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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:

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