{
"cells": [
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:25.849389Z",
"start_time": "2025-05-28T10:16:18.604191Z"
}
},
"cell_type": "code",
"source": "%use dataframe",
"outputs": [],
"execution_count": 1
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:33.602396Z",
"start_time": "2025-05-28T10:16:25.875493Z"
}
},
"source": [
"%useLatestDescriptors\n",
"%use kandy"
],
"outputs": [],
"execution_count": 2
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:38.183961Z",
"start_time": "2025-05-28T10:16:33.616915Z"
}
},
"source": [
"val df = DataFrame.readCsv(\n",
" fileOrUrl = \"titanic.csv\",\n",
" delimiter = ';',\n",
" parserOptions = ParserOptions(locale = java.util.Locale.FRENCH),\n",
")\n",
"\n",
"df.head()"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
"
\n",
" \n",
" \n",
" \n",
" pclass survived name sex age sibsp parch ticket fare cabin embarked boat body homedest 1 1 Allen, Miss. Elisabeth Walton null 29.000000 null null 24160 211.337500 B5 null 2 null St Louis, MO 1 1 Allison, Master. Hudson Trevor male 0.916700 1 2 113781 151.550000 C22 C26 AA 11 null Montreal, PQ / Chesterville, ON 1 0 Allison, Miss. Helen Loraine female 2.000000 1 2 113781 151.550000 C22 C26 S null null Montreal, PQ / Chesterville, ON 1 0 Allison, Mr. Hudson Joshua Creighton male 30.000000 1 2 113781 151.550000 C22 C26 S null 135 Montreal, PQ / Chesterville, ON 1 0 Allison, Mrs. Hudson J C (Bessie Wald... female 25.000000 1 2 113781 151.550000 C22 C26 S null null Montreal, PQ / Chesterville, ON
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"pclass\",\"survived\",\"name\",\"sex\",\"age\",\"sibsp\",\"parch\",\"ticket\",\"fare\",\"cabin\",\"embarked\",\"boat\",\"body\",\"homedest\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"}],\"nrow\":5,\"ncol\":14},\"kotlin_dataframe\":[{\"pclass\":1,\"survived\":1,\"name\":\"Allen, Miss. Elisabeth Walton\",\"sex\":null,\"age\":29.0,\"sibsp\":null,\"parch\":null,\"ticket\":\"24160\",\"fare\":211.3375,\"cabin\":\"B5\",\"embarked\":null,\"boat\":\"2\",\"body\":null,\"homedest\":\"St Louis, MO\"},{\"pclass\":1,\"survived\":1,\"name\":\"Allison, Master. Hudson Trevor\",\"sex\":\"male\",\"age\":0.9167,\"sibsp\":1,\"parch\":2,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"AA\",\"boat\":\"11\",\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Miss. Helen Loraine\",\"sex\":\"female\",\"age\":2.0,\"sibsp\":1,\"parch\":2,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Mr. Hudson Joshua Creighton\",\"sex\":\"male\",\"age\":30.0,\"sibsp\":1,\"parch\":2,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":135,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)\",\"sex\":\"female\",\"age\":25.0,\"sibsp\":1,\"parch\":2,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"}]}"
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"We have a dataset that uses an alternative pattern for decimal numbers. This is a reason why the French locale will be used in the example.\n",
"\n",
"But before data conversion, we should handle *null* values."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:38.794245Z",
"start_time": "2025-05-28T10:16:38.197758Z"
}
},
"source": [
"df.describe()"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" name type count unique nulls top freq mean std min p25 median p75 max pclass Int 1309 3 0 3 709 2.294882 0.837836 1 2.000000 3.000000 3.000000 3 survived Int 1309 2 0 0 809 0.381971 0.486055 0 0.000000 0.000000 1.000000 1 name String 1309 1307 0 Connolly, Miss. Kate 2 null null Abbing, Mr. Anthony Devaney, Miss. Margaret Delia Kink, Miss. Maria Quick, Mrs. Frederick Charles (Jane R... van Melkebeke, Mr. Philemon sex String? 1309 3 1 male 843 null null female female male male male age Double? 1309 99 263 24.000000 47 29.881135 14.413500 0.166700 21.000000 28.000000 39.000000 80.000000 sibsp Int? 1309 8 1 0 890 0.499235 1.041965 0 0.000000 0.000000 1.000000 8 parch Int? 1309 9 1 0 1001 0.385321 0.865826 0 0.000000 0.000000 0.000000 9 ticket String 1309 929 0 CA. 2343 11 null null 110152 248738 347082 A/5 3536 WE/P 5735 fare Double? 1309 282 1 8.050000 60 33.295479 51.758668 0.000000 7.895800 14.454200 31.275000 512.329200 cabin String? 1309 187 1014 C23 C25 C27 6 null null A10 B73 C62 C64 D48 T embarked String? 1309 5 3 S 912 null null AA Q S S S boat String? 1309 28 823 13 39 null null 1 14 3 8 D body Int? 1309 122 1188 135 1 160.809917 97.696922 1 71.333333 155.000000 256.666667 328 homedest String? 1309 370 564 New York, NY 64 null null ?Havana, Cuba England Lucca, Italy / California Provo, UT Zurich, Switzerland
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"name\",\"type\",\"count\",\"unique\",\"nulls\",\"top\",\"freq\",\"mean\",\"std\",\"min\",\"p25\",\"median\",\"p75\",\"max\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Comparable<*>\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Comparable<*>\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Comparable<*>\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Comparable<*>\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Comparable<*>\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Comparable<*>\"}],\"nrow\":14,\"ncol\":14},\"kotlin_dataframe\":[{\"name\":\"pclass\",\"type\":\"Int\",\"count\":1309,\"unique\":3,\"nulls\":0,\"top\":\"3\",\"freq\":709,\"mean\":2.294881588999236,\"std\":0.837836018970131,\"min\":\"1\",\"p25\":\"2.0\",\"median\":\"3.0\",\"p75\":\"3.0\",\"max\":\"3\"},{\"name\":\"survived\",\"type\":\"Int\",\"count\":1309,\"unique\":2,\"nulls\":0,\"top\":\"0\",\"freq\":809,\"mean\":0.3819709702062643,\"std\":0.48605517086648004,\"min\":\"0\",\"p25\":\"0.0\",\"median\":\"0.0\",\"p75\":\"1.0\",\"max\":\"1\"},{\"name\":\"name\",\"type\":\"String\",\"count\":1309,\"unique\":1307,\"nulls\":0,\"top\":\"Connolly, Miss. Kate\",\"freq\":2,\"mean\":null,\"std\":null,\"min\":\"Abbing, Mr. Anthony\",\"p25\":\"Devaney, Miss. Margaret Delia\",\"median\":\"Kink, Miss. Maria\",\"p75\":\"Quick, Mrs. Frederick Charles (Jane Richards)\",\"max\":\"van Melkebeke, Mr. Philemon\"},{\"name\":\"sex\",\"type\":\"String?\",\"count\":1309,\"unique\":3,\"nulls\":1,\"top\":\"male\",\"freq\":843,\"mean\":null,\"std\":null,\"min\":\"female\",\"p25\":\"female\",\"median\":\"male\",\"p75\":\"male\",\"max\":\"male\"},{\"name\":\"age\",\"type\":\"Double?\",\"count\":1309,\"unique\":99,\"nulls\":263,\"top\":\"24.0\",\"freq\":47,\"mean\":29.8811345124283,\"std\":14.413499699923594,\"min\":\"0.1667\",\"p25\":\"21.0\",\"median\":\"28.0\",\"p75\":\"39.0\",\"max\":\"80.0\"},{\"name\":\"sibsp\",\"type\":\"Int?\",\"count\":1309,\"unique\":8,\"nulls\":1,\"top\":\"0\",\"freq\":890,\"mean\":0.49923547400611623,\"std\":1.041965373922986,\"min\":\"0\",\"p25\":\"0.0\",\"median\":\"0.0\",\"p75\":\"1.0\",\"max\":\"8\"},{\"name\":\"parch\",\"type\":\"Int?\",\"count\":1309,\"unique\":9,\"nulls\":1,\"top\":\"0\",\"freq\":1001,\"mean\":0.3853211009174312,\"std\":0.8658257885990794,\"min\":\"0\",\"p25\":\"0.0\",\"median\":\"0.0\",\"p75\":\"0.0\",\"max\":\"9\"},{\"name\":\"ticket\",\"type\":\"String\",\"count\":1309,\"unique\":929,\"nulls\":0,\"top\":\"CA. 2343\",\"freq\":11,\"mean\":null,\"std\":null,\"min\":\"110152\",\"p25\":\"248738\",\"median\":\"347082\",\"p75\":\"A/5 3536\",\"max\":\"WE/P 5735\"},{\"name\":\"fare\",\"type\":\"Double?\",\"count\":1309,\"unique\":282,\"nulls\":1,\"top\":\"8.05\",\"freq\":60,\"mean\":33.29547928134572,\"std\":51.758668239174135,\"min\":\"0.0\",\"p25\":\"7.8958\",\"median\":\"14.4542\",\"p75\":\"31.275\",\"max\":\"512.3292\"},{\"name\":\"cabin\",\"type\":\"String?