| import org.jetbrains.kotlinx.dataframe.* | |
| import org.jetbrains.kotlinx.dataframe.annotations.* | |
| import org.jetbrains.kotlinx.dataframe.api.* | |
| import org.jetbrains.kotlinx.dataframe.io.* | |
| import java.math.BigInteger | |
| fun box(): String { | |
| // multiple columns | |
| val personsDf = dataFrameOf( | |
| "name", "age", "city", "weight", "height", "yearsToRetirement", "workExperienceYears", "dependentsCount", "annualIncome", "bigNumber", | |
| )( | |
| "Alice", 15, "London", 99.5, "1.85", 50f, 0.toShort(), 0.toByte(), 0L, BigInteger.valueOf(23L), | |
| "Bob", 20, "Paris", 140.0, "1.35", 45f, 2.toShort(), 0.toByte(), 12000L, BigInteger.valueOf(12L), | |
| "Charlie", 100, "Dubai", 75.0, "1.95", 0f, 70.toShort(), 0.toByte(), 0L, BigInteger.valueOf(68798L), | |
| "Rose", 1, "Moscow", 45.33, "0.79", 64f, 0.toShort(), 2.toByte(), 0L, BigInteger.valueOf(46556L), | |
| "Dylan", 35, "London", 23.4, "1.83", 30f, 15.toShort(), 1.toByte(), 90000L, BigInteger.valueOf(235L), | |
| "Eve", 40, "Paris", 56.72, "1.85", 25f, 18.toShort(), 3.toByte(), 125000L, BigInteger.valueOf(-23534L), | |
| "Frank", 55, "Dubai", 78.9, "1.35", 10f, 35.toShort(), 2.toByte(), 145000L, BigInteger.valueOf(235L), | |
| "Grace", 29, "Moscow", 67.8, "1.65", 36f, 5.toShort(), 1.toByte(), 70000L, BigInteger.valueOf(0L), | |
| "Hank", 60, "Paris", 80.22, "1.75", 5f, 40.toShort(), 4.toByte(), 200000L, BigInteger.valueOf(-4L), | |
| "Isla", 22, "London", 75.1, "1.85", 43f, 1.toShort(), 0.toByte(), 30000L, BigInteger.valueOf(2345L), | |
| ) | |
| // scenario #0: all numerical columns | |
| personsDf.sum().let { row -> | |
| row.df().compareSchemas() | |
| val sum01: Int = row.age | |
| val sum02: Double = row.weight | |
| val sum03: Float = row.yearsToRetirement | |
| val sum04: Int = row.workExperienceYears | |
| val sum05: Int = row.dependentsCount | |
| val sum06: Long = row.annualIncome | |
| } | |
| // scenario #1: particular column | |
| personsDf.sumFor { age }.let { row -> | |
| row.df().compareSchemas() | |
| val sum11: Int = row.age | |
| } | |
| // scenario #1.1: particular column with converted type | |
| personsDf.sumFor { dependentsCount }.let { row -> | |
| row.df().compareSchemas() | |
| val sum111: Int = row.dependentsCount | |
| } | |
| // scenario #2: sum of values per columns separately | |
| personsDf.sumFor { age and weight and workExperienceYears and dependentsCount and annualIncome }.let { row -> | |
| row.df().compareSchemas() | |
| val sum31: Int = row.age | |
| val sum32: Double = row.weight | |
| val sum33: Int = row.workExperienceYears | |
| val sum34: Int = row.dependentsCount | |
| val sum35: Long = row.annualIncome | |
| } | |
| return "OK" | |
| } |