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Practice

Data Type Conversion and Copying Arrays

NumPy arrays have a fixed data type, like int, float, or bool.
You can change the type using .astype().

Also, when copying arrays, it’s important to know the difference between a real copy and just a reference.


Changing Data Type with .astype()​

You can convert an array from one type to another:

arr = np.array([1.5, 2.8, 3.0])
int_arr = arr.astype(int)

print(int_arr)  # [1 2 3]

This turns float values into integers.


Copying Arrays​

By default, assigning one array to another does not create a real copy — they both point to the same data.

a = np.array([1, 2, 3])
b = a  # Not a copy!
b[0] = 99

print(a)  # [99 2 3] — original was modified

Use .copy() to make a true copy:

c = a.copy()
c[0] = 0

print(a)  # Still [99 2 3]

Summary​

  • Use .astype() to change data types (e.g., float to int)
  • Use .copy() to create a real copy of an array
  • Without .copy(), both variables refer to the same array in memory

What’s Next​

You’ll now practice converting types and copying arrays safely in Jupyter.