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Given the following text problem statement, write Python code to implement the functionality described below in problem statement
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Problem:
First off, I'm no mathmatician. I admit that. Yet I still need to understand how ScyPy's sparse matrices work arithmetically in order to switch from a dense NumPy matrix to a SciPy sparse matrix in an application I have to work on. The issue is memory usage. A large dense matrix will consume tons of memory.
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Python Code:
from scipy import sparse
V = sparse.random(10, 10, density = 0.05, format = 'coo', random_state = 42)
x = 100
y = 99
V = V.copy()
V.data += x
V.eliminate_zeros()
V.data += y
V.eliminate_zeros()
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