\",\"count\":1309,\"unique\":187,\"nulls\":1014,\"top\":\"C23 C25 C27\",\"freq\":6,\"mean\":null,\"std\":null,\"min\":\"A10\",\"p25\":\"B73\",\"median\":\"C62 C64\",\"p75\":\"D48\",\"max\":\"T\"},{\"name\":\"embarked\",\"type\":\"String?\",\"count\":1309,\"unique\":5,\"nulls\":3,\"top\":\"S\",\"freq\":912,\"mean\":null,\"std\":null,\"min\":\"AA\",\"p25\":\"Q\",\"median\":\"S\",\"p75\":\"S\",\"max\":\"S\"},{\"name\":\"boat\",\"type\":\"String?\",\"count\":1309,\"unique\":28,\"nulls\":823,\"top\":\"13\",\"freq\":39,\"mean\":null,\"std\":null,\"min\":\"1\",\"p25\":\"14\",\"median\":\"3\",\"p75\":\"8\",\"max\":\"D\"},{\"name\":\"body\",\"type\":\"Int?\",\"count\":1309,\"unique\":122,\"nulls\":1188,\"top\":\"135\",\"freq\":1,\"mean\":160.8099173553719,\"std\":97.6969219960031,\"min\":\"1\",\"p25\":\"71.33333333333333\",\"median\":\"155.0\",\"p75\":\"256.66666666666663\",\"max\":\"328\"},{\"name\":\"homedest\",\"type\":\"String?\",\"count\":1309,\"unique\":370,\"nulls\":564,\"top\":\"New York, NY\",\"freq\":64,\"mean\":null,\"std\":null,\"min\":\"?Havana, Cuba\",\"p25\":\"England\",\"median\":\"Lucca, Italy / California\",\"p75\":\"Provo, UT\",\"max\":\"Zurich, Switzerland\"}]}"
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 4
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:38.988769Z",
"start_time": "2025-05-28T10:16:38.801330Z"
}
},
"source": [
"df"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" pclass survived name sex age sibsp parch ticket fare cabin embarked boat body homedest 1 1 Allen, Miss. Elisabeth Walton null 29.000000 null null 24160 211.337500 B5 null 2 null St Louis, MO 1 1 Allison, Master. Hudson Trevor male 0.916700 1 2 113781 151.550000 C22 C26 AA 11 null Montreal, PQ / Chesterville, ON 1 0 Allison, Miss. Helen Loraine female 2.000000 1 2 113781 151.550000 C22 C26 S null null Montreal, PQ / Chesterville, ON 1 0 Allison, Mr. Hudson Joshua Creighton male 30.000000 1 2 113781 151.550000 C22 C26 S null 135 Montreal, PQ / Chesterville, ON 1 0 Allison, Mrs. Hudson J C (Bessie Wald... female 25.000000 1 2 113781 151.550000 C22 C26 S null null Montreal, PQ / Chesterville, ON 1 1 Anderson, Mr. Harry male 48.000000 0 0 19952 26.550000 E12 S 3 null New York, NY 1 1 Andrews, Miss. Kornelia Theodosia female 63.000000 1 0 13502 77.958300 D7 S 10 null Hudson, NY 1 0 Andrews, Mr. Thomas Jr male 39.000000 0 0 112050 0.000000 A36 S null null Belfast, NI 1 1 Appleton, Mrs. Edward Dale (Charlotte... female 53.000000 2 0 11769 51.479200 C101 S D null Bayside, Queens, NY 1 0 Artagaveytia, Mr. Ramon male 71.000000 0 0 PC 17609 49.504200 null C null 22 Montevideo, Uruguay 1 0 Astor, Col. John Jacob male 47.000000 1 0 PC 17757 227.525000 C62 C64 C null 124 New York, NY 1 1 Astor, Mrs. John Jacob (Madeleine Tal... female 18.000000 1 0 PC 17757 227.525000 C62 C64 C 4 null New York, NY 1 1 Aubart, Mme. Leontine Pauline female 24.000000 0 0 PC 17477 69.300000 B35 C 9 null Paris, France 1 1 Barber, Miss. Ellen "Nellie" female 26.000000 0 0 19877 78.850000 null S 6 null null 1 1 Barkworth, Mr. Algernon Henry Wilson male 80.000000 0 0 27042 30.000000 A23 S B null Hessle, Yorks 1 0 Baumann, Mr. John D male null 0 0 PC 17318 25.925000 null S null null New York, NY 1 0 Baxter, Mr. Quigg Edmond male 24.000000 0 1 PC 17558 247.520800 B58 B60 C null null Montreal, PQ 1 1 Baxter, Mrs. James (Helene DeLaudenie... female 50.000000 0 1 PC 17558 247.520800 B58 B60 C 6 null Montreal, PQ 1 1 Bazzani, Miss. Albina female 32.000000 0 0 11813 76.291700 D15 C 8 null null 1 0 Beattie, Mr. Thomson male 36.000000 0 0 13050 75.241700 C6 C A null Winnipeg, MN
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"pclass\",\"survived\",\"name\",\"sex\",\"age\",\"sibsp\",\"parch\",\"ticket\",\"fare\",\"cabin\",\"embarked\",\"boat\",\"body\",\"homedest\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"}],\"nrow\":1309,\"ncol\":14},\"kotlin_dataframe\":[{\"pclass\":1,\"survived\":1,\"name\":\"Allen, Miss. Elisabeth Walton\",\"sex\":null,\"age\":29.0,\"sibsp\":null,\"parch\":null,\"ticket\":\"24160\",\"fare\":211.3375,\"cabin\":\"B5\",\"embarked\":null,\"boat\":\"2\",\"body\":null,\"homedest\":\"St Louis, MO\"},{\"pclass\":1,\"survived\":1,\"name\":\"Allison, Master. Hudson Trevor\",\"sex\":\"male\",\"age\":0.9167,\"sibsp\":1,\"parch\":2,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"AA\",\"boat\":\"11\",\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Miss. Helen Loraine\",\"sex\":\"female\",\"age\":2.0,\"sibsp\":1,\"parch\":2,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Mr. Hudson Joshua Creighton\",\"sex\":\"male\",\"age\":30.0,\"sibsp\":1,\"parch\":2,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":135,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)\",\"sex\":\"female\",\"age\":25.0,\"sibsp\":1,\"parch\":2,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":1,\"name\":\"Anderson, Mr. Harry\",\"sex\":\"male\",\"age\":48.0,\"sibsp\":0,\"parch\":0,\"ticket\":\"19952\",\"fare\":26.55,\"cabin\":\"E12\",\"embarked\":\"S\",\"boat\":\"3\",\"body\":null,\"homedest\":\"New York, NY\"},{\"pclass\":1,\"survived\":1,\"name\":\"Andrews, Miss. Kornelia Theodosia\",\"sex\":\"female\",\"age\":63.0,\"sibsp\":1,\"parch\":0,\"ticket\":\"13502\",\"fare\":77.9583,\"cabin\":\"D7\",\"embarked\":\"S\",\"boat\":\"10\",\"body\":null,\"homedest\":\"Hudson, NY\"},{\"pclass\":1,\"survived\":0,\"name\":\"Andrews, Mr. Thomas Jr\",\"sex\":\"male\",\"age\":39.0,\"sibsp\":0,\"parch\":0,\"ticket\":\"112050\",\"fare\":0.0,\"cabin\":\"A36\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Belfast, NI\"},{\"pclass\":1,\"survived\":1,\"name\":\"Appleton, Mrs. Edward Dale (Charlotte Lamson)\",\"sex\":\"female\",\"age\":53.0,\"sibsp\":2,\"parch\":0,\"ticket\":\"11769\",\"fare\":51.4792,\"cabin\":\"C101\",\"embarked\":\"S\",\"boat\":\"D\",\"body\":null,\"homedest\":\"Bayside, Queens, NY\"},{\"pclass\":1,\"survived\":0,\"name\":\"Artagaveytia, Mr. Ramon\",\"sex\":\"male\",\"age\":71.0,\"sibsp\":0,\"parch\":0,\"ticket\":\"PC 17609\",\"fare\":49.5042,\"cabin\":null,\"embarked\":\"C\",\"boat\":null,\"body\":22,\"homedest\":\"Montevideo, Uruguay\"},{\"pclass\":1,\"survived\":0,\"name\":\"Astor, Col. John Jacob\",\"sex\":\"male\",\"age\":47.0,\"sibsp\":1,\"parch\":0,\"ticket\":\"PC 17757\",\"fare\":227.525,\"cabin\":\"C62 C64\",\"embarked\":\"C\",\"boat\":null,\"body\":124,\"homedest\":\"New York, NY\"},{\"pclass\":1,\"survived\":1,\"name\":\"Astor, Mrs. John Jacob (Madeleine Talmadge Force)\",\"sex\":\"female\",\"age\":18.0,\"sibsp\":1,\"parch\":0,\"ticket\":\"PC 17757\",\"fare\":227.525,\"cabin\":\"C62 C64\",\"embarked\":\"C\",\"boat\":\"4\",\"body\":null,\"homedest\":\"New York, NY\"},{\"pclass\":1,\"survived\":1,\"name\":\"Aubart, Mme. Leontine Pauline\",\"sex\":\"female\",\"age\":24.0,\"sibsp\":0,\"parch\":0,\"ticket\":\"PC 17477\",\"fare\":69.3,\"cabin\":\"B35\",\"embarked\":\"C\",\"boat\":\"9\",\"body\":null,\"homedest\":\"Paris, France\"},{\"pclass\":1,\"survived\":1,\"name\":\"Barber, Miss. Ellen \\\"Nellie\\\"\",\"sex\":\"female\",\"age\":26.0,\"sibsp\":0,\"parch\":0,\"ticket\":\"19877\",\"fare\":78.85,\"cabin\":null,\"embarked\":\"S\",\"boat\":\"6\",\"body\":null,\"homedest\":null},{\"pclass\":1,\"survived\":1,\"name\":\"Barkworth, Mr. Algernon Henry Wilson\",\"sex\":\"male\",\"age\":80.0,\"sibsp\":0,\"parch\":0,\"ticket\":\"27042\",\"fare\":30.0,\"cabin\":\"A23\",\"embarked\":\"S\",\"boat\":\"B\",\"body\":null,\"homedest\":\"Hessle, Yorks\"},{\"pclass\":1,\"survived\":0,\"name\":\"Baumann, Mr. John