NumPy Project Euler Problem 8

Project Euler Problem 8 requires a lot of string manipulation. Still we have some opportunities to practice our NumPy skills.

1. Calculate the product of the 5 element array

First we need to compute the product of an array with 5 elements. We can calculate the product of the elements in an array with the NumPy prod function.

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products.append(digits[i:i + 5].prod())

2. Get the max of the products

The products are stored in a Python list. We can convert this to a NumPy array and then find the greatest product with the NumPy max function.

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print numpy.array(products).max()


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import numpy
 
#Find the greatest product of five consecutive digits in the 1000-digit number.
 
number = "73167176531330624919225119674426574742355349194934\
96983520312774506326239578318016984801869478851843\
85861560789112949495459501737958331952853208805511\
12540698747158523863050715693290963295227443043557\
66896648950445244523161731856403098711121722383113\
62229893423380308135336276614282806444486645238749\
30358907296290491560440772390713810515859307960866\
70172427121883998797908792274921901699720888093776\
65727333001053367881220235421809751254540594752243\
52584907711670556013604839586446706324415722155397\
53697817977846174064955149290862569321978468622482\
83972241375657056057490261407972968652414535100474\
82166370484403199890008895243450658541227588666881\
16427171479924442928230863465674813919123162824586\
17866458359124566529476545682848912883142607690042\
24219022671055626321111109370544217506941658960408\
07198403850962455444362981230987879927244284909188\
84580156166097919133875499200524063689912560717606\
05886116467109405077541002256983155200055935729725\
71636269561882670428252483600823257530420752963450"
 
digits = numpy.zeros(1000)
 
for i in xrange(len(number)):
digits[i] = int(number[i])
 
products = []
 
for i in xrange(len(digits) - 5):
#1. Calculate the product of the 5 element array
products.append(digits[i:i + 5].prod())
 
#2. Get the max of the products
print numpy.array(products).max()

If you liked this post and are interested in NumPy check out NumPy Beginner's Guide by yours truly.