[//]: # (title: mean) Computes the [mean (average)](https://en.wikipedia.org/wiki/Arithmetic_mean) of values. `null` values are ignored. All primitive numeric types are supported: `Byte`, `Short`, `Int`, `Long`, `Float`, and `Double`. `mean` also supports the "mixed" `Number` type, as long as the column consists only of the aforementioned primitive numbers. The numbers are automatically converted to a [common type](numberUnification.md) for the operation. The return type is always `Double`; `Double.NaN` for empty columns. All operations on `Double`/`Float`/`Number` have the `skipNaN` option, which is set to `false` by default. This means that if a `NaN` is present in the input, it will be propagated to the result. When it's set to `true`, `NaN` values are ignored. ```kotlin df.mean() // mean of values per every numeric column df.mean { age and weight } // mean of all values in `age` and `weight` df.meanFor(skipNaN = true) { age and weight } // mean of values per `age` and `weight` separately, skips NaN df.meanOf { (weight ?: 0) / age } // median of expression evaluated for every row ``` ```kotlin df.mean() df.age.mean() df.groupBy { city }.mean() df.pivot { city }.mean() df.pivot { city }.groupBy { name.lastName }.mean() ``` See [statistics](summaryStatistics.md#groupby-statistics) for details on complex data aggregations. See [column selectors](ColumnSelectors.md) for how to select the columns for this operation. ### Type Conversion The following automatic type conversions are performed for the `mean` operation: | Conversion | Result for Empty Input | |----------------------------------------------------------------------------|------------------------| | Int -> Double | Double.NaN | | Byte -> Double | Double.NaN | | Short -> Double | Double.NaN | | Long -> Double | Double.NaN | | Double -> Double | Double.NaN | | Float -> Double | Double.NaN | | Number -> Conversion([Common number type](numberUnification.md)) -> Double | Double.NaN | | Nothing -> Double | Double.NaN |