init research

2026-02-08 11:20:43 -10:00
commit bdf064f54d
3041 changed files with 1592200 additions and 0 deletions
@@ -0,0 +1,65 @@
+import org.jetbrains.kotlinx.dataframe.*
+import org.jetbrains.kotlinx.dataframe.annotations.*
+import org.jetbrains.kotlinx.dataframe.api.*
+import org.jetbrains.kotlinx.dataframe.io.*
+
+fun box(): String {
+    // multiple columns
+    val personsDf = dataFrameOf(
+        "name",
+        "age",
+        "city",
+        "weight",
+        "height",
+        "yearsToRetirement",
+        "workExperienceYears",
+        "dependentsCount",
+        "annualIncome"
+    )(
+        "Alice", 15, "London", 99.5, "1.85", 50, 0.toShort(), 0.toByte(), 0L,
+        "Bob", 20, "Paris", 140.0, "1.35", 45, 2.toShort(), 0.toByte(), 12000L,
+        "Charlie", 100, "Dubai", 75.0, "1.95", 0, 70.toShort(), 0.toByte(), 0L,
+        "Rose", 1, "Moscow", 45.33, "0.79", 64, 0.toShort(), 2.toByte(), 0L,
+        "Dylan", 35, "London", 23.4, "1.83", 30, 15.toShort(), 1.toByte(), 90000L,
+        "Eve", 40, "Paris", 56.72, "1.85", 25, 18.toShort(), 3.toByte(), 125000L,
+        "Frank", 55, "Dubai", 78.9, "1.35", 10, 35.toShort(), 2.toByte(), 145000L,
+        "Grace", 29, "Moscow", 67.8, "1.65", 36, 5.toShort(), 1.toByte(), 70000L,
+        "Hank", 60, "Paris", 80.22, "1.75", 5, 40.toShort(), 4.toByte(), 200000L,
+        "Isla", 22, "London", 75.1, "1.85", 43, 1.toShort(), 0.toByte(), 30000L,
+    )
+
+    // scenario #0: all numerical columns
+    val res0 = personsDf.std()
+    res0.df().compareSchemas()
+
+    val std01: Double? = res0.age
+    val std02: Double? = res0.weight
+    val std03: Double? = res0.yearsToRetirement
+    val std04: Double? = res0.workExperienceYears
+    val std05: Double? = res0.dependentsCount
+    val std06: Double? = res0.annualIncome
+
+    // scenario #1: particular column
+    val res1 = personsDf.stdFor { age }
+    res1.df().compareSchemas()
+
+    val std11: Double? = res1.age
+
+    // scenario #1.1: particular column with converted type
+    val res11 = personsDf.stdFor { dependentsCount }
+    res11.df().compareSchemas()
+
+    val std111: Double? = res11.dependentsCount
+
+    // scenario #2: std of values per columns separately
+    val res3 = personsDf.stdFor { age and weight and workExperienceYears and dependentsCount and annualIncome }
+    res3.df().compareSchemas()
+
+    val std31: Double? = res3.age
+    val std32: Double? = res3.weight
+    val std33: Double? = res3.workExperienceYears
+    val std34: Double? = res3.dependentsCount
+    val std35: Double? = res3.annualIncome
+
+    return "OK"
+}