Change the data type of the specified array

Problem # 1: There is an array with an empty array, the underlying data of which is & # 39; int32 & # 39; of type & # 39; int32 & # 39; . Change the dtype of this object to & # 39; float64 & # 39; .

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

# import numpy library as np import numpy as np   # Create an empty array arr = np.array ([ 10 , 20 , 30 , 40 , 50 ])    # Print array print (arr)

Exit :

Now we will check the dtype of this array object.

# Print dtype print (arr.dtype)

Output:

As we can see in the output, the current type d of this object array — & # 39; int32 & # 39 ;. Now we will change this to type & # 39; float64 & # 39 ;.

# change dtype to & # 39; float64 & # 39; arr = arr.astype ( ’float64’ )    # Print array after modification # data type print (arr)   # Also print the data type print (arr.dtype)

Output:

Problem # 2: An array with an empty array is given, the base data of which is & # 39; int32 & # 39; type & # 39; int32 & # 39; . Change the dtype of this object to & # 39; complex128 & # 39; .

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

# import numpy library as np import numpy as np   # Create an empty array arr = np.array ([ 10 , 20 , 30 , 40 , 50 ] )    # Print array print (arr)

Output:

Now we will check the dtype of this array object .

# Print dtype print (arr.dtype)

Output:

As we can see in the output, the current type d of the given array object — & # 39; int32 & # 39 ;. We will now change this to type complex128.

# change dtype to complex128 arr = arr = arr.astype ( ’ complex128’ )    # Print array after modification # data type print (arr)   # Also print the data type print (arr.dtype)

Exit: