Add statistics on DataFrame support

core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/max.kt

@@ -73,10 +73,13 @@ public inline fun <reified T : Comparable<T>> AnyRow.rowMaxOf(skipNaN: Boolean =
 // endregion
 
 // region DataFrame
-
+@Refine
+@Interpretable("Max0")
 public fun <T> DataFrame<T>.max(skipNaN: Boolean = skipNaNDefault): DataRow<T> =
     maxFor(skipNaN, intraComparableColumns())
 
+@Refine
+@Interpretable("Max1")
 public fun <T, C : Comparable<C & Any>?> DataFrame<T>.maxFor(
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,

core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/mean.kt

@@ -60,10 +60,13 @@ public inline fun <reified T : Number> AnyRow.rowMeanOf(skipNaN: Boolean = skipN
 // endregion
 
 // region DataFrame
-
+@Refine
+@Interpretable("Mean0")
 public fun <T> DataFrame<T>.mean(skipNaN: Boolean = skipNaNDefault): DataRow<T> =
     meanFor(skipNaN, primitiveOrMixedNumberColumns())
 
+@Refine
+@Interpretable("Mean1")
 public fun <T, C : Number?> DataFrame<T>.meanFor(
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,

core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/median.kt

@@ -130,10 +130,13 @@ public inline fun <reified T> AnyRow.rowMedianOf(
 // endregion
 
 // region DataFrame
-
+@Refine
+@Interpretable("Median0")
 public fun <T> DataFrame<T>.median(skipNaN: Boolean = skipNaNDefault): DataRow<T> =
     medianFor(skipNaN, intraComparableColumns())
 
+@Refine
+@Interpretable("Median1")
 public fun <T, C : Comparable<C & Any>?> DataFrame<T>.medianFor(
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,

core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/min.kt

@@ -73,10 +73,13 @@ public inline fun <reified T : Comparable<T>> AnyRow.rowMinOf(skipNaN: Boolean =
 // endregion
 
 // region DataFrame
-
+@Refine
+@Interpretable("Min0")
 public fun <T> DataFrame<T>.min(skipNaN: Boolean = skipNaNDefault): DataRow<T> =
     minFor(skipNaN, intraComparableColumns())
 
+@Refine
+@Interpretable("Min1")
 public fun <T, C : Comparable<C & Any>?> DataFrame<T>.minFor(
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,

core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/percentile.kt

@@ -144,10 +144,13 @@ public inline fun <reified T> AnyRow.rowPercentileOf(
 // endregion
 
 // region DataFrame
-
+@Refine
+@Interpretable("Percentile0")
 public fun <T> DataFrame<T>.percentile(percentile: Double, skipNaN: Boolean = skipNaNDefault): DataRow<T> =
     percentileFor(percentile, skipNaN, intraComparableColumns())
 
+@Refine
+@Interpretable("Percentile1")
 public fun <T, C : Comparable<C & Any>?> DataFrame<T>.percentileFor(
     percentile: Double,
     skipNaN: Boolean = skipNaNDefault,

core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/std.kt

@@ -65,10 +65,13 @@ public inline fun <reified T : Number?> AnyRow.rowStdOf(
 // endregion
 
 // region DataFrame
-
+@Refine
+@Interpretable("Std0")
 public fun <T> DataFrame<T>.std(skipNaN: Boolean = skipNaNDefault, ddof: Int = ddofDefault): DataRow<T> =
     stdFor(skipNaN, ddof, primitiveOrMixedNumberColumns())
 
+@Refine
+@Interpretable("Std1")
 public fun <T, C : Number?> DataFrame<T>.stdFor(
     skipNaN: Boolean = skipNaNDefault,
     ddof: Int = ddofDefault,

core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/impl/aggregation/aggregators/Aggregators.kt

@@ -113,7 +113,7 @@ public object Aggregators {
     // T : Comparable<T & Any>? -> T?
     public fun <T : Comparable<T & Any>?> min(skipNaN: Boolean): Aggregator<T & Any, T?> = min.invoke(skipNaN).cast2()
 
