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update README with copy-paste snippets for better first hands-on experience
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‎README.md‎

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@@ -37,143 +37,65 @@ You could find the following articles there:
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## Setup
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### Gradle for JVM
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```groovy
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// build.gradle
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plugins {
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// Optional Gradle plugin for enhanced type safety and schema generation
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// https://kotlin.github.io/dataframe/gradle.html
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id 'org.jetbrains.kotlinx.dataframe' version '0.12.0'
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}
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repositories {
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mavenCentral()
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}
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dependencies {
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implementation 'org.jetbrains.kotlinx:dataframe:0.12.0'
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}
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```kotlin
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implementation("org.jetbrains.kotlinx:dataframe:0.12.0")
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```
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Optional Gradle plugin for enhanced type safety and schema generation
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https://kotlin.github.io/dataframe/schemasgradle.html
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```kotlin
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// build.gradle.kts
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plugins {
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// Optional Gradle plugin for enhanced type safety and schema generation
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// https://kotlin.github.io/dataframe/gradle.html
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id("org.jetbrains.kotlinx.dataframe") version "0.12.0"
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}
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repositories {
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mavenCentral()
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}
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dependencies {
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implementation("org.jetbrains.kotlinx:dataframe:0.12.0")
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}
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id("org.jetbrains.kotlinx.dataframe") version "0.12.0"
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```
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### Gradle for Android
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```groovy
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// build.gradle
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plugins {
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// Optional Gradle plugin for enhanced type safety and schema generation
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// https://kotlin.github.io/dataframe/gradle.html
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id 'org.jetbrains.kotlinx.dataframe' version '0.12.0'
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}
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Check out [custom setup page](https://kotlin.github.io/dataframe/gettingstartedgradleadvanced.html) if you don't need some of the formats as dependencies,
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for Groovy and configurations specific for Android project
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dependencies {
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implementation 'org.jetbrains.kotlinx:dataframe:0.12.0'
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}
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## Getting started
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android {
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defaultConfig {
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minSdk 26 // Android O+
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}
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compileOptions {
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sourceCompatibility JavaVersion.VERSION_1_8
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targetCompatibility JavaVersion.VERSION_1_8
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}
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kotlinOptions {
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jvmTarget = '1.8'
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}
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packagingOptions {
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resources {
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pickFirsts = ["META-INF/AL2.0",
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"META-INF/LGPL2.1",
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"META-INF/ASL-2.0.txt",
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"META-INF/LICENSE.md",
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"META-INF/NOTICE.md",
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"META-INF/LGPL-3.0.txt"]
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excludes = ["META-INF/kotlin-jupyter-libraries/libraries.json",
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"META-INF/{INDEX.LIST,DEPENDENCIES}",
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"{draftv3,draftv4}/schema",
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"arrow-git.properties"]
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}
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}
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}
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// optional, could be required for KSP
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tasks.withType(KotlinCompile).configureEach {
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kotlinOptions {
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jvmTarget = '1.8'
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}
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}
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```kotlin
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import org.jetbrains.kotlinx.dataframe.*
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import org.jetbrains.kotlinx.dataframe.api.*
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import org.jetbrains.kotlinx.dataframe.io.*
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```
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```kotlin
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// build.gradle.kts
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val df = DataFrame.read("https://raw.githubusercontent.com/Kotlin/dataframe/master/data/jetbrains_repositories.csv")
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df["full_name"][0] // Indexing https://kotlin.github.io/dataframe/access.html
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plugins {
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// Optional Gradle plugin for enhanced type safety and schema generation
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// https://kotlin.github.io/dataframe/gradle.html
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id("org.jetbrains.kotlinx.dataframe") version "0.12.0"
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}
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df.filter { "stargazers_count"<Int>() > 50 }.print()
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```
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dependencies {
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implementation("org.jetbrains.kotlinx:dataframe:0.12.0")
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}
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## Getting started with data schema
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android {
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defaultConfig {
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minSdk = 26 // Android O+
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}
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compileOptions {
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sourceCompatibility = JavaVersion.VERSION_1_8
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targetCompatibility = JavaVersion.VERSION_1_8
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}
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kotlinOptions {
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jvmTarget = "1.8"
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}
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packaging {
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resources {
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pickFirsts += listOf(
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"META-INF/AL2.0",
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"META-INF/LGPL2.1",
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"META-INF/ASL-2.0.txt",
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"META-INF/LICENSE.md",
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"META-INF/NOTICE.md",
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"META-INF/LGPL-3.0.txt",
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)
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excludes += listOf(
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"META-INF/kotlin-jupyter-libraries/libraries.json",
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"META-INF/{INDEX.LIST,DEPENDENCIES}",
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"{draftv3,draftv4}/schema",
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"arrow-git.properties",
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)
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}
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}
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}
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Requires Gradle plugin to work
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```kotlin
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id("org.jetbrains.kotlinx.dataframe") version "0.12.0"
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```
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Plugin generates extension properties API for provided sample of data. Column names and their types become discoverable in completion.
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// required for KSP
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tasks.withType<org.jetbrains.kotlin.gradle.tasks.KotlinCompile> {
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kotlinOptions.jvmTarget = "1.8"
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```kotlin
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// Make sure to place file annotation above package directive
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@file:ImportDataSchema(
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"Repository",
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"https://raw.githubusercontent.com/Kotlin/dataframe/master/data/jetbrains_repositories.csv",
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)
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package example
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import org.jetbrains.kotlinx.dataframe.annotations.ImportDataSchema
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import org.jetbrains.kotlinx.dataframe.api.*
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fun main() {
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// execute `assemble` to generate extension properties API
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val df = Repository.readCSV()
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df.fullName[0]
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df.filter { stargazersCount > 50 }
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}
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```
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### Jupyter Notebook
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## Getting started in Jupyter Notebook / Kotlin Notebook
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Install [Kotlin kernel](https://github.com/Kotlin/kotlin-jupyter) for [Jupyter](https://jupyter.org/)
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%use dataframe(<version>)
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```
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```kotlin
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val df = DataFrame.read("https://raw.githubusercontent.com/Kotlin/dataframe/master/data/jetbrains_repositories.csv")
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df // last expression in the cell is displayed
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```
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When cell with variable declaration is executed, in the next cell `DataFrame` provides extension properties API based on data
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```kotlin
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df.filter { stargazers_count > 50 }
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```
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## Data model
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* `DataFrame` is a list of columns with equal sizes and distinct names.
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* `DataColumn` is a named list of values. Can be one of three kinds:
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* `ValueColumn` — contains data
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* `ColumnGroup` — contains columns
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* `FrameColumn` — contains dataframes
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## Usage example
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## Syntax example
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Let us show you how data cleaning and aggregation pipeline could look like with DataFrame.
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**Create:**
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```kotlin
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}
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```
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[Try it in **Datalore**](https://datalore.jetbrains.com/view/notebook/vq5j45KWkYiSQnACA2Ymij) and explore [**more examples here**](examples).
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Check it on [**Datalore**](https://datalore.jetbrains.com/view/notebook/vq5j45KWkYiSQnACA2Ymij) to get better visual impression of what happens and how hierarchical DataFrame structure looks like.
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Explore [**more examples here**](examples).
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## Kotlin, Kotlin Jupyter, OpenAPI, Arrow and JDK versions
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‎docs/StardustDocs/topics/gettingStartedJupyterNotebook.md‎

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```
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After loading, all essential types will be already imported, so you can start using the Kotlin DataFrame library. Enjoy!
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```kotlin
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val df = DataFrame.read("https://raw.githubusercontent.com/Kotlin/dataframe/master/data/jetbrains_repositories.csv")
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df // last expression in the cell is displayed
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```
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When previous cell with variable declaration is executed, `DataFrame` provides data schema API based on data:
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```kotlin
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df.filter { stargazers_count > 50 }
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```

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