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# scipy.fft() in Python

• Last Updated : 29 Aug, 2020

With the help of scipy.fft() method, we can compute the fast fourier transformation by passing simple 1-D numpy array and it will return the transformed array by using this method.

Fast Fourier Transformation

Syntax : scipy.fft(x)

Return : Return the transformed array.

Example #1 :

In this example we can see that by using scipy.fft() method, we are able to compute the fast fourier transformation by passing sequence of numbers and return the transformed array.

## Python3

 `# import scipy and numpy ` `import` `scipy ` `import` `numpy as np ` ` `  `x ``=` `np.array(np.arange(``10``)) ` `# Using scipy.fft() method ` `gfg ``=` `scipy.fft(x) ` ` `  `print``(gfg)`

Output :

[45. +0.j         -5.+15.38841769j -5. +6.8819096j  -5. +3.63271264j

-5. +1.62459848j -5. +0.j         -5. -1.62459848j -5. -3.63271264j

-5. -6.8819096j  -5.-15.38841769j]

Example #2 :

## Python3

 `# import scipy and numpy ` `import` `scipy ` `import` `numpy as np ` ` `  `x ``=` `np.array(np.arange(``5``)) ` `# Using scipy.fft() method ` `gfg ``=` `scipy.fft(x) ` ` `  `print``(gfg)`

Output :

[10. +0.j         -2.5+3.4409548j  -2.5+0.81229924j -2.5-0.81229924j

-2.5-3.4409548j ]

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