# .exp()

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Published Jun 13, 2024
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The `.exp()` function in NumPy calculates the exponential of all elements in the input array. The exponential function, `.exp(𝑥)`, returns `e^x`, where `e` is Euler’s number with an approximate value of 2.71828. As a part of the NumPy library, which is widely used for numerical computing in Python, this function is particularly useful in scientific computations where exponential functions are common.

## Syntax

``````numpy.exp(arr, out=None, where=True, casting=‘same_kind’, order=‘K’, dtype=None)
``````
• `arr`: The input array or list for computing the exponential.
• `out`: The location to store the result. It must be broadcastable to the shape of `arr`.
• `where`: The condition to be checked. When `True`, the function is applied and when `False`, the original values are retained.
• `casting`: Controls the type of data casting that may occur.
• `order`: Defines the memory layout order of the result: `C` for C-order, `F` for Fortran-order, `A` for automatic, and `K` for input layout.
• `dtype`: Overrides the data type of the resultant array.

Note: In the `.exp()` function, the only mandatory parameter is `arr`. All other parameters, including `out`, `where`, `casting`, `order`, and `dtype`, are optional and have default values.

## Example

Here is an example demonstrating the use of the `.exp()` function:

```import numpy as np
# Create an input arrayarr = np.array([0, 1, 2, 3])
# Compute the exponential of each element in the arrayresult = np.exp(arr)
# Print the resultprint("Exponential of input array:", result)
```

The code above produces the following output:

```Exponential of input array: [ 1.          2.71828183  7.3890561  20.08553692]
```

In this example, the `.exp()` function is used to compute the exponential of each element in the array `[0, 1, 2, 3]`.

## Codebyte Example

Here is a working codebyte example demonstrating the `.exp()` function in action:

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