# numpy.true_divide () in Python

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Python traditionally follows gender. Regardless of the type of input, true division corrects the answer at its best.
"//" — floor subdivision operator.
"/" Is a true division operator.

Parameters :

`  arr1:  [array_like] Input array or object which works as numerator.  arr2:  [array_like] Input array or object which works as denominator.  out:  [ndarray, None, optional] Output array with same dimensions as Input array, placed with result.  ** kwargs:  allows you to pass keyword variable length of argument to a function. It is used when we want to handle named argument in a function.  where:  [array_like, optional] True value means to calculate the universal functions (ufunc) at that position, False value means to leave the value in the output alone. `

Return:

` If inputs are scalar then scalar; otherwise array with arr1 / arr2 (element-wise) ie true division `

Code 1: arr1 divides by arr2

` `

` # Python program explaining # true_divide () function import numpy as np   # input_array arr1 = [ 6 , 7 , 2 , 9 , 1 ] arr2 = [ 2 , 3 , 4 , 5 , 6 ] print ( " arr1 : " , arr1) print ( "arr1 :" , arr2)   # output_array out = np.true_divide (arr1 , arr2) print ( "Output array: " , out) `

` `

< p> Output:

` arr1: [6, 7, 2, 9, 1] arr1: [2, 3, 4, 5, 6] Output array: [3. 2.33333333 0.5 1.8 0.16666667] `

Code 2: arr1 elements separated by divider

` `

` # Python program explaining # true_divide () function import numpy as np    # input_array arr1 = [ 2 , 7 , 3 , 11 , 4 ] < / p> divisor = 3 print ( "arr1 :" , arr1)    # output_array out = np.true_divide (arr1, divisor) print ( "Output array:" , out) `

Output:

` arr1: [2, 7, 3, 11, 4] Output array: [0.66666667 2.33333333 1. 3.66666667 1.33333333] `

Code 3: Comparison between floor_division (//) and true-Division (/)

 ` # Python program explaining ` ` # true_divide () function ` ` import ` ` numpy as np `   ` # input_array ` ` arr1 ` ` = ` ` np. arange (` ` 5 ` `) ` ` arr2 ` ` = ` ` [` ` 2 ` `, ` ` 3 ` `, ` ` 4 ` `, ` ` 5 ` `, ` ` 6 ` `] ` ` print ` ` (` `" arr1 : "` `, arr1) ` ` print ` ` (` ` "arr1 :" ` `, arr2) `   ` # output_array ` ` out ` ` = ` ` np.floor_divide (arr1, arr2) ` ` out_arr ` ` = ` ` np.true_divide (arr1, arr2) ` ` print ` ` (` ` "Output array with floor divide:" ` `, out) ` ` print ` ` (` ` "Output array with true divide :" ` `, out_arr) `     ` print ` ` (` ` "Output array with floor divide (//):" ` `, arr1 ` ` / ` ` / ` ` arr2) ` ` print ` ` (` ` "Output array with true divide (/) :" ` `, arr1 ` ` / ` ` arr2) `

Output:

` arr1: [0 1 2 3 4] arr1: [2, 3, 4, 5, 6] Output array with floor divide: [0 0 0 0 0] Output array with true divide: [0. 0.33333333 0.5 0.6 0.66666667] Output array with floor divide (//): [0 0 0 0 0] Output array with true divide (/): [0. 0.33333333 0.5 0.6 0.66666667] `

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