D\",\"sex\":\"male\",\"age\":null,\"sibsp\":0,\"parch\":0,\"ticket\":\"PC 17318\",\"fare\":25.925,\"cabin\":null,\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"New York, NY\"},{\"pclass\":1,\"survived\":0,\"name\":\"Baxter, Mr. Quigg Edmond\",\"sex\":\"male\",\"age\":24.0,\"sibsp\":0,\"parch\":1,\"ticket\":\"PC 17558\",\"fare\":247.5208,\"cabin\":\"B58 B60\",\"embarked\":\"C\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ\"},{\"pclass\":1,\"survived\":1,\"name\":\"Baxter, Mrs. James (Helene DeLaudeniere Chaput)\",\"sex\":\"female\",\"age\":50.0,\"sibsp\":0,\"parch\":1,\"ticket\":\"PC 17558\",\"fare\":247.5208,\"cabin\":\"B58 B60\",\"embarked\":\"C\",\"boat\":\"6\",\"body\":null,\"homedest\":\"Montreal, PQ\"},{\"pclass\":1,\"survived\":1,\"name\":\"Bazzani, Miss. Albina\",\"sex\":\"female\",\"age\":32.0,\"sibsp\":0,\"parch\":0,\"ticket\":\"11813\",\"fare\":76.2917,\"cabin\":\"D15\",\"embarked\":\"C\",\"boat\":\"8\",\"body\":null,\"homedest\":null},{\"pclass\":1,\"survived\":0,\"name\":\"Beattie, Mr. Thomson\",\"sex\":\"male\",\"age\":36.0,\"sibsp\":0,\"parch\":0,\"ticket\":\"13050\",\"fare\":75.2417,\"cabin\":\"C6\",\"embarked\":\"C\",\"boat\":\"A\",\"body\":null,\"homedest\":\"Winnipeg, MN\"}]}"
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Imputing null values\n",
"Let's convert all columns of our dataset to non-nullable and impute null values based on mean values."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:41.323938Z",
"start_time": "2025-05-28T10:16:38.994285Z"
}
},
"source": [
"val df1 = df\n",
" // imputing\n",
" .fillNulls { sibsp and parch and age and fare }.perCol { mean() }\n",
" .fillNulls { sex }.with { \"other\" }\n",
" .fillNulls { embarked }.with { \"S\" }\n",
" .convert { sibsp and parch and age and fare }.toDouble()\n",
"\n",
"df1.head()"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" pclass survived name sex age sibsp parch ticket fare cabin embarked boat body homedest 1 1 Allen, Miss. Elisabeth Walton other 29.000000 0.000000 0.000000 24160 211.337500 B5 S 2 null St Louis, MO 1 1 Allison, Master. Hudson Trevor male 0.916700 1.000000 2.000000 113781 151.550000 C22 C26 AA 11 null Montreal, PQ / Chesterville, ON 1 0 Allison, Miss. Helen Loraine female 2.000000 1.000000 2.000000 113781 151.550000 C22 C26 S null null Montreal, PQ / Chesterville, ON 1 0 Allison, Mr. Hudson Joshua Creighton male 30.000000 1.000000 2.000000 113781 151.550000 C22 C26 S null 135 Montreal, PQ / Chesterville, ON 1 0 Allison, Mrs. Hudson J C (Bessie Wald... female 25.000000 1.000000 2.000000 113781 151.550000 C22 C26 S null null Montreal, PQ / Chesterville, ON
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"pclass\",\"survived\",\"name\",\"sex\",\"age\",\"sibsp\",\"parch\",\"ticket\",\"fare\",\"cabin\",\"embarked\",\"boat\",\"body\",\"homedest\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"}],\"nrow\":5,\"ncol\":14},\"kotlin_dataframe\":[{\"pclass\":1,\"survived\":1,\"name\":\"Allen, Miss. Elisabeth Walton\",\"sex\":\"other\",\"age\":29.0,\"sibsp\":0.0,\"parch\":0.0,\"ticket\":\"24160\",\"fare\":211.3375,\"cabin\":\"B5\",\"embarked\":\"S\",\"boat\":\"2\",\"body\":null,\"homedest\":\"St Louis, MO\"},{\"pclass\":1,\"survived\":1,\"name\":\"Allison, Master. Hudson Trevor\",\"sex\":\"male\",\"age\":0.9167,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"AA\",\"boat\":\"11\",\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Miss. Helen Loraine\",\"sex\":\"female\",\"age\":2.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Mr. Hudson Joshua Creighton\",\"sex\":\"male\",\"age\":30.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":135,\"homedest\":\"Montreal, PQ / Chesterville, ON\"},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)\",\"sex\":\"female\",\"age\":25.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\"}]}"
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 6
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:41.441Z",
"start_time": "2025-05-28T10:16:41.332676Z"
}
},
"source": [
"df1.schema()"
],
"outputs": [
{
"data": {
"text/plain": [
"pclass: Int\n",
"survived: Int\n",
"name: String\n",
"sex: String\n",
"age: Double\n",
"sibsp: Double\n",
"parch: Double\n",
"ticket: String\n",
"fare: Double\n",
"cabin: String?\n",
"embarked: String\n",
"boat: String?\n",
"body: Int?\n",
"homedest: String?"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 7
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:41.598448Z",
"start_time": "2025-05-28T10:16:41.446624Z"
}
},
"source": [
"df1.corr()"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" column pclass survived age sibsp parch fare pclass 1.000000 -0.312469 -0.366370 0.060832 0.018322 -0.558477 survived -0.312469 1.000000 -0.050199 -0.027825 0.082660 0.244208 age -0.366370 -0.050199 1.000000 -0.190747 -0.130872 0.171521 sibsp 0.060832 -0.027825 -0.190747 1.000000 0.373587 0.160224 parch 0.018322 0.082660 -0.130872 0.373587 1.000000 0.221522 fare -0.558477 0.244208 0.171521 0.160224 0.221522 1.000000
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"column\",\"pclass\",\"survived\",\"age\",\"sibsp\",\"parch\",\"fare\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":6,\"ncol\":7},\"kotlin_dataframe\":[{\"column\":\"pclass\",\"pclass\":1.0,\"survived\":-0.31246936264968,\"age\":-0.36637035869802936,\"sibsp\":0.06083200757490747,\"parch\":0.018322202009786036,\"fare\":-0.5584773475043957},{\"column\":\"survived\",\"pclass\":-0.31246936264968,\"survived\":1.0,\"age\":-0.050198983636982906,\"sibsp\":-0.02782511923058273,\"parch\":0.0826595703861011,\"fare\":0.24420775279437662},{\"column\":\"age\",\"pclass\":-0.36637035869802936,\"survived\":-0.050198983636982906,\"age\":1.0,\"sibsp\":-0.19074715633383899,\"parch\":-0.1308719630307398,\"fare\":0.17152056539956614},{\"column\":\"sibsp\",\"pclass\":0.06083200757490747,\"survived\":-0.02782511923058273,\"age\":-0.19074715633383899,\"sibsp\":1.0,\"parch\":0.3735871906264913,\"fare\":0.16022419622116035},{\"column\":\"parch\",\"pclass\":0.018322202009786036,\"survived\":0.0826595703861011,\"age\":-0.1308719630307398,\"sibsp\":0.3735871906264913,\"parch\":1.0,\"fare\":0.2215218879995723},{\"column\":\"fare\",\"pclass\":-0.5584773475043957,\"survived\":0.24420775279437662,\"age\":0.17152056539956614,\"sibsp\":0.16022419622116035,\"parch\":0.2215218879995723,\"fare\":1.0}]}"
},
"execution_count": 8,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 8
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:42.151986Z",
"start_time": "2025-05-28T10:16:41.603918Z"
}
},
"source": [
"val correlations = df1\n",
" .corr { all() }.with { survived }\n",
" .sortBy { survived }\n",
"correlations"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" column survived pclass -0.312469 age -0.050199 sibsp -0.027825 parch 0.082660 fare 0.244208 survived 1.000000
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"column\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":6,\"ncol\":2},\"kotlin_dataframe\":[{\"column\":\"pclass\",\"survived\":-0.31246936264968},{\"column\":\"age\",\"survived\":-0.050198983636982906},{\"column\":\"sibsp\",\"survived\":-0.02782511923058273},{\"column\":\"parch\",\"survived\":0.0826595703861011},{\"column\":\"fare\",\"survived\":0.24420775279437662},{\"column\":\"survived\",\"survived\":1.0}]}"
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 9
},
{
"cell_type": "markdown",
"metadata": {},
"source": "Great, at this moment we have five numerical features available for numerical analysis: **pclass, age, sibsp, parch, fare**."
