Cosine Similarity between 2 Number Lists

Question

I want to calculate the cosine similarity between two lists, let's say for example list 1 which is dataSetI and list 2 which is dataSetII.

Let's say dataSetI is [3, 45, 7, 2] and dataSetII is [2, 54, 13, 15]. The length of the lists are always equal. I want to report cosine similarity as a number between 0 and 1.

dataSetI = [3, 45, 7, 2]
dataSetII = [2, 54, 13, 15]

def cosine_similarity(list1, list2):
  # How to?
  pass

print(cosine_similarity(dataSetI, dataSetII))

Answer 1

You should try SciPy. It has a bunch of useful scientific routines for example, "routines for computing integrals numerically, solving differential equations, optimization, and sparse matrices." It uses the superfast optimized NumPy for its number crunching. See here for installing.

Note that spatial.distance.cosine computes the distance, and not the similarity. So, you must subtract the value from 1 to get the similarity.

from scipy import spatial

dataSetI = [3, 45, 7, 2]
dataSetII = [2, 54, 13, 15]
result = 1 - spatial.distance.cosine(dataSetI, dataSetII)

Answer 2

another version based on numpy only

from numpy import dot
from numpy.linalg import norm

cos_sim = dot(a, b)/(norm(a)*norm(b))