Fixed incorrect columns in valueCounts of 0 rows

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

@@ -148,7 +148,13 @@ public fun <T> DataColumn<T>.valueCounts(
     }
     if (dropNA) grouped = grouped.filter { !it.first.isNA }
     val nulls = if (dropNA) false else hasNulls()
-    val values = DataColumn.createByType(name(), grouped.map { it.first }, type().withNullability(nulls))
+    val values =
+        if (grouped.isEmpty() && !isValueColumn()) {
+            // #2034 Preserve nested columns even when the input is empty
+            this.take(0)
+        } else {
+            DataColumn.createByType(name(), grouped.map { it.first }, type().withNullability(nulls))
+        }
     val countName = if (resultColumn == name()) resultColumn + "1" else resultColumn
     val counts = DataColumn.createByType(countName, grouped.map { it.second }, typeOf<Int>())
     return dataFrameOf(values, counts).cast()

core/src/test/kotlin/org/jetbrains/kotlinx/dataframe/api/valueCounts.kt

@@ -1,6 +1,7 @@
 package org.jetbrains.kotlinx.dataframe.api
 
 import io.kotest.matchers.shouldBe
+import org.jetbrains.kotlinx.dataframe.DataColumn
 import org.jetbrains.kotlinx.dataframe.nrow
 import org.junit.Test
 import kotlin.reflect.typeOf
@@ -104,6 +105,30 @@ class ValueCountsTests {
         result.rowsCount() shouldBe 0
     }
 
+    @Test
+    fun `value counts of an empty nullable value column preserves type when NA values are included`() {
+        val input = DataColumn.createByType("city", emptyList<String?>(), typeOf<String?>())
+        val result = input.valueCounts(dropNA = false)
+
+        result.columnNames() shouldBe listOf("city", "count")
+        result.nrow shouldBe 0
+        result["city"].isValueColumn() shouldBe true
+        result["city"].type() shouldBe typeOf<String?>()
+        result["count"].type() shouldBe typeOf<Int>()
+    }
+
+    @Test
+    fun `value counts of an empty nullable value column drops nullability when NA values are excluded`() {
+        val input = DataColumn.createByType("city", emptyList<String?>(), typeOf<String?>())
+        val result = input.valueCounts()
+
+        result.columnNames() shouldBe listOf("city", "count")
+        result.nrow shouldBe 0
+        result["city"].isValueColumn() shouldBe true
+        result["city"].type() shouldBe typeOf<String>()
+        result["count"].type() shouldBe typeOf<Int>()
+    }
+
     @Test
     fun `value counts of a column with a result column name clashing with the column name`() {
         val count by columnOf("a", "b", "a")
@@ -265,5 +290,50 @@ class ValueCountsTests {
         df.drop(df.nrow).valueCounts().count() shouldBe 0
     }
 
+    @Test
+    fun `value counts of an empty DataFrame retains all columns`() {
+        val result = df.take(0).valueCounts()
+
+        result.columnNames() shouldBe listOf("name", "city", "age", "count")
+        result.nrow shouldBe 0
+        result["name"].type() shouldBe typeOf<String>()
+        result["age"].type() shouldBe typeOf<Int>()
+        result["count"].type() shouldBe typeOf<Int>()
+    }
+
+    @Test
+    fun `value counts of an empty DataFrame retains selected columns`() {
+        val result = df.take(0).valueCounts("city")
+
+        result.columnNames() shouldBe listOf("city", "count")
+        result.nrow shouldBe 0
+        result["city"].type() shouldBe typeOf<String>()
+        result["count"].type() shouldBe typeOf<Int>()
+    }
+
+    @Test
+    fun `value counts retains selected columns when every row is dropped`() {
+        val input = dataFrameOf("city" to columnOf("London", null)).drop(1)
+        val result = input.valueCounts("city")
+
+        result.columnNames() shouldBe listOf("city", "count")
+        result.nrow shouldBe 0
+        result["city"].type() shouldBe typeOf<String>()
+        result["count"].type() shouldBe typeOf<Int>()
+    }
+
+    @Test
+    fun `value counts of an empty column group retains its observed columns`() {
+        val input = df.group("name", "city").into("details").take(0)
+        val result = input["details"].valueCounts()
+
+        result.columnNames() shouldBe listOf("details", "count")
+        result["details"].asColumnGroup().columnNames() shouldBe listOf("name", "city")
+        result.nrow shouldBe 0
+        result["details"].asColumnGroup()["name"].type() shouldBe typeOf<String>()
+        result["details"].asColumnGroup()["city"].type() shouldBe typeOf<String>()
+        result["count"].type() shouldBe typeOf<Int>()
+    }
+
     // endregion
 }