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Analyze by pivoting features\n",
"To confirm some of our observations and assumptions, we can quickly analyze our feature correlations by pivoting features against each other. We can only do so at this stage for features which do not have any empty values. It also makes sense doing so only for features which are categorical (Sex), ordinal (Pclass) or discrete (SibSp, Parch) type.\n",
"\n",
"- **Pclass**: We observe a significant correlation (>0.5) between **Pclass**=1 and **Survived**.\n",
"\n",
"- **Sex**: We confirm the observation during problem definition that Sex=female had a very high survival rate at 74%.\n",
"\n",
"- **SibSp** and **Parch**: These features have zero correlation for the certain values. It may be best to derive a feature or a set of features from these individual features."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:42.420112Z",
"start_time": "2025-05-28T10:16:42.157822Z"
}
},
"source": [
"df1.groupBy { pclass }.mean { survived }.sortBy { pclass }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" pclass survived 1 0.619195 2 0.429603 3 0.255289
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"pclass\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":3,\"ncol\":2},\"kotlin_dataframe\":[{\"pclass\":1,\"survived\":0.6191950464396285},{\"pclass\":2,\"survived\":0.4296028880866426},{\"pclass\":3,\"survived\":0.2552891396332863}]}"
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 10
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:42.626934Z",
"start_time": "2025-05-28T10:16:42.424738Z"
}
},
"source": [
"df1.groupBy { sex }.mean { survived }.sortBy { survived }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" sex survived male 0.190985 female 0.726882 other 1.000000
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"sex\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":3,\"ncol\":2},\"kotlin_dataframe\":[{\"sex\":\"male\",\"survived\":0.19098457888493475},{\"sex\":\"female\",\"survived\":0.7268817204301076},{\"sex\":\"other\",\"survived\":1.0}]}"
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 11
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:42.795186Z",
"start_time": "2025-05-28T10:16:42.630617Z"
}
},
"source": [
"df1.groupBy { sibsp }.mean { survived }.sortBy { sibsp }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" sibsp survived 0.000000 0.346801 1.000000 0.510972 2.000000 0.452381 3.000000 0.300000 4.000000 0.136364 5.000000 0.000000 8.000000 0.000000
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"sibsp\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":7,\"ncol\":2},\"kotlin_dataframe\":[{\"sibsp\":0.0,\"survived\":0.3468013468013468},{\"sibsp\":1.0,\"survived\":0.5109717868338558},{\"sibsp\":2.0,\"survived\":0.4523809523809524},{\"sibsp\":3.0,\"survived\":0.3},{\"sibsp\":4.0,\"survived\":0.13636363636363635},{\"sibsp\":5.0,\"survived\":0.0},{\"sibsp\":8.0,\"survived\":0.0}]}"
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 12
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:42.953015Z",
"start_time": "2025-05-28T10:16:42.798529Z"
}
},
"source": [
"df1.groupBy { parch }.mean { survived }.sortBy { parch }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" parch survived 0.000000 0.335329 1.000000 0.588235 2.000000 0.504425 3.000000 0.625000 4.000000 0.166667 5.000000 0.166667 6.000000 0.000000 9.000000 0.000000
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"parch\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":8,\"ncol\":2},\"kotlin_dataframe\":[{\"parch\":0.0,\"survived\":0.33532934131736525},{\"parch\":1.0,\"survived\":0.5882352941176471},{\"parch\":2.0,\"survived\":0.504424778761062},{\"parch\":3.0,\"survived\":0.625},{\"parch\":4.0,\"survived\":0.16666666666666666},{\"parch\":5.0,\"survived\":0.16666666666666666},{\"parch\":6.0,\"survived\":0.0},{\"parch\":9.0,\"survived\":0.0}]}"
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 13
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Analyze the importance of the Age feature\n",
"\n",
"It's interesting to discover both **age** distributions: among the survived and perished passengers."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:16:43.402600Z",
"start_time": "2025-05-28T10:16:42.955679Z"
}
},
"source": [
"val byAge = df1.valueCounts { age }.sortBy { age }\n",
"byAge"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" age count 0.166700 1 0.333300 1 0.416700 1 0.666700 1 0.750000 3 0.833300 3 0.916700 2 1.000000 10 2.000000 12 3.000000 7 4.000000 10 5.000000 5 6.000000 6 7.000000 4 8.000000 6 9.000000 10 10.000000 4 11.000000 4 11.500000 1 12.000000 3
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"age\",\"count\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}],\"nrow\":99,\"ncol\":2},\"kotlin_dataframe\":[{\"age\":0.1667,\"count\":1},{\"age\":0.3333,\"count\":1},{\"age\":0.4167,\"count\":1},{\"age\":0.6667,\"count\":1},{\"age\":0.75,\"count\":3},{\"age\":0.8333,\"count\":3},{\"age\":0.9167,\"count\":2},{\"age\":1.0,\"count\":10},{\"age\":2.0,\"count\":12},{\"age\":3.0,\"count\":7},{\"age\":4.0,\"count\":10},{\"age\":5.0,\"count\":5},{\"age\":6.0,\"count\":6},{\"age\":7.0,\"count\":4},{\"age\":8.0,\"count\":6},{\"age\":9.0,\"count\":10},{\"age\":10.0,\"count\":4},{\"age\":11.0,\"count\":4},{\"age\":11.5,\"count\":1},{\"age\":12.0,\"count\":3}]}"
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 14
},
{
"cell_type": "code",
"source": [
"// JetBrains color palette\n",
"object JetBrainsColors {\n",
" val lightOrange = Color.hex(\"#ffb59e\")\n",
" val orange = Color.hex(\"#ff6632\")\n",
" val lightGrey = Color.hex(\"#a6a6a6\")\n",
" val darkGrey = Color.hex(\"#4c4c4c\")\n",
"}"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:16:43.529164Z",
"start_time": "2025-05-28T10:16:43.406945Z"
}
},
"outputs": [],
"execution_count": 15
},
{
"cell_type": "code",
"source": [
"byAge.plot { \n",
" points {\n",
" x(age)\n",
" y(count)\n",
" size = 5.0\n",
" color = JetBrainsColors.lightGrey\n",
" }\n",
" layout { \n",
" size = 850 to 500\n",
" }\n",
"}"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T09:39:05.623936Z",
"start_time": "2025-05-28T09:39:02.983218Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 10 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 20 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 30 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 40 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 50 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 60 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 70 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 80 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 50 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 100 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 150 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 200 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 250 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" count \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" "
],
"application/plot+json": {
"output_type": "lets_plot_spec",
"output": {
"mapping": {},
"data": {
"count": [
1.0,
1.0,
1.0,
1.0,
3.0,
3.0,
2.0,
10.0,
12.0,
7.0,
10.0,
5.0,
6.0,
4.0,
6.0,
10.0,
4.0,
4.0,
1.0,
3.0,
5.0,
8.0,
2.0,
6.0,
19.0,
20.0,
39.0,
3.0,
29.0,
23.0,
1.0,
41.0,
43.0,
1.0,
26.0,
1.0,
47.0,
1.0,
34.0,
30.0,
1.0,
30.0,
32.0,
3.0,
30.0,
263.0,
40.0,
2.0,
23.0,
24.0,
4.0,
21.0,
16.0,
2.0,
23.0,
31.0,
2.0,
9.0,
14.0,
1.0,
20.0,
18.0,
3.0,
11.0,
18.0,
9.0,
10.0,
21.0,
2.0,
6.0,
14.0,
14.0,
9.0,
15.0,
8.0,
6.0,
4.0,
10.0,
8.0,
1.0,
4.0,
5.0,
6.0,
3.0,
7.0,
1.0,
5.0,
5.0,
4.0,
5.0,
3.0,
1.0,
1.0,
2.0,
1.0,
2.0,
1.0,
1.0,
1.0
],
"age": [
0.1667,
0.3333,
0.4167,
0.6667,
0.75,
0.8333,
0.9167,
1.0,
2.0,
3.0,
4.0,
5.0,
6.0,
7.0,
8.0,
9.0,
10.0,
11.0,
11.5,
12.0,
13.0,
14.0,
14.5,
15.0,
16.0,
17.0,
18.0,
18.5,
19.0,
20.0,
20.5,
21.0,
22.0,
22.5,
23.0,
23.5,
24.0,
24.5,
25.0,
26.0,
26.5,
27.0,
28.0,
28.5,
29.0,
29.8811345124283,
30.0,
30.5,
31.0,
32.0,
32.5,
33.0,
34.0,
34.5,
35.0,
36.0,
36.5,
37.0,
38.0,
38.5,
39.0,
40.0,
40.5,
41.0,
42.0,
43.0,
44.0,
45.0,
45.5,
46.0,
47.0,
48.0,
49.0,
50.0,
51.0,
52.0,
53.0,
54.0,
55.0,
55.5,
56.0,
57.0,
58.0,
59.0,
60.0,
60.5,
61.0,
62.0,
63.0,
64.0,
65.0,
66.0,
67.0,
70.0,
70.5,
71.0,
74.0,
76.0,
80.0
]
},
"ggsize": {
"width": 850.0,
"height": 500.0
},
"kind": "plot",
"scales": [
{
"aesthetic": "x",
"limits": [
null,
null
]
},
{
"aesthetic": "y",
"limits": [
null,
null
]
}
],
"layers": [
{
"mapping": {
"x": "age",
"y": "count"
},
"stat": "identity",
"size": 5.0,
"color": "#a6a6a6",
"sampling": "none",
"inherit_aes": false,
"position": "identity",
"geom": "point"
}
],
"data_meta": {
"series_annotations": [
{
"type": "float",
"column": "age"
},
{
"type": "int",
"column": "count"
}
]
}
},
"apply_color_scheme": true,
"swing_enabled": true
}
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 17
