# Moving average This Moving average step smooths out short-term fluctuations in your data by calculating averages over a specified window of time or number of rows. It's particularly helpful for identifying trends in time-series data. ### Step parameters * `Value column` **column(string)**: the value column used as the basis for the moving average computation * `Reference column to sort (usually dates)` **column(string)**: the column used to sort rows * `Moving window (in number of rows)` **int\***: the number of rows included in the moving window * `Group by` **(optional)**: if you want perform the computation by group of rows (see example 2 below) * `New column name` **(optional)**: if you want to specify a custom column name (by default, it will be your original value column name suffixed with `_MOVING_AVG`) ### Example **Input**

**Configuration** ```json { "value_col": "sales", "column_to_sort": "date", "moving_window": 3, "group_by": [], "new_column_name": "sales_moving_avg" } ``` **Output**