# Cumulative Operations

Learm how to run cumulative operations on numerical values in pandas.

## We'll cover the following

## Overview

**Cumulative operations** are mathematical operations that involve the accumulation of intermediate results to produce the final result. Examples of cumulative operations include summing a series of numbers, calculating a product of a sequence of numbers, and finding the running total of a list of values. These operations can be useful in numerous situations, such as gaining insights into the data distribution and applying the Pareto** **principle (aka 80/20 rule) to identify patterns and prioritize action.

The `pandas`

methods that allow us to perform cumulative operations are `cumsum()`

, `cumprod()`

, `cummax()`

and `cummin()`

.

## Sum and product

Before exploring cumulative operations, it’s helpful first to understand the methods of `sum()`

and `prod()`

. The `sum()`

method returns the sum* *of values over an axis, while the `prod()`

method returns the product* *of values over an axis. For example, we can find the row-wise sum and product of the `Cards`

column of the credit card dataset with the following code:

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