},
{
"cell_type": "code",
"source": [
"val age = df.select { age }.dropNulls().sortBy { age }"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:17:25.886932Z",
"start_time": "2025-05-28T10:17:25.626228Z"
}
},
"outputs": [],
"execution_count": 16
},
{
"cell_type": "code",
"source": [
"age.plot {\n",
" histogram(x = age, binsOption = BinsOption.byWidth(5.0)) {\n",
" fillColor = JetBrainsColors.orange\n",
" }\n",
" layout { \n",
" size = 850 to 500\n",
" }\n",
"}"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:17:28.073921Z",
"start_time": "2025-05-28T10:17:26.675537Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 10 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 20 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 30 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 40 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 50 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 60 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 70 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 80 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 20 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 40 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 60 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 80 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 100 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 120 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 140 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 160 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 180 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" count \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" "
],
"application/plot+json": {
"output_type": "lets_plot_spec",
"output": {
"mapping": {},
"data": {},
"ggsize": {
"width": 850.0,
"height": 500.0
},
"kind": "plot",
"scales": [
{
"aesthetic": "x",
"name": "age",
"limits": [
null,
null
]
},
{
"aesthetic": "x",
"limits": [
null,
null
]
},
{
"aesthetic": "y",
"limits": [
null,
null
]
}
],
"layers": [
{
"mapping": {
"x": "x",
"y": "count"
},
"stat": "identity",
"data": {
"x": [
2.5,
7.5,
12.5,
17.5,
22.5,
27.5,
32.5,
37.5,
42.5,
47.5,
52.5,
57.5,
62.5,
67.5,
72.5,
77.5
],
"count": [
51.0,
31.0,
27.0,
116.0,
184.0,
160.0,
132.0,
100.0,
69.0,
66.0,
43.0,
27.0,
27.0,
5.0,
6.0,
2.0
]
},
"sampling": "none",
"inherit_aes": false,
"position": "identity",
"geom": "bar",
"fill": "#ff6632",
"data_meta": {
"series_annotations": [
{
"type": "float",
"column": "x"
},
{
"type": "int",
"column": "count"
}
]
}
}
]
},
"apply_color_scheme": true,
"swing_enabled": true
}
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 17
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:18:16.355854Z",
"start_time": "2025-05-28T10:18:16.137889Z"
}
},
"source": [
"df1.groupBy { age }.pivotCounts { survived }.sortBy { age }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" age survived 1 0 0.166700 1 0 0.333300 0 1 0.416700 1 0 0.666700 1 0 0.750000 2 1 0.833300 3 0 0.916700 2 0 1.000000 7 3 2.000000 4 8 3.000000 5 2 4.000000 7 3 5.000000 4 1 6.000000 3 3 7.000000 2 2 8.000000 4 2 9.000000 4 6 10.000000 0 4 11.000000 1 3 11.500000 0 1 12.000000 3 0
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"age\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ColumnGroup\"}],\"nrow\":99,\"ncol\":2},\"kotlin_dataframe\":[{\"age\":0.1667,\"survived\":{\"data\":{\"1\":1,\"0\":0},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":0.3333,\"survived\":{\"data\":{\"1\":0,\"0\":1},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":0.4167,\"survived\":{\"data\":{\"1\":1,\"0\":0},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":0.6667,\"survived\":{\"data\":{\"1\":1,\"0\":0},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":0.75,\"survived\":{\"data\":{\"1\":2,\"0\":1},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":0.8333,\"survived\":{\"data\":{\"1\":3,\"0\":0},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":0.9167,\"survived\":{\"data\":{\"1\":2,\"0\":0},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":1.0,\"survived\":{\"data\":{\"1\":7,\"0\":3},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":2.0,\"survived\":{\"data\":{\"1\":4,\"0\":8},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":3.0,\"survived\":{\"data\":{\"1\":5,\"0\":2},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":4.0,\"survived\":{\"data\":{\"1\":7,\"0\":3},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":5.0,\"survived\":{\"data\":{\"1\":4,\"0\":1},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":6.0,\"survived\":{\"data\":{\"1\":3,\"0\":3},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":7.0,\"survived\":{\"data\":{\"1\":2,\"0\":2},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":8.0,\"survived\":{\"data\":{\"1\":4,\"0\":2},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":9.0,\"survived\":{\"data\":{\"1\":4,\"0\":6},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":10.0,\"survived\":{\"data\":{\"1\":0,\"0\":4},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":11.0,\"survived\":{\"data\":{\"1\":1,\"0\":3},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":11.5,\"survived\":{\"data\":{\"1\":0,\"0\":1},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}},{\"age\":12.0,\"survived\":{\"data\":{\"1\":3,\"0\":0},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"0\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}]}}}]}"
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 18
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:19:32.161797Z",
"start_time": "2025-05-28T10:19:31.804724Z"
}
},
"source": [
"val survivedByAge = df1\n",
" .select { survived and age }\n",
" .sortBy { age }\n",
" .convert { survived }.with { if (it == 1) \"Survived\" else \"Died\" }\n",
"\n",
"survivedByAge"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived age Survived 0.166700 Died 0.333300 Survived 0.416700 Survived 0.666700 Survived 0.750000 Survived 0.750000 Died 0.750000 Survived 0.833300 Survived 0.833300 Survived 0.833300 Survived 0.916700 Survived 0.916700 Survived 1.000000 Survived 1.000000 Survived 1.000000 Survived 1.000000 Died 1.000000 Survived 1.000000 Died 1.000000 Survived 1.000000
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"survived\",\"age\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":1309,\"ncol\":2},\"kotlin_dataframe\":[{\"survived\":\"Survived\",\"age\":0.1667},{\"survived\":\"Died\",\"age\":0.3333},{\"survived\":\"Survived\",\"age\":0.4167},{\"survived\":\"Survived\",\"age\":0.6667},{\"survived\":\"Survived\",\"age\":0.75},{\"survived\":\"Survived\",\"age\":0.75},{\"survived\":\"Died\",\"age\":0.75},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.9167},{\"survived\":\"Survived\",\"age\":0.9167},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Died\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Died\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0}]}"
},
"execution_count": 23,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 23
},
{
"cell_type": "code",
"source": [
"survivedByAge.groupBy { survived }"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:19:37.007186Z",
"start_time": "2025-05-28T10:19:36.902859Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived group Survived DataFrame [500 x 2] survived age Survived 0.166700 Survived 0.416700 Survived 0.666700 Survived 0.750000 Survived 0.750000
... showing only top 5 of 500 rows
Died DataFrame [809 x 2] survived age Died 0.333300 Died 0.750000 Died 1.000000 Died 1.000000 Died 1.000000
... showing only top 5 of 809 rows
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"survived\",\"group\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"FrameColumn\"}],\"nrow\":2,\"ncol\":2},\"kotlin_dataframe\":[{\"survived\":\"Survived\",\"group\":{\"data\":[{\"survived\":\"Survived\",\"age\":0.1667},{\"survived\":\"Survived\",\"age\":0.4167},{\"survived\":\"Survived\",\"age\":0.6667},{\"survived\":\"Survived\",\"age\":0.75},{\"survived\":\"Survived\",\"age\":0.75},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.9167},{\"survived\":\"Survived\",\"age\":0.9167},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":2.0},{\"survived\":\"Survived\",\"age\":2.0},{\"survived\":\"Survived\",\"age\":2.0}],\"metadata\":{\"kind\":\"FrameColumn\",\"columns\":[\"survived\",\"age\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"ncol\":2,\"nrow\":500}}},{\"survived\":\"Died\",\"group\":{\"data\":[{\"survived\":\"Died\",\"age\":0.3333},{\"survived\":\"Died\",\"age\":0.75},{\"survived\":\"Died\",\"age\":1.0},{\"survived\":\"Died\",\"age\":1.0},{\"survived\":\"Died\",\"age\":1.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":3.0},{\"survived\":\"Died\",\"age\":3.0},{\"survived\":\"Died\",\"age\":4.0},{\"survived\":\"Died\",\"age\":4.0},{\"survived\":\"Died\",\"age\":4.0},{\"survived\":\"Died\",\"age\":5.0},{\"survived\":\"Died\",\"age\":6.0}],\"metadata\":{\"kind\":\"FrameColumn\",\"columns\":[\"survived\",\"age\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"ncol\":2,\"nrow\":809}}}]}"
