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Mar 24, 2023
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Overload toDataFrame for basic types to avoid surprising results #314

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4a826a5
Overload toDataFrame for basic types to avoid surprising results
koperagen Mar 20, 2023
ef8c188
rename OfSingleValueColumn -> ValueProperty
koperagen Mar 23, 2023
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78 changes: 78 additions & 0 deletions core/src/main/kotlin/org/jetbrains/kotlinx/dataframe/api/toDataFrame.kt
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Expand Up @@ -7,6 +7,7 @@ import org.jetbrains.kotlinx.dataframe.ColumnsSelector
import org.jetbrains.kotlinx.dataframe.DataColumn
import org.jetbrains.kotlinx.dataframe.DataFrame
import org.jetbrains.kotlinx.dataframe.DataRow
import org.jetbrains.kotlinx.dataframe.annotations.DataSchema
import org.jetbrains.kotlinx.dataframe.columns.ColumnPath
import org.jetbrains.kotlinx.dataframe.impl.ColumnNameGenerator
import org.jetbrains.kotlinx.dataframe.impl.api.createDataFrameImpl
Expand Down Expand Up @@ -187,6 +188,83 @@ public abstract class CreateDataFrameDsl<T> : TraversePropertiesDsl {

// endregion

// region toDataFrame overloads for built-in types

/*
Without overloads Iterable<String>.toDataFrame produces unexpected result


```
val string = listOf("aaa", "aa", null)
string.toDataFrame()
```
=>
length
0 3
1 2
2 null
*/

@JvmName("toDataFrameByte")
public inline fun <reified B : Byte?> Iterable<B>.toDataFrame(): DataFrame<ValueProperty<B>> = toDataFrame {
ValueProperty<B>::value from { it }
}.cast()

@JvmName("toDataFrameShort")
public inline fun <reified S : Short?> Iterable<S>.toDataFrame(): DataFrame<ValueProperty<S>> = toDataFrame {
ValueProperty<S>::value from { it }
}.cast()

@JvmName("toDataFrameInt")
public inline fun <reified I : Int?> Iterable<I>.toDataFrame(): DataFrame<ValueProperty<I>> = toDataFrame {
ValueProperty<I>::value from { it }
}.cast()

@JvmName("toDataFrameLong")
public inline fun <reified L : Long?> Iterable<L>.toDataFrame(): DataFrame<ValueProperty<L>> = toDataFrame {
ValueProperty<L>::value from { it }
}.cast()

@JvmName("toDataFrameString")
public inline fun <reified S : String?> Iterable<S>.toDataFrame(): DataFrame<ValueProperty<S>> = toDataFrame {
ValueProperty<S>::value from { it }
}.cast()

@JvmName("toDataFrameChar")
public inline fun <reified C : Char?> Iterable<C>.toDataFrame(): DataFrame<ValueProperty<C>> = toDataFrame {
ValueProperty<C>::value from { it }
}.cast()

@JvmName("toDataFrameBoolean")
public inline fun <reified B : Boolean?> Iterable<B>.toDataFrame(): DataFrame<ValueProperty<B>> = toDataFrame {
ValueProperty<B>::value from { it }
}.cast()

@JvmName("toDataFrameUByte")
public inline fun <reified U : UByte?> Iterable<U>.toDataFrame(): DataFrame<ValueProperty<U>> = toDataFrame {
ValueProperty<U>::value from { it }
}.cast()

@JvmName("toDataFrameUShort")
public inline fun <reified U : UShort?> Iterable<U>.toDataFrame(): DataFrame<ValueProperty<U>> = toDataFrame {
ValueProperty<U>::value from { it }
}.cast()

@JvmName("toDataFrameUInt")
public inline fun <reified U : UInt?> Iterable<U>.toDataFrame(): DataFrame<ValueProperty<U>> = toDataFrame {
ValueProperty<U>::value from { it }
}.cast()

@JvmName("toDataFrameULong")
public inline fun <reified U : ULong?> Iterable<U>.toDataFrame(): DataFrame<ValueProperty<U>> = toDataFrame {
ValueProperty<U>::value from { it }
}.cast()

@DataSchema
public interface ValueProperty<T> {
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Could maybe be moved to a separate file, similar to KeyValueProperty :)

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I'd prefer it here, doesn't have much value on its own i think

