implementation("org.jetbrains.kotlinx:dataframe:0.15.0")

id("org.jetbrains.kotlinx.dataframe") version "0.15.0"

import org.jetbrains.kotlinx.dataframe.* import org.jetbrains.kotlinx.dataframe.api.* import org.jetbrains.kotlinx.dataframe.io.*

val df = DataFrame.read("https://raw.githubusercontent.com/Kotlin/dataframe/master/data/jetbrains_repositories.csv") df["full_name"][0] // Indexing https://kotlin.github.io/dataframe/access.html df.filter { "stargazers_count"<Int>() > 50 }.print() 

id("org.jetbrains.kotlinx.dataframe") version "0.15.0"

// Make sure to place the file annotation above the package directive @file:ImportDataSchema( "Repository", "https://raw.githubusercontent.com/Kotlin/dataframe/master/data/jetbrains_repositories.csv", ) package example import org.jetbrains.kotlinx.dataframe.annotations.ImportDataSchema import org.jetbrains.kotlinx.dataframe.api.* fun main() { // execute `assemble` to generate extension properties API val df = Repository.readCSV() df.fullName[0] df.filter { stargazersCount > 50 } }

val df = DataFrame.read("https://raw.githubusercontent.com/Kotlin/dataframe/master/data/jetbrains_repositories.csv") df // the last expression in the cell is displayed

df.filter { stargazers_count > 50 }

// create columns val fromTo by columnOf("LoNDon_paris", "MAdrid_miLAN", "londON_StockhOlm", "Budapest_PaRis", "Brussels_londOn") val flightNumber by columnOf(10045.0, Double.NaN, 10065.0, Double.NaN, 10085.0) val recentDelays by columnOf("23,47", null, "24, 43, 87", "13", "67, 32") val airline by columnOf("KLM(!)", "{Air France} (12)", "(British Airways. )", "12. Air France", "'Swiss Air'") // create dataframe val df = dataFrameOf(fromTo, flightNumber, recentDelays, airline) // print dataframe df.print()

// typed accessors for columns // that will appear during // dataframe transformation val origin by column<String>() val destination by column<String>() val clean = df // fill missing flight numbers .fillNA { flightNumber }.with { prev()!!.flightNumber + 10 } // convert flight numbers to int .convert { flightNumber }.toInt() // clean 'airline' column .update { airline }.with { "([a-zA-Z\\s]+)".toRegex().find(it)?.value ?: "" } // split 'fromTo' column into 'origin' and 'destination' .split { fromTo }.by("_").into(origin, destination) // clean 'origin' and 'destination' columns .update { origin and destination }.with { it.lowercase().replaceFirstChar(Char::uppercase) } // split lists of delays in 'recentDelays' into separate columns // 'delay1', 'delay2'... and nest them inside original column `recentDelays` .split { recentDelays }.inward { "delay$it" } // convert string values in `delay1`, `delay2` into ints .parse { recentDelays }

clean // group by the flight origin renamed into "from" .groupBy { origin named "from" }.aggregate { // we are in the context of a single data group // total number of flights from origin count() into "count" // list of flight numbers flightNumber into "flight numbers" // counts of flights per airline airline.valueCounts() into "airlines" // max delay across all delays in `delay1` and `delay2` recentDelays.maxOrNull { delay1 and delay2 } into "major delay" // separate lists of recent delays for `delay1`, `delay2` and `delay3` recentDelays.implode(dropNA = true) into "recent delays" // total delay per destination pivot { destination }.sum { recentDelays.colsOf<Int?>() } into "total delays to" }