# How to get element-wise true division of an array using Numpy?

True Division in Python3 returns a floating result containing the remainder of the division. To get the true division of an array, NumPy library has a function numpy.true_divide(x1, x2). This function gives us the value of true division done on the arrays passed in the function. To get the element-wise division we need to enter the first parameter as an array and the second parameter as a single element.

Syntax: np.true_divide(x1,x2)
Parameters:

• x1: The dividend array
• x2: divisor (can be an array or an element)

Return: If inputs are scalar then scalar; otherwise array with arr1 / arr2(element- wise) i.e. true division

Now, let’s see an example:

Example 1:

## Python3

 `# import library ` `import` `numpy as np ` ` `  `# create 1d-array ` `x ``=` `np.arange(``5``) ` ` `  `print``(``"Original array:"``,  ` `      ``x) ` ` `  `# apply true division  ` `# on each array element ` `rslt ``=` `np.true_divide(x, ``4``) ` ` `  `print``(``"After the element-wise division:"``,  ` `      ``rslt)`

Output :

```Original array: [0 1 2 3 4]
After the element-wise division: [0.   0.25 0.5  0.75 1.  ]```

Example 2:

## Python3

 `# import library ` `import` `numpy as np ` ` `  `# create a 1d-array ` `x ``=` `np.arange(``10``) ` ` `  `print``(``"Original array:"``,  ` `      ``x) ` ` `  `# apply true division  ` `# on each array element ` `rslt ``=` `np.true_divide(x, ``3``) ` ` `  `print``(``"After the element-wise division:"``, ` `      ``rslt)`

Output:

Original array: [0 1 2 3 4 5 6 7 8 9]
After the element-wise division: [0. 0.33333333 0.66666667 1. 1.33333333 1.66666667
2. 2.33333333 2.66666667 3. ]

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