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thought the same about KeyValueProperty, but who knows, we cannot know everything a user might want :) And a value-only DataSchema seems to me exactly the sort of thing people might want to use (or create themselves)

public val value: T
}

// region Create DataFrame from Map

public fun Map<String, Iterable<Any?>>.toDataFrame(): AnyFrame {
Expand Down
27 changes: 27 additions & 0 deletions core/src/test/kotlin/org/jetbrains/kotlinx/dataframe/api/toDataFrame.kt
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Expand Up @@ -3,10 +3,12 @@ package org.jetbrains.kotlinx.dataframe.api
import io.kotest.matchers.shouldBe
import org.jetbrains.kotlinx.dataframe.DataFrame
import org.jetbrains.kotlinx.dataframe.DataRow
import org.jetbrains.kotlinx.dataframe.alsoDebug
import org.jetbrains.kotlinx.dataframe.annotations.DataSchema
import org.jetbrains.kotlinx.dataframe.columns.ColumnKind
import org.jetbrains.kotlinx.dataframe.kind
import org.jetbrains.kotlinx.dataframe.type
import org.junit.Ignore
import org.junit.Test
import kotlin.reflect.typeOf

Expand Down Expand Up @@ -197,4 +199,29 @@ class CreateDataFrameTests {

df["name"][0] shouldBe name
}

@Test
fun builtInTypes() {
val string = listOf("aaa", "aa", null)
string.toDataFrame().also { it.print() } shouldBe dataFrameOf("value")(*string.toTypedArray())

val int = listOf(1, 2, 3)
int.toDataFrame().alsoDebug() shouldBe dataFrameOf("value")(*int.toTypedArray())
}

@Ignore
@Test
fun generateBuiltInsOverrides() {
listOf("Byte", "Short", "Int", "Long", "String", "Char", "Boolean", "UByte", "UShort", "UInt", "ULong").forEach { type ->
val typeParameter = type.first()
val func = """
@JvmName("toDataFrame$type")
public inline fun <reified $typeParameter : $type?> Iterable<$typeParameter>.toDataFrame(): DataFrame<ValueProperty<$typeParameter>> = toDataFrame {
ValueProperty<$typeParameter>::value from { it }
}.cast()
""".trimIndent()
println(func)
println()
}
}
}
13 changes: 13 additions & 0 deletions core/src/test/kotlin/org/jetbrains/kotlinx/dataframe/samples/api/Create.kt
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@@ -1,7 +1,9 @@
package org.jetbrains.kotlinx.dataframe.samples.api

import io.kotest.matchers.shouldBe
import org.jetbrains.kotlinx.dataframe.DataFrame
import org.jetbrains.kotlinx.dataframe.api.Infer
import org.jetbrains.kotlinx.dataframe.api.ValueProperty
import org.jetbrains.kotlinx.dataframe.api.add
import org.jetbrains.kotlinx.dataframe.api.column
import org.jetbrains.kotlinx.dataframe.api.columnGroup
Expand All @@ -18,6 +20,7 @@ import org.jetbrains.kotlinx.dataframe.api.sortBy
import org.jetbrains.kotlinx.dataframe.api.toColumn
import org.jetbrains.kotlinx.dataframe.api.toColumnOf
import org.jetbrains.kotlinx.dataframe.api.toDataFrame
import org.jetbrains.kotlinx.dataframe.api.value
import org.jetbrains.kotlinx.dataframe.api.withValues
import org.jetbrains.kotlinx.dataframe.columns.ColumnKind
import org.jetbrains.kotlinx.dataframe.kind
Expand Down Expand Up @@ -314,6 +317,16 @@ class Create : TestBase() {
df["age"].type() shouldBe typeOf<Int>()
}

@Test
fun readDataFrameFromValues() {
// SampleStart
val names = listOf("Alice", "Bob", "Charlie")
val df: DataFrame<ValueProperty<String>> = names.toDataFrame()
df.add("length") { value.length }
// SampleEnd
df.value.toList() shouldBe names
}

@Test
fun readDataFrameFromObject() {
// SampleStart
Expand Down
14 changes: 14 additions & 0 deletions docs/StardustDocs/topics/createDataFrame.md
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Expand Up @@ -134,6 +134,20 @@ map.toDataFrame()

<!---END-->

[`DataFrame`](DataFrame.md) from [`Iterable`](https://kotlinlang.org/api/latest/jvm/stdlib/kotlin.collections/-iterable/) of [basic types](https://kotlinlang.org/docs/basic-types.html) (except arrays):

Return type of these overloads is a typed DataFrame. Its data schema defines column that can be used right after conversion for additional computations

<!---FUN readDataFrameFromValues-->

```kotlin
val names = listOf("Alice", "Bob", "Charlie")
val df: DataFrame<ValueProperty<String>> = names.toDataFrame()
df.add("length") { value.length }
```

<!---END-->

[`DataFrame`](DataFrame.md) from [`Iterable`](https://kotlinlang.org/api/latest/jvm/stdlib/kotlin.collections/-iterable/) of objects:

<!---FUN readDataFrameFromObject-->
Expand Down