--- title: sma description: This page explains the Simple Moving Average (sma), a method used to filter noise and identify trends in data by averaging the previous set of values within a given time period. It includes the usage and parameter details. keywords: - sma - moving averages - simple moving average - filter noise - identify trends - time period - n_length - n_offset --- import HeadTitle from '@site/src/components/General/HeadTitle.tsx'; Moving Averages are used to smooth the data in an array to help eliminate noise and identify trends. The Simple Moving Average is literally the simplest form of a moving average. Each output value is the average of the previous n values. In a Simple Moving Average, each value in the time period carries equal weight, and values outside of the time period are not included in the average. This makes it less responsive to recent changes in the data, which can be useful for filtering out those changes. ### Usage ```python sma [-l N_LENGTH] [-o N_OFFSET] ``` --- ## Parameters | Name | Description | Default | Optional | Choices | | ---- | ----------- | ------- | -------- | ------- | | n_length | Window lengths. Multiple values indicated as comma separated values. | 20, 50 | True | None | | n_offset | offset | 0 | True | None | ![sma](https://user-images.githubusercontent.com/46355364/154311791-5b130d08-55bd-406b-a68e-914a733c5191.png) ---