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 24
},
{
"cell_type": "code",
"source": [
"survivedByAge.groupBy { survived }.plot {\n",
" histogram(x = age, binsOption = BinsOption.byWidth(5.0)) {\n",
" fillColor(key.survived) {\n",
" scale = categorical(\n",
" \"Survived\" to JetBrainsColors.orange,\n",
" \"Died\" to JetBrainsColors.darkGrey,\n",
" )\n",
" }\n",
" alpha = 0.7\n",
" position = Position.dodge()\n",
" }\n",
" layout {\n",
" size = 850 to 500\n",
" }\n",
"}"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:19:42.226196Z",
"start_time": "2025-05-28T10:19:41.738286Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 10 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 20 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 30 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 40 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 50 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 60 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 70 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 80 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 50 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 100 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 150 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 200 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 250 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 300 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" count \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Died \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" "
],
"application/plot+json": {
"output_type": "lets_plot_spec",
"output": {
"mapping": {},
"data": {
"&merged_groups": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
],
"survived": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
]
},
"ggsize": {
"width": 850.0,
"height": 500.0
},
"kind": "plot",
"scales": [
{
"aesthetic": "x",
"name": "age",
"limits": [
null,
null
]
},
{
"aesthetic": "x",
"limits": [
null,
null
]
},
{
"aesthetic": "y",
"limits": [
null,
null
]
},
{
"aesthetic": "fill",
"values": [
"#ff6632",
"#4c4c4c"
],
"limits": [
"Survived",
"Died"
]
}
],
"layers": [
{
"mapping": {
"x": "x",
"y": "count",
"fill": "survived",
"group": "&merged_groups"
},
"stat": "identity",
"data": {
"&merged_groups": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
],
"x": [
2.5,
7.5,
12.5,
17.5,
22.5,
27.5,
32.5,
37.5,
42.5,
47.5,
52.5,
57.5,
62.5,
67.5,
72.5,
77.5,
2.5,
7.5,
12.5,
17.5,
22.5,
27.5,
32.5,
37.5,
42.5,
47.5,
52.5,
57.5,
62.5,
67.5,
72.5,
77.5
],
"count": [
33.0,
17.0,
11.0,
45.0,
71.0,
129.0,
54.0,
44.0,
20.0,
32.0,
21.0,
11.0,
10.0,
0.0,
0.0,
2.0,
18.0,
14.0,
16.0,
71.0,
113.0,
294.0,
78.0,
56.0,
49.0,
34.0,
22.0,
16.0,
17.0,
5.0,
6.0,
0.0
],
"survived": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
]
},
"sampling": "none",
"alpha": 0.7,
"inherit_aes": false,
"position": "dodge",
"geom": "bar",
"data_meta": {
"series_annotations": [
{
"type": "str",
"column": "survived"
},
{
"type": "float",
"column": "x"
},
{
"type": "int",
"column": "count"
},
{
"type": "str",
"column": "&merged_groups"
}
]
}
}
],
"data_meta": {
"series_annotations": [
{
"type": "str",
"column": "survived"
},
{
"type": "str",
"column": "&merged_groups"
}
]
}
},
"apply_color_scheme": true,
"swing_enabled": true
}
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 25
},
{
"cell_type": "code",
"source": [
"// Density plot\n",
"survivedByAge.groupBy { survived }.plot {\n",
" densityPlot(x = age) {\n",
" fillColor = Color.GREY\n",
" alpha = 0.3\n",
" borderLine {\n",
" color(key.survived) {\n",
" scale = categorical(\n",
" \"Survived\" to JetBrainsColors.orange,\n",
" \"Died\" to JetBrainsColors.darkGrey,\n",
" )\n",
" }\n",
" }\n",
" }\n",
" layout {\n",
" size = 850 to 250\n",
" }\n",
"}"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:19:45.886242Z",
"start_time": "2025-05-28T10:19:45.132559Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 10 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 20 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 30 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 40 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 50 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 60 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 70 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 80 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0.00 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0.02 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0.04 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0.06 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" density \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Died \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" "
],
"application/plot+json": {
"output_type": "lets_plot_spec",
"output": {
"mapping": {},
"data": {
"&merged_groups": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
],
"survived": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
]
},
"ggsize": {
"width": 850.0,
"height": 250.0
},
"kind": "plot",
"scales": [
{
"aesthetic": "x",
"name": "age",
"limits": [
null,
null
]
},
{
"aesthetic": "x",
"limits": [
null,
null
]
},
{
"aesthetic": "y",
"limits": [
null,
null
]
},
{
"aesthetic": "fill",
"discrete": true
},
{
"aesthetic": "color",
"values": [
"#ff6632",
"#4c4c4c"
],
"limits": [
"Survived",
"Died"
]
}
],
"layers": [
{
"mapping": {
"x": "x",
"y": "density",
"fill": "survived",
"color": "survived",
"group": "&merged_groups"
},
"stat": "identity",
"data": {
"&merged_groups": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
],
"density": [
0.007603449598253003,
0.007839311760184098,
0.008065122210652623,
0.008279887668496458,
0.008482691057487888,
0.008672700036986326,
0.008849174394524628,
0.009011472200546811,
0.009159054650167217,
0.009291489542623441,
0.009408453375387026,
0.009509732056020143,
0.00959522026019833,
0.009664919488273522,
0.009718934894802203,
0.00975747098516982,
0.009780826290433088,
0.009789387145510154,
0.009783620706694524,
0.009764067352064188,
0.009731332612713885,
0.009686078783931913,
0.009629016363644119,
0.009560895460867686,
0.009482497309835443,
0.009394626016171106,
0.009298100650353837,
0.009193747791050746,
0.009082394607066828,
0.008964862552007881,
0.008841961730592957,
0.008714485980202288,
0.008583208695977824,
0.008448879412869075,
0.008312221143653807,
0.008173928458372887,
0.00803466627795961,
0.007895069343282015,
0.007755742310462583,
0.007617260414313915,
0.007480170634106047,
0.007344993289742324,
0.007212223991808518,
0.007082335865910689,
0.006955781970247384,
0.0068329978254636475,
0.006714403977472512,
0.0066004085170665045,
0.006491409484677464,
0.006387797094495143,
0.006289955719169018,
0.0061982655843525174,
0.006113104131210684,
0.006034847014498778,
0.005963868713708321,
0.0059005427448385675,
0.005845241470333389,
0.005798335514401441,
0.005760192800072672,
0.005731177232720742,
0.005711647062219298,
0.005701952962227557,
0.005702435870200304,
0.005713424635511115,
0.00573523352551142,
0.005768159640441861,
0.005812480287911493,
0.0058684503662465365,
0.00593629980353222,
0.006016231095767982,
0.0061084169834313955,
0.006212998301086015,
0.006330082029696965,
0.006459739576228963,
0.006602005300095898,
0.006756875301294032,
0.00692430648071211,
0.0071042158793068015,
0.007296480299626792,
0.007500936210605247,
0.007717379934606831,
0.007945568114377174,
0.008185218456703655,
0.008436010749146404,
0.008697588146001644,
0.008969558719537753,
0.00925149727235514,
0.009542947406270224,
0.009843423842275432,
0.010152414984733618,
0.010469385720924278,
0.010793780444299423,
0.011125026286304981,
0.011462536537402765,
0.011805714233053818,
0.012153955875030927,
0.012506655252684153,
0.01286320732289012,
0.013223012101661042,
0.013585478515005509,
0.013950028151964772,
0.01431609885906845,
0.0146831481130585,
0.015050656107926793,
0.015418128493283027,
0.01578509870406988,
0.01615112982674939,
0.01651581595441163,
0.01687878299274578,
0.0172396888904117,
0.017598223280847588,
0.017954106537705097,
0.018307088262559827,
0.018656945240902837,
0.019003478920187274,
0.01934651248136131,
0.01968588759230367,
0.020021460947294907,
0.02035310071054009,
0.020680682993231843,
0.02100408850216467,
0.02132319950303581,
0.021637897242863288,
0.021948059973113387,
0.022253561707947556,
0.022554271840347993,
0.0228500557227964,
0.023140776298774604,
0.023426296846904747,
0.023706484871415336,
0.023981217141313127,
0.024250385846759603,
0.02451390580539729,
0.024771722614539464,
0.025023821608058664,
0.025270237440442905,
0.02551106408573334,
0.025746465006899276,
0.025976683222609567,
0.026202050974263095,
0.02642299867742139,
0.02664006282931548,
0.026853892538582343,
0.02706525434550085,
0.02727503501127002,
0.02748424197362665,
