Documentation improvements

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

@@ -821,6 +821,62 @@ class Modify : TestBase() {
         // SampleEnd
     }
 
+    private class CityInfo(val city: String?, val population: Int, val location: String)
+    private fun queryCityInfo(city: String?): CityInfo { return CityInfo(city, city?.length ?: 0, "35.5 32.2") }
+
+    @Test
+    fun addCalculatedApi() {
+        // SampleStart
+        class CityInfo(val city: String?, val population: Int, val location: String)
+        fun queryCityInfo(city: String?): CityInfo {
+            return CityInfo(city, city?.length ?: 0, "35.5 32.2")
+        }
+        // SampleEnd
+    }
+
+    @Test
+    fun addCalculated_properties() {
+        // SampleStart
+        val personWithCityInfo = df.add {
+            val cityInfo = city.map { queryCityInfo(it) }
+            "cityInfo" {
+                cityInfo.map { it.location } into CityInfo::location
+                cityInfo.map { it.population } into "population"
+            }
+        }
+        // SampleEnd
+        personWithCityInfo["cityInfo"]["population"] shouldBe df.city.map { it?.length ?: 0 }.named("population")
+    }
+
+    @Test
+    fun addCalculated_accessors() {
+        // SampleStart
+        val city by column<String?>()
+        val personWithCityInfo = df.add {
+            val cityInfo = city().map { queryCityInfo(it) }
+            "cityInfo" {
+                cityInfo.map { it.location } into CityInfo::location
+                cityInfo.map { it.population } into "population"
+            }
+        }
+        // SampleEnd
+        personWithCityInfo["cityInfo"]["population"] shouldBe df.city.map { it?.length ?: 0 }.named("population")
+    }
+
+    @Test
+    fun addCalculated_strings() {
+        // SampleStart
+        val personWithCityInfo = df.add {
+            val cityInfo = "city"<String?>().map { queryCityInfo(it) }
+            "cityInfo" {
+                cityInfo.map { it.location } into CityInfo::location
+                cityInfo.map { it.population } into "population"
+            }
+        }
+        // SampleEnd
+        personWithCityInfo["cityInfo"]["population"] shouldBe df.city.map { it?.length ?: 0 }.named("population")
+    }
+
     @Test
     fun addMany_properties() {
         // SampleStart

docs/StardustDocs/d.tree

@@ -25,7 +25,8 @@
         <toc-element id="DataColumn.md"/>
         <toc-element id="DataRow.md"/>
     </toc-element>
-    <toc-element id="operations.md">
+    <toc-element id="operations.md"/>
+    <toc-element toc-title="Operations">
         <toc-element id="create.md"  show-structure-depth="3">
             <toc-element id="createColumn.md" toc-title="DataColumn"/>
             <toc-element id="createDataFrame.md" toc-title="DataFrame"/>
@@ -172,4 +173,5 @@
         </toc-element>
     </toc-element>
     <toc-element id="gradleReference.md"/>
+    <toc-element href="https://github.com/Kotlin/dataframe/tree/master/examples" toc-title="Examples"/>
 </product-profile>

docs/StardustDocs/project.ihp

@@ -7,4 +7,7 @@
     <images dir="images" version="0.9" web-path="images/" />
     <vars src="v.list"/>
     <product src="d.tree" version="0.9" id="dataframe"/>
+    <settings>
+        <default-property element-name="toc-element" property-name="show-structure-depth" value="2"/>
+    </settings>
 </ihp>

docs/StardustDocs/topics/add.md

@@ -4,7 +4,7 @@
 
 Returns `DataFrame` which contains all columns from original `DataFrame` followed by newly added columns. Original `DataFrame` is not modified.
 
