)
+plt.plot(x, y2, 'go')
+plt.title("Second Derivative")
+plt.xlabel('x')
+plt.ylabel('y')
+plt.show()
diff --git a/NumPy/Code/ch9code/scatterprice.py b/NumPy/Code/ch9code/scatterprice.py
new file mode 100644
index 0000000..5a6c4e3
--- /dev/null
+++ b/NumPy/Code/ch9code/scatterprice.py
@@ -0,0 +1,28 @@
+from matplotlib.finance import quotes_historical_yahoo
+import sys
+from datetime import date
+import matplotlib.pyplot as plt
+import numpy as np
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+symbol = 'DISH'
+
+if len(sys.argv) == 2:
+   symbol = sys.argv[1]
+
+quotes = quotes_historical_yahoo(symbol, start, today)
+quotes = np.array(quotes)
+close = quotes.T[4]
+volume = quotes.T[5]
+ret = np.diff(close)/close[:-1]
+volchange = np.diff(volume)/volume[:-1]
+
+fig = plt.figure()
+ax = fig.add_subplot(111)
+ax.scatter(ret, volchange, c=ret * 100, s=volchange * 100, alpha=0.5)
+ax.set_title('Close and volume returns')
+ax.grid(True)
+
+plt.show()
diff --git a/NumPy/Code/ch9code/stockhistogram.py b/NumPy/Code/ch9code/stockhistogram.py
new file mode 100644
index 0000000..c80a120
--- /dev/null
+++ b/NumPy/Code/ch9code/stockhistogram.py
@@ -0,0 +1,20 @@
+from matplotlib.finance import quotes_historical_yahoo
+import sys
+from datetime import date
+import matplotlib.pyplot as plt
+import numpy as np
+
+today = date.today()
+start = (today.year - 1, today.month, today.day)
+
+symbol = 'DISH'
+
+if len(sys.argv) == 2:
+   symbol = sys.argv[1]
+
+quotes = quotes_historical_yahoo(symbol, start, today)
+quotes = np.array(quotes)
+close = quotes.T[4]
+
+plt.hist(close, np.sqrt(len(close)))
+plt.show()
diff --git a/NumPy/Code/ch9code/three_d.py b/NumPy/Code/ch9code/three_d.py
new file mode 100644
index 0000000..72ee7c4
--- /dev/null
+++ b/NumPy/Code/ch9code/three_d.py
@@ -0,0 +1,15 @@
+from mpl_toolkits.mplot3d import Axes3D
+import matplotlib.pyplot as plt
+import numpy as np
+from matplotlib import cm
+
+fig = plt.figure()
+ax = fig.add_subplot(111, projection='3d')
+
+u = np.linspace(-1, 1, 100)
+
+x, y = np.meshgrid(u, u)
+z = x ** 2 + y ** 2
+ax.plot_surface(x, y, z, cmap=cm.YlGnBu_r)
+
+plt.show()
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