Python for Data Science: Chapter 5: NumPy and Pandas Libraries
NumPy: Copying Arrays
Python library
An array copy in NumPy means creating a new array that has the same data as the original array, but is stored separately in memory.
Copying
Arrays
•
An array copy in NumPy means creating a new array that has the same data as the
original array, but is stored separately in memory.
To
create a copy, we use the function
new_array
= old_array.copy()
This
creates another array having same data values but they are stored in different
memory locations.
Python program
import numpy as np
arr1 = np.array([100,200,300])
arr2 = arr1.copy()
print("After copy operation...")
print("arr1: ",arr1)
print("arr2: ",arr2)
arr2[0]=500
print("After modification...")
print("arr1: ",arr1)
print("arr2: ",arr2)
Output
After copy
operation...
arr1: [100 200 300]
arr2: [100 200 300]
After modification...
arr1: [100 200 300]
arr2: [500 200 300]
Note
that in above code, arr1 and arr2 now exist independently. Changing arr2 does not change arr1.
Review Question
1. What happens if you
modify an array created using .copy () ?
Python for Data Science: Chapter 5: NumPy and Pandas Libraries : Tag: Computer Programming, Python, Data Science : Python library - NumPy: Copying Arrays
Python for Data Science: Chapter 5: NumPy and Pandas Libraries
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