add public API to create dataframes with empty columns by a schema

It's needed in Kandy to create GroupBy with empty groups that can still be aggregated, as per added test

Author: koperagen

core/generated-sources/src/main/kotlin/org/jetbrains/kotlinx/dataframe/DataFrame.kt

@@ -16,7 +16,9 @@ import org.jetbrains.kotlinx.dataframe.impl.DataFrameSize
 import org.jetbrains.kotlinx.dataframe.impl.getColumnsImpl
 import org.jetbrains.kotlinx.dataframe.impl.headPlusArray
 import org.jetbrains.kotlinx.dataframe.impl.headPlusIterable
+import org.jetbrains.kotlinx.dataframe.impl.schema.createEmptyDataFrame
 import org.jetbrains.kotlinx.dataframe.impl.schema.createEmptyDataFrameOf
+import org.jetbrains.kotlinx.dataframe.schema.DataFrameSchema
 import kotlin.reflect.KType
 
 /**
@@ -33,6 +35,8 @@ public interface DataFrame<out T> : Aggregatable<T>, ColumnsContainer<T> {
         public fun empty(nrow: Int = 0): AnyFrame = if (nrow == 0) Empty else DataFrameImpl<Unit>(emptyList(), nrow)
 
         public inline fun <reified T> emptyOf(): DataFrame<T> = createEmptyDataFrameOf(T::class).cast()
+
+        public fun empty(schema: DataFrameSchema): AnyFrame = schema.createEmptyDataFrame()
     }
 
     // region columns

core/generated-sources/src/test/kotlin/org/jetbrains/kotlinx/dataframe/testSets/person/DataFrameTests.kt

@@ -2383,4 +2383,26 @@ class DataFrameTests : BaseTest() {
         val newName by column<String>()
         typed.select { name into newName and age }.columnNames() shouldBe listOf("newName", "age")
     }
+
+    @Test
+    fun `api for creating GroupBy with empty groups which can be aggregated using statistics`() {
+        val df1 = dataFrameOf("a", "b")(1, "c")
+        val df2 = DataFrame.empty()
+        val groupBy = dataFrameOf(columnOf("group1", "group2") named "group", columnOf(df1, df2)).asGroupBy()
+
+        shouldThrow<IllegalStateException> {
+            groupBy.aggregate {
+                sum("a")
+            }
+        }
+
+        val groupBy1 = groupBy
+            .updateGroups { if (it.isEmpty()) DataFrame.empty(groupBy.groups.schema.value) else it }
+
+        val res = groupBy1.aggregate {
+            sum("a")
+        }
+
+        res["aggregated"].values() shouldBe listOf(1, 0)
+    }
 }

core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/DataFrame.kt

@@ -16,7 +16,9 @@ import org.jetbrains.kotlinx.dataframe.impl.DataFrameSize
 import org.jetbrains.kotlinx.dataframe.impl.getColumnsImpl
 import org.jetbrains.kotlinx.dataframe.impl.headPlusArray
 import org.jetbrains.kotlinx.dataframe.impl.headPlusIterable
+import org.jetbrains.kotlinx.dataframe.impl.schema.createEmptyDataFrame
 import org.jetbrains.kotlinx.dataframe.impl.schema.createEmptyDataFrameOf
+import org.jetbrains.kotlinx.dataframe.schema.DataFrameSchema
 import kotlin.reflect.KType
 
 /**
@@ -33,6 +35,8 @@ public interface DataFrame<out T> : Aggregatable<T>, ColumnsContainer<T> {
         public fun empty(nrow: Int = 0): AnyFrame = if (nrow == 0) Empty else DataFrameImpl<Unit>(emptyList(), nrow)
 
         public inline fun <reified T> emptyOf(): DataFrame<T> = createEmptyDataFrameOf(T::class).cast()
+
+        public fun empty(schema: DataFrameSchema): AnyFrame = schema.createEmptyDataFrame()
     }
 
     // region columns

core/src/test/kotlin/org/jetbrains/kotlinx/dataframe/testSets/person/DataFrameTests.kt

@@ -2383,4 +2383,26 @@ class DataFrameTests : BaseTest() {
         val newName by column<String>()
         typed.select { name into newName and age }.columnNames() shouldBe listOf("newName", "age")
     }
+
+    @Test
+    fun `api for creating GroupBy with empty groups which can be aggregated using statistics`() {
+        val df1 = dataFrameOf("a", "b")(1, "c")
+        val df2 = DataFrame.empty()
+        val groupBy = dataFrameOf(columnOf("group1", "group2") named "group", columnOf(df1, df2)).asGroupBy()
+
+        shouldThrow<IllegalStateException> {
+            groupBy.aggregate {
+                sum("a")
+            }
+        }
+
+        val groupBy1 = groupBy
+            .updateGroups { if (it.isEmpty()) DataFrame.empty(groupBy.groups.schema.value) else it }
+
+        val res = groupBy1.aggregate {
+            sum("a")
+        }
+
+        res["aggregated"].values() shouldBe listOf(1, 0)
+    }
 }