How to Use Excel's EXP Function in Pandas

Excel's EXP function calculates the exponential of a given number, using the constant 'e' as the base. This function plays a vital role in various fields such as finance, engineering, and statistics.

This page explains how to use Excel's EXP function in Python using pandas.

Understanding the Exponential Formula in Excel#

The EXP function in Excel takes a single argument and returns 'e' raised to the power of that number.

=EXP(number)

EXP Excel Syntax

Examples

Implementing the Exponential function in Pandas#

To replicate the EXP function in Excel using Python and pandas, here are some common implementations:

Single value#

To calculate the exponential of a single number in Excel, you would use the formula =EXP(number).

In pandas, you can use the numpy library's exp function to accomplish the same task

import numpy as np
result = np.exp(2)

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Entire column#

To calculate the exponential of an entire column in Excel, you would drag the EXP formula, =EXP(A1) dragged down the entire column.

In pandas, apply the numpy exp function to the whole column:

df['Exponential'] = np.exp(df['number'])

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Common mistakes when using EXP in Python#

While using the EXP function in pandas, certain mistakes are commonly made. Here are some and how to rectify them.

Using Log Base 10#

It's easy to confuse the natural logarithm (base 'e') with the logarithm base 10. Remember that np.exp uses base e, not base 10.