Change data type of given numpy array

In this post, we are going to see the ways in which we can change the dtype of the given numpy array. In order to change the dtype of the given array object, we will use numpy.astype() function. The function takes an argument which is the target data type. The function supports all the generic types and built-in types of data.

Problem #1 : Given a numpy array whose underlying data is of 'int32' type. Change the dtype of the given object to 'float64'.

Solution : We will use numpy.astype() function to change the data type of the underlying data of the given numpy array.

# importing the numpy library as np
import numpy as np

# Create a numpy array
arr = np.array([10, 20, 30, 40, 50])

# Print the array
print(arr)

Output :

Now we will check the dtype of the given array object.

# Print the dtype
print(arr.dtype)

Output :

As we can see in the output, the current dtype of the given array object is ‘int32’. Now we will change this to ‘float64’ type.

# change the dtype to 'float64'
arr = arr.astype('float64')

# Print the array after changing
# the data type
print(arr)

# Also print the data type
print(arr.dtype)

Output :

Problem #2 : Given a numpy array whose underlying data is of 'int32' type. Change the dtype of the given object to 'complex128'.

Solution : We will use numpy.astype() function to change the data type of the underlying data of the given numpy array.

# importing the numpy library as np
import numpy as np

# Create a numpy array
arr = np.array([10, 20, 30, 40, 50])

# Print the array
print(arr)

Output :

Now we will check the dtype of the given array object.

# Print the dtype
print(arr.dtype)

Output :

As we can see in the output, the current dtype of the given array object is ‘int32’. Now we will change this to ‘complex128’ type.

# change the dtype to 'complex128'
arr = arr = arr.astype('complex128')

# Print the array after changing
# the data type
print(arr)

# Also print the data type
print(arr.dtype)

Output :