0.027694001193641897,
0.027905552154801214,
0.028120239820388533,
0.028339503408332713,
0.02856486190347115,
0.028797896294814575,
0.02904022859883757,
0.029293497807736282,
0.029559332982583977,
0.029839323793614644,
0.030134988891621684,
0.030447742573676925,
0.030778860280906848,
0.03112944353370254,
0.031500384968356505,
0.031892334186473394,
0.03230566516269781,
0.03274044597536654,
0.03319641162719926,
0.033672940707726536,
0.03416903661504288,
0.034683314001234075,
0.035213991033585544,
0.03575888797304403,
0.036315432463600465,
0.03688067180304666,
0.03745129232919425,
0.0380236459090281,
0.03859378336457084,
0.03915749451222387,
0.039710354335874755,
0.04024777466233878,
0.0407650605648623,
0.04125747059063954,
0.041720279795479306,
0.04214884447653051,
0.042538667425439304,
0.04288546248207291,
0.04318521715482137,
0.04343425208866562,
0.043629276206899915,
0.04376743642611207,
0.043846360945307715,
0.04386419523667216,
0.04381963001436841,
0.043711920625264175,
0.043540897487239695,
0.04330696739203422,
0.0430111056853426,
0.0426548395319112,
0.042240222662490536,
0.041769802177696214,
0.04124657814644704,
0.04067395687952865,
0.0400556988784116,
0.03939586255291493,
0.03869874486663006,
0.0379688201050199,
0.03721067796752177,
0.03642896216235467,
0.03562831063249602,
0.03481329846560542,
0.033988384442383765,
0.033157862060374244,
0.032325815737391454,
0.03149608275474146,
0.030672221349501847,
0.029857485211670313,
0.0290548044901884,
0.028266773265664596,
0.027495643310650165,
0.02674332383372249,
0.02601138679402167,
0.025301077280279513,
0.024613328374218216,
0.02394877986324923,
0.02330780013184463,
0.022690510544395734,
0.02209681163385595,
0.02152641042859923,
0.020978848282913982,
0.02045352862228668,
0.01994974407080603,
0.019466702492186832,
0.019003551545592953,
0.018559401430201183,
0.018133345565977156,
0.017724479030302158,
0.017331914639016326,
0.01695479662452245,
0.01659231192153555,
0.016243699121904487,
0.015908255203029152,
0.015585340169442198,
0.015274379774089505,
0.014974866504983041,
0.014686359034696133,
0.014408480335294195,
0.014140914660565844,
0.013883403591752018,
0.013635741333339287,
0.01339776943286046,
0.013169371083982216,
0.012950465156333364,
0.012741000079327132,
0.012540947691324996,
0.012350297150414238,
0.012169048989229188,
0.01199720938388984,
0.01183478469639206,
0.011681776340657635,
0.011538176014834095,
0.01140396133613835,
0.011279091909298636,
0.0111635058551781,
0.01105711682213836,
0.010959811498823935,
0.01087144764302936,
0.0107918526369214,
0.010720822573950588,
0.01065812187719441,
0.010603483442599234,
0.010556609293677346,
0.010517171726791097,
0.010484814918404278,
0.010459156957849096,
0.01043979226152643,
0.010426294317342379,
0.010418218701900156,
0.010415106307823087,
0.010416486714859449,
0.010421881636346705,
0.010430808372366455,
0.01044278320260424,
0.010457324655562955,
0.010473956596306913,
0.010492211082188847,
0.010511630944811261,
0.010531772066500692,
0.010552205330468198,
0.010572518235192828,
0.010592316174958859,
0.010611223399465656,
0.01062888367557249,
0.010644960683138211,
0.010659138184211119,
0.01067112001022222,
0.010680629915124668,
0.010687411343473853,
0.010691227161229982,
0.01069185939365083,
0.010689109009193785,
0.01068279578111335,
0.010672758249755148,
0.010658853798807945,
0.010640958848424836,
0.01061896915763887,
0.010592800218358645,
0.010562387713904893,
0.010527688006978227,
0.010488678615512009,
0.010445358630380142,
0.010397749026627066,
0.010345892819905812,
0.01028985502218702,
0.010229722355475122,
0.01016560268907531,
0.01009762417464178,
0.010025934063468595,
0.00995069720185547,
0.009872094212436925,
0.009790319381618633,
0.009705578285220532,
0.009618085195591897,
0.009528060323378008,
0.009435726955365905,
0.009341308556067053,
0.009245025904633853,
0.009147094340168443,
0.009047721187376003,
0.008947103430847689,
0.008845425700135577,
0.008742858619400683,
0.008639557565059552,
0.008535661862878897,
0.008431294442790033,
0.008326561955772865,
0.008221555342980379,
0.008116350833331124,
0.008011011332574775,
0.007905588154786931,
0.0078001230367882365,
0.00769465036745904,
0.007589199557617602,
0.007483797472247546,
0.00737847084551377,
0.007273248600220427,
0.007168163997077009,
0.007063256545198314,
0.006958573613444085,
0.006854171692205845,
0.006750117266716301,
0.006646487275489749,
0.006543369140672008,
0.006440860370439944,
0.006339067746704194,
0.006238106123809524,
0.006138096875304356,
0.006039166035818151,
0.0059414421933535345,
0.005845054193644518,
0.005750128722501491,
0.005656787834180453,
0.005565146493777615,
0.005475310199534209,
0.00538737274688268,
0.005301414190278889,
0.005217499051602557,
0.005135674815469902,
0.00505597074251577,
0.0049783970219136366,
0.004902944274458668,
0.004829583407780188,
0.004758265815992401,
0.004688923907619817,
0.004621471938188196,
0.004555807117644434,
0.004491810957897619,
0.0044293508223363955,
0.004368281637196868,
0.004308447724094003,
0.004249684713800282,
0.004191821503323186,
0.004134682221324598,
0.004078088170736741,
0.004021859721836981,
0.003965818133814373,
0.003909787287760783,
0.0038535953188255432,
0.0037970761397819867,
0.0037400708522892017,
0.003682429045551002,
0.0036240099847711983,
0.003564683693716089,
0.003504331936800863,
0.0034428491064351476,
0.0033801430209530097,
0.003316135637406488,
0.0032507636819395372,
0.003183979198523972,
0.003115750014686943,
0.0030460601206533594,
0.0029749099562279896,
0.0029023165979025394,
0.0028283138372285107,
0.002752952140560903,
0.0026762984799373166,
0.00259843602516778,
0.0025194636881962435,
0.0024394955124459067,
0.0023586599021354652,
0.002277098689381093,
0.002194966040182245,
0.002112427204009193,
0.0020296571155322424,
0.0019468388609122323,
0.0018641620248604504,
0.0017818209382287659,
0.0017000128490692757,
0.0016189360427850126,
0.001538787939074198,
0.0014597631947682415,
0.0013820518423219184,
0.001305837493602159,
0.0012312956377379606,
0.0011585920601617668,
0.0010878814076418007,
0.0010193059211470199,
9.529943548932429E-4,
8.890610959963795E-4,
8.276054949250565E-4,
7.687114125239009E-4,
7.124469848969296E-4,
6.588646030215655E-4,
6.080010997258506E-4,
5.598781327114834E-4,
5.145027487388296E-4,
4.718681109861509E-4,
4.3195436901677196E-4,
3.947296487793495E-4,
3.601511386546962E-4,
3.281662467560602E-4,
2.98713804480758E-4,
2.7172529167567564E-4,
2.4712605968034104E-4,
2.2483652989993962E-4,
2.0477334737877855E-4,
1.868504710265469E-4,
1.7098018462542093E-4,
1.5707401544258194E-4,
1.4504355011674117E-4,
1.3480114040654147E-4,
1.2626049431393289E-4,
1.193371509613402E-4,
1.139488403476733E-4,
1.100157316806959E-4,
1.0746057633440958E-4,
1.0620875356923659E-4,
1.0618822894645773E-4,
1.0732943684036045E-4,
1.09565099583052E-4,
1.1282999655624765E-4,
1.1706069696711815E-4,
1.2219527011404495E-4,
1.2817298667230274E-4,
1.3493402392541934E-4,
1.4241918695775472E-4,
1.5056965663642237E-4,
1.5932677378050188E-4,
1.686318672822708E-4,
1.7842613215341354E-4,
1.886505615671334E-4,
1.9924593500623798E-4,
2.10152862660925E-4,
2.2131188430231467E-4,
2.3266361904220715E-4,
2.4414896072768964E-4,
2.5570931225889275E-4,
2.672868509023079E-4,
2.7882481573686353E-4,
2.902678077437635E-4,
3.015620927529918E-4,
3.126558974985427E-4,
3.234996894089588E-4,
3.34046431456877E-4,
3.442518043870456E-4,
3.540743899022862E-4,
3.634758098669618E-4,
3.7242081823537387E-4,
3.80877344168965E-4,
3.8881648660762914E-4,
3.9621246234072805E-4,
4.030425113165905E-4,
4.092867644718484E-4,
4.1492808069561876E-4,
4.1995186061716093E-4,
4.2434584567773614E-4,
4.280999113876095E-4,
4.312058637597098E-4,
4.3365724764799266E-4,
4.3544917511041296E-4,
4.365781809863268E-4,
4.370421116615511E-4,
4.368400515379037E-4,
4.3597229008399455E-4,
4.3444033058378975E-4,
4.3224693988714414E-4,
4.2939623667226097E-4,
4.258938140231844E-4,
4.21746890571692E-4,
4.16964483111818E-4,
4.1155759251767815E-4,
4.0553939402167917E-4,
3.9892542246898737E-4,
3.917337430706528E-4,
3.8398509843388983E-4,
0.0029062365005629266,
0.0030391527847771164,
0.0031668919744145974,
0.0032884746340393466,
0.003402980967753703,
0.003509567479581156,
0.00360748243833365,
0.003696079747824025,
0.0037748308626115857,
0.0038433344411442833,
0.0039013234904063266,
0.003948669826752153,
0.003985385753899541,
0.004011622938203209,
0.004027668540355853,
0.004033938738596153,
0.004030969848528143,
0.004019407306233326,
0.003999992832341977,
0.0039735501334697615,
0.003940969522815904,
0.0039031918532668017,
0.0038611921541590066,
0.003815963347635062,
0.003768500393518182,
0.003719785174556258,
0.003670772388835858,
0.00362237666550141,
0.0035754610661376043,
0.003530827079806489,
0.003489206167194613,
0.003451252860820749,
0.0034175393856662327,
0.0033885517294028815,
0.003364687064632342,
0.003346252407750602,
0.003333464390241091,
0.0033264500179238906,
0.0033252483010466067,
0.003329812651811846,
0.0033400139644114554,