-**Create new column and add it to `DataFrame`:**
+## Create new column and add it to `DataFrame`
 
 ```text
 add(columnName: String) { rowExpression }
@@ -55,7 +55,7 @@ df.add("fibonacci") {
 
 <!---END-->
 
-**Create and add several columns to `DataFrame`:**
+## Create and add several columns to `DataFrame`
 
 ```kotlin
 add { 
@@ -64,7 +64,14 @@ add {
     ...
 }
 
-columnMapping = column into columnName | columnName from column | columnName from { rowExpression }
+columnMapping = column into columnName 
+    | columnName from column 
+    | columnName from { rowExpression }
+    | columnGroupName { 
+        columnMapping
+        columnMapping
+        ...
+    }
 ```
 
 <!---FUN addMany-->
@@ -123,7 +130,68 @@ df.add {
 </tab></tabs>
 <!---END-->
 
-**Add existing column to `DataFrame`:**
+### Create columns using intermediate result
+
+Consider this API:
+
+<!---FUN addCalculatedApi-->
+
+```kotlin
+class CityInfo(val city: String?, val population: Int, val location: String)
+fun queryCityInfo(city: String?): CityInfo {
+    return CityInfo(city, city?.length ?: 0, "35.5 32.2")
+}
+```
+
+<!---END-->
+
+Use the following approach to add multiple columns by calling the given API only once per row:
+
+<!---FUN addCalculated-->
+<tabs>
+<tab title="Properties">
+
+```kotlin
+val personWithCityInfo = df.add {
+    val cityInfo = city.map { queryCityInfo(it) }
+    "cityInfo" {
+        cityInfo.map { it.location } into CityInfo::location
+        cityInfo.map { it.population } into "population"
+    }
+}
+```
+
+</tab>
+<tab title="Accessors">
+
+```kotlin
+val city by column<String?>()
+val personWithCityInfo = df.add {
+    val cityInfo = city().map { queryCityInfo(it) }
+    "cityInfo" {
+        cityInfo.map { it.location } into CityInfo::location
+        cityInfo.map { it.population } into "population"
+    }
+}
+```
+
+</tab>
+<tab title="Strings">
+
+```kotlin
+val personWithCityInfo = df.add {
+    val cityInfo = "city"<String?>().map { queryCityInfo(it) }
+    "cityInfo" {
+        cityInfo.map { it.location } into CityInfo::location
+        cityInfo.map { it.population } into "population"
+    }
+}
+```
+
+</tab></tabs>
+<!---END-->
+
+## Add existing column to `DataFrame`
 
 <!---FUN addExisting-->
 
@@ -136,7 +204,7 @@ df + score
 
 <!---END-->
 
-**Add all columns from another `DataFrame`:**
+## Add all columns from another `DataFrame`
 
 <!---FUN addDfs-->
 

docs/StardustDocs/topics/operations.md

@@ -1,4 +1,4 @@
-[//]: # (title: Operations)
+[//]: # (title: Operations Overview)
 
 <!---IMPORT org.jetbrains.kotlinx.dataframe.samples.api.Modify-->
 

docs/StardustDocs/topics/types.md

@@ -1,4 +1,4 @@
-[//]: # (title: Types)
+[//]: # (title: Data Abstractions)
 
 * [`DataColumn`](DataColumn.md) is a named, typed and ordered collection of elements
 * [`DataFrame`](DataFrame.md) consists of one or several [`DataColumns`](DataColumn.md) with unique names and equal size

examples/README.md

@@ -1,12 +1,16 @@
 # Examples of Kotlin Dataframe
 
 ### Idea examples
-* [movies](idea-examples/movies)
+* [movies](idea-examples/movies) Using 3 different [Access APIs](https://kotlin.github.io/dataframe/apilevels.html) to perform data cleaning task
 * [titanic](idea-examples/titanic)
 * [youtube](idea-examples/youtube)
+* [json](idea-examples/json) Using OpenAPI support in DataFrame's Gradle and KSP plugins to access data from [API guru](https://apis.guru/) in a type-safe manner
 
 ### Notebook examples
 
+* people [Datalore](https://datalore.jetbrains.com/view/notebook/aOTioEClQQrsZZBKeUPAQj)
+Small artificial dataset used in [DataFrame API examples](https://kotlin.github.io/dataframe/operations.html) 
+
 * puzzles ([Jupyter](jupyter-notebooks/puzzles/40%20puzzles.ipynb)/[Datalore](https://datalore.jetbrains.com/view/notebook/CVp3br3CDXjUGaxxqfJjFF)) –
 Inspired [by 100 pandas puzzles](https://github.com/ajcr/100-pandas-puzzles). You will go from the simplest tasks to 
 complex problems where need to think. This notebook will show you how to solve these tasks with the Kotlin