-    private val min by withOneOption { skipNaN: Boolean ->
+    public val min: AggregatorOptionSwitch1<Boolean, Comparable<Any>, Comparable<Any>?> by withOneOption { skipNaN: Boolean ->
         twoStepSelectingForAny<Comparable<Any>, Comparable<Any>?>(
             getReturnType = minTypeConversion,
             stepOneSelector = { type -> minOrNull(type, skipNaN) },
@@ -125,7 +125,7 @@ public object Aggregators {
     // T : Comparable<T & Any>? -> T?
     public fun <T : Comparable<T & Any>?> max(skipNaN: Boolean): Aggregator<T & Any, T?> = max.invoke(skipNaN).cast2()
 
-    private val max by withOneOption { skipNaN: Boolean ->
+    public val max: AggregatorOptionSwitch1<Boolean, Comparable<Any>, Comparable<Any>?> by withOneOption { skipNaN: Boolean ->
         twoStepSelectingForAny<Comparable<Any>, Comparable<Any>?>(
             getReturnType = maxTypeConversion,
             stepOneSelector = { type -> maxOrNull(type, skipNaN) },
@@ -151,23 +151,23 @@ public object Aggregators {
         }
     }
 
-    // T : primitive Number? -> Double?
-    // T : Comparable<T & Any>? -> T?
+    // T: primitive Number? -> Double?
+    // T: Comparable<T & Any>? -> T?
     public fun <T> percentileCommon(
         percentile: Double,
         skipNaN: Boolean,
     ): Aggregator<T & Any, T?>
         where T : Comparable<T & Any>? =
         this.percentile.invoke(percentile, skipNaN).cast2()
 
-    // T : Comparable<T & Any>? -> T?
+    // T: Comparable<T & Any>? -> T?
     public fun <T> percentileComparables(
         percentile: Double,
     ): Aggregator<T & Any, T?>
         where T : Comparable<T & Any>? =
         percentileCommon<T>(percentile, skipNaNDefault).cast2()
 
-    // T : primitive Number? -> Double?
+    // T: primitive Number? -> Double?
     public fun <T> percentileNumbers(
         percentile: Double,
         skipNaN: Boolean,
@@ -176,34 +176,34 @@ public object Aggregators {
         percentileCommon<T>(percentile, skipNaN).cast2()
 
     @Suppress("UNCHECKED_CAST")
-    private val percentile by withTwoOptions { percentile: Double, skipNaN: Boolean ->
+    public val percentile: AggregatorOptionSwitch2<Double, Boolean, Comparable<Any>, Comparable<Any>?> by withTwoOptions { percentile: Double, skipNaN: Boolean ->
         flattenHybridForAny<Comparable<Any>, Comparable<Any>?>(
             getReturnType = percentileConversion,
             reducer = { type -> percentileOrNull(percentile, type, skipNaN) as Comparable<Any>? },
             indexOfResult = { type -> indexOfPercentile(percentile, type, skipNaN) },
         )
     }
 
-    // T : primitive Number? -> Double?
-    // T : Comparable<T & Any>? -> T?
+    // T: primitive Number? -> Double?
+    // T: Comparable<T & Any>? -> T?
     public fun <T> medianCommon(skipNaN: Boolean): Aggregator<T & Any, T?>
         where T : Comparable<T & Any>? =
         median.invoke(skipNaN).cast2()
 
-    // T : Comparable<T & Any>? -> T?
+    // T: Comparable<T & Any>? -> T?
     public fun <T> medianComparables(): Aggregator<T & Any, T?>
         where T : Comparable<T & Any>? =
         medianCommon<T>(skipNaNDefault).cast2()
 
-    // T : primitive Number? -> Double?
+    // T: primitive Number? -> Double?
     public fun <T> medianNumbers(
         skipNaN: Boolean,
     ): Aggregator<T & Any, Double?>
         where T : Comparable<T & Any>?, T : Number? =
         medianCommon<T>(skipNaN).cast2()
 
     @Suppress("UNCHECKED_CAST")
-    private val median by withOneOption { skipNaN: Boolean ->
+    public val median: AggregatorOptionSwitch1<Boolean, Comparable<Any>, Comparable<Any>?> by withOneOption { skipNaN: Boolean ->
         flattenHybridForAny<Comparable<Any>, Comparable<Any>?>(
             getReturnType = medianConversion,
             reducer = { type -> medianOrNull(type, skipNaN) as Comparable<Any>? },