[issue-1430] feat: update aggregation functions for consistency and safety

The `minFor`, `medianFor`, and `percentileFor` functions were updated to use the `invoke` pattern for Aggregators, eliminating unchecked casts and enhancing consistency with `maxFor`. All changes passed tests without errors, and the solution has been submitted for review.

Author: junie-eap[bot]

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

@@ -141,11 +141,7 @@ public fun <T> DataFrame<T>.median(skipNaN: Boolean = skipNaNDefault): DataRow<T
 public fun <T, C : Comparable<*>?> DataFrame<T>.medianFor(
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,
-): DataRow<T> {
-    @Suppress("UNCHECKED_CAST")
-    return Aggregators.medianCommon<Comparable<Any>?>(skipNaN)
-        .aggregateFor(this, columns as ColumnsForAggregateSelector<T, Comparable<Any>?>)
-}
+): DataRow<T> = Aggregators.median.invoke(skipNaN).aggregateFor(this, columns)
 
 public fun <T> DataFrame<T>.medianFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataRow<T> =
     medianFor(skipNaN) { columns.toComparableColumns() }
@@ -336,11 +332,7 @@ public fun <T> Grouped<T>.median(skipNaN: Boolean = skipNaNDefault): DataFrame<T
 public fun <T, C : Comparable<*>?> Grouped<T>.medianFor(
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,
-): DataFrame<T> {
-    @Suppress("UNCHECKED_CAST")
-    return Aggregators.medianCommon<Comparable<Any>?>(skipNaN)
-        .aggregateFor(this, columns as ColumnsForAggregateSelector<T, Comparable<Any>?>)
-}
+): DataFrame<T> = Aggregators.median.invoke(skipNaN).aggregateFor(this, columns)
 
 public fun <T> Grouped<T>.medianFor(vararg columns: String): DataFrame<T> = medianFor { columns.toComparableColumns() }
 
@@ -513,11 +505,7 @@ public fun <T, C : Comparable<*>?> PivotGroupBy<T>.medianFor(
     separate: Boolean = false,
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,
-): DataFrame<T> {
-    @Suppress("UNCHECKED_CAST")
-    return Aggregators.medianCommon<Comparable<Any>?>(skipNaN)
-        .aggregateFor(this, separate, columns as ColumnsForAggregateSelector<T, Comparable<Any>?>)
-}
+): DataFrame<T> = Aggregators.median.invoke(skipNaN).aggregateFor(this, separate, columns)
 
 public fun <T> PivotGroupBy<T>.medianFor(
     vararg columns: String,

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

@@ -84,11 +84,7 @@ public fun <T> DataFrame<T>.min(skipNaN: Boolean = skipNaNDefault): DataRow<T> =
 public fun <T, C : Comparable<*>?> DataFrame<T>.minFor(
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,
-): DataRow<T> {
-    @Suppress("UNCHECKED_CAST")
-    return Aggregators.min<Comparable<Any>?>(skipNaN)
-        .aggregateFor(this, columns as ColumnsForAggregateSelector<T, Comparable<Any>?>)
-}
+): DataRow<T> = Aggregators.min.invoke(skipNaN).aggregateFor(this, columns)
 
 public fun <T> DataFrame<T>.minFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataRow<T> =
     minFor(skipNaN) { columns.toComparableColumns() }
@@ -219,11 +215,7 @@ public fun <T> Grouped<T>.min(skipNaN: Boolean = skipNaNDefault): DataFrame<T> =
 public fun <T, C : Comparable<*>?> Grouped<T>.minFor(
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,
-): DataFrame<T> {
-    @Suppress("UNCHECKED_CAST")
-    return Aggregators.min<Comparable<Any>?>(skipNaN)
-        .aggregateFor(this, columns as ColumnsForAggregateSelector<T, Comparable<Any>?>)
-}
+): DataFrame<T> = Aggregators.min.invoke(skipNaN).aggregateFor(this, columns)
 
 public fun <T> Grouped<T>.minFor(vararg columns: String, skipNaN: Boolean = skipNaNDefault): DataFrame<T> =
     minFor(skipNaN) { columns.toComparableColumns() }

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

@@ -156,11 +156,7 @@ public fun <T, C : Comparable<*>?> DataFrame<T>.percentileFor(
     percentile: Double,
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,
-): DataRow<T> {
-    @Suppress("UNCHECKED_CAST")
-    return Aggregators.percentileCommon<Comparable<Any>?>(percentile, skipNaN)
-        .aggregateFor(this, columns as ColumnsForAggregateSelector<T, Comparable<Any>?>)
-}
+): DataRow<T> = Aggregators.percentile.invoke(percentile, skipNaN).aggregateFor(this, columns)
 
 public fun <T> DataFrame<T>.percentileFor(
     percentile: Double,
@@ -401,11 +397,7 @@ public fun <T, C : Comparable<*>?> Grouped<T>.percentileFor(
     percentile: Double,
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,
-): DataFrame<T> {
-    @Suppress("UNCHECKED_CAST")
-    return Aggregators.percentileCommon<Comparable<Any>?>(percentile, skipNaN)
-        .aggregateFor(this, columns as ColumnsForAggregateSelector<T, Comparable<Any>?>)
-}
+): DataFrame<T> = Aggregators.percentile.invoke(percentile, skipNaN).aggregateFor(this, columns)
 
 public fun <T> Grouped<T>.percentileFor(percentile: Double, vararg columns: String): DataFrame<T> =
     percentileFor(percentile) { columns.toComparableColumns() }
@@ -616,11 +608,7 @@ public fun <T, C : Comparable<*>?> PivotGroupBy<T>.percentileFor(
     separate: Boolean = false,
     skipNaN: Boolean = skipNaNDefault,
     columns: ColumnsForAggregateSelector<T, C>,
-): DataFrame<T> {
-    @Suppress("UNCHECKED_CAST")
-    return Aggregators.percentileCommon<Comparable<Any>?>(percentile, skipNaN)
-        .aggregateFor(this, separate, columns as ColumnsForAggregateSelector<T, Comparable<Any>?>)
-}
+): DataFrame<T> = Aggregators.percentile.invoke(percentile, skipNaN).aggregateFor(this, separate, columns)
 
 public fun <T> PivotGroupBy<T>.percentileFor(
     percentile: Double,