0.003355644314090144,
0.003376421234296929,
0.0034019925527144085,
0.003431941786108286,
0.003465794108943032,
0.0035030229202918303,
0.0035430570368231726,
0.0035852885360702267,
0.003629081263731115,
0.0036737800017816492,
0.0037187202715137768,
0.0037632387184088237,
0.00380668399549765,
0.003848428030255067,
0.003887877528957713,
0.003924485543674605,
0.003957762902447083,
0.003987289284378467,
0.0040127237096472135,
0.0040338142109118055,
0.004050406457808574,
0.004062451120453526,
0.004070009780782478,
0.004073259231501483,
0.004072494040256928,
0.004068127299899247,
0.004060689532634898,
0.004050825764472147,
0.00403929083457428,
0.004026943049848374,
0.004014736336312682,
0.004003711073687707,
0.003994983826716562,
0.003989736204771144,
0.003989203089598251,
0.003994660469330579,
0.004007413105350239,
0.004028782237954813,
0.0040600935082127886,
0.004102665238506404,
0.004157797174986187,
0.004226759753718865,
0.004310783911062777,
0.004411051420165443,
0.004528685701781123,
0.004664743030977528,
0.004820204043549964,
0.004995965438467559,
0.005192831776294158,
0.005411507288519866,
0.00565258763875261,
0.005916551612718983,
0.006203752758389017,
0.006514411048050365,
0.006848604688098331,
0.007206262256627006,
0.007587155400266581,
0.007990892366750078,
0.008416912685121253,
0.00886448332830355,
0.009332696700422163,
0.009820470781844294,
0.010326551737262553,
0.010849519245952647,
0.01138779474928999,
0.01193965273030292,
0.012503235046099475,
0.013076568229831621,
0.01365758356875676,
0.014244139653687739,
0.014834046987869278,
0.01542509414547479,
0.01601507488656132,
0.016601815571302286,
0.017183202175648282,
0.01775720619637121,
0.018321908747682733,
0.01887552219488873,
0.01941640874202859,
0.019943095487857092,
0.02045428558421989,
0.020948865267816936,
0.021425906684650022,
0.021884666579267683,
0.022324581071164543,
0.022745256881124505,
0.023146459494212644,
0.02352809884737029,
0.023890213203472684,
0.0242329519166566,
0.024556557804152255,
0.024861349817748252,
0.025147706655297357,
0.025416051873049874,
0.025666840958180566,
0.025900550704172617,
0.02611767110688764,
0.02631869987396119,
0.02650413952205874,
0.026674496932546945,
0.026830285152212755,
0.026972027166285557,
0.027100261338970914,
0.02721554821282428,
0.027318478381368062,
0.027409681196257807,
0.027489834136090192,
0.02755967274210361,
0.02762000110907836,
0.027671702999402,
0.027715753716164235,
0.027753232919315956,
0.0277853385901964,
0.027813402338346633,
0.027838906196490112,
0.027863500962780206,
0.0278890260243421,
0.027917530435297665,
0.027951294831008923,
0.027992853545472134,
0.028045016070015572,
0.02811088675985013,
0.02819388147309822,
0.02829773962813331,
0.02842653000332768,
0.02858464849239547,
0.028776805981603863,
0.029008004544075965,
0.029283500261163803,
0.02960875118900266,
0.029989349294234014,
0.030430935587306276,
0.03093909818139534,
0.03151925359195559,
0.0321765122535053,
0.032915529949018904,
0.03374034760067803,
0.03465422263212276,
0.03565945585085423,
0.03675721848157173,
0.03794738457151384,
0.03922837445156463,
0.04059701523758897,
0.04204842446401618,
0.04357592282998585,
0.045170981688398844,
0.04682321030973512,
0.0485203871056733,
0.05024853791376216,
0.05199206314735993,
0.05373391414020464,
0.05545581740933492,
0.05713854388050145,
0.05876221843154273,
0.06030666348151673,
0.061751768858780184,
0.06307787889034476,
0.06426618663313802,
0.06529912447177849,
0.06616073998155102,
0.0668370460285618,
0.06731633456360868,
0.06758944445534797,
0.06764997497645935,
0.06749443815990151,
0.06712234512098002,
0.06653622352094385,
0.06574156554536742,
0.0647467079955462,
0.06356264825227341,
0.06220280188011825,
0.06068270941612554,
0.05901970136025679,
0.05723253150165488,
0.05534098943780767,
0.053365503454625124,
0.05132674483520954,
0.04924524417301452,
0.047141029417340455,
0.0450332942262403,
0.04294010380547989,
0.040878143841487836,
0.03886251646402164,
0.036906585473316864,
0.035021871405844784,
0.03321799545465106,
0.031502669857500505,
0.02988173116042306,
0.02835921178522237,
0.026937444594015772,
0.025617194656669288,
0.02439781218170313,
0.023277400551771788,
0.022252993587311774,
0.02132073651675122,
0.02047606562553765,
0.019713882154311007,
0.019028716684292662,
0.01841488095269475,
0.017866604753174357,
0.01737815627058022,
0.016943944854589072,
0.016558605837212477,
0.016217067533189234,
0.015914601022911933,
0.015646853701615192,
0.015409867886096587,
0.015200086003869108,
0.01501434405383031,
0.014849855128047408,
0.014704184827589359,
0.014575220398297284,
0.01446113536176098,
0.014360351329119976,
0.014271498566842055,
0.014193376740158187,
0.014124917096776001,
0.01406514717593291,
0.014013158940583083,
0.013968081038099907,
0.013929055701679247,
0.013895220614824443,
0.013865695878840026,
0.013839576051862257,
0.013815927070986382,
0.013793787729480016,
0.013772175261361078,
0.013750094487667834,
0.013726549903791716,
0.013700560035859025,
0.013671173366189443,
0.013637485122528043,
0.013598654241597528,
0.013553919852566291,
0.013502616677837125,
0.013444188814360606,
0.013378201435500482,
0.013304350038262087,
0.01322246695043703,
0.013132524904041234,
0.01303463757269962,
0.012929057059019136,
0.012816168401494533,
0.01269648124746736,
0.012570618907825478,
0.012439305069537792,
0.012303348493128306,
0.012163626063420302,
0.012021064593167641,
0.011876621800550548,
0.011731266893091653,
0.011585961192601402,
0.011441639228617354,
0.011299190711852173,
0.011159443774867071,
0.011023149835054742,
0.010890970395635765,
0.010763466054413534,
0.010641087938268803,
0.010524171724681564,
0.010412934350951787,
0.010307473448383632,
0.010207769473758135,
0.010113690445328038,
0.010024999126804818,
0.00994136244193819,
0.009862362845912784,
0.009787511329525787,
0.009716261689527456,
0.009648025665084893,
0.009582188517390339,
0.009518124618090202,
0.009455212613300562,
0.009392849744007337,
0.00933046493075034,
0.009267530270360765,
0.00920357064440085,
0.009138171201610198,
0.00907098254839167,
0.009001723560018106,
0.008930181808260402,
0.0088562116856501,
0.008779730389483572,
0.008700712006728522,
0.008619180010992537,
0.008535198541615862,
0.008448862880018001,
0.00836028956738376,
0.00826960661893485,
0.008176944282419914,
0.008082426761884467,
0.007986165282911255,
0.007888252813861853,
0.0077887606815312364,
0.007687737232115873,
0.007585208593178032,
0.007481181493508234,
0.007375647999854614,
0.007268591936874755,
0.007159996673681329,
0.007049853890929799,
0.006938172889888415,
0.0068249899719331104,
0.0067103774051261444,
0.00659445150468061,
0.006477379385864049,
0.006359383999910559,
0.006240747133490142,
0.006121810137075118,
0.006002972243302279,
0.0058846864388126495,
0.00576745295742428,
0.005651810564168807,
0.005538325894177869,
0.005427581193505134,
0.005320160877161831,
0.005216637370111527,
0.005117556727765045,
0.0050234245426232635,
0.004934692633083581,
0.0048517469799441906,
0.004774897327569532,
0.004704368802542384,
0.004640295826057482,
0.004582718510890494,
0.004531581643338946,
0.004486736258979805,
0.004447943732194564,
0.004414882216652507,
0.004387155200340734,
0.0043643018767402925,
0.0043458089851699895,
0.004331123739253178,
0.0043196674432995465,
0.0043108493918514275,
0.004304080656830844,
0.004298787388233567,
0.0042944232863452135,
0.004290480943927685,
0.004286501803530635,
0.004282084525804231,
0.00427689161731635,
0.004270654219008668,
0.004263175007440956,
0.004254329209080716,
0.004244063772151502,
0.004232394780352682,
0.004219403227807103,
0.0042052293048345105,
0.004190065369729482,
0.004174147802898086,
0.004157747956772827,
0.00414116242815159,
0.0041247028891824924,
0.004108685719216841,
0.004093421682116506,
0.004079205892140956,
0.00406630830595972,
0.004054964968284217,
0.004045370223729302,
0.004037670087502205,
0.004031956942204228,
0.004028265697440948,
0.004026571513336278,
0.004026789148984114,
0.004028773953198141,
0.004032324468781024,
0.004037186574340405,
0.004043059041058546,
0.004049600337545702,
0.004056436475800626,
0.004063169657148543,
0.004069387450463806,
0.004074672217402092,
0.004078610491817323,
0.004080802023660963,
0.004080868211627134,
0.004078459673290559,
0.004073262735661694,
0.004065004671658156,
0.0040534575572500125,
0.0040384406779249635,
0.004019821469343683,
0.003997515033192719,
0.00397148232286349,
0.003941727142375376,
0.003908292143835089,
0.0038712540419326576,
0.0038307182871837988,
0.0037868134519879913,
0.0037396855847437946,
0.0036894927774355716,
0.0036364001719690732,
0.0035805756012360686,
0.0035221860239690963,
0.003461394869748128,
0.0033983603640883025,
0.003333234855516408,
0.0032661651190706415,
0.003197293565761136,
0.003126760247035466,
0.0030547055087571297,
0.0029812731218458186,
0.002906613697398229,
0.002830888183274136,
0.0027542712368832712,
0.0026769542749757354,
0.0025991480150388897,
0.0025210843435880107,
0.00244301737315062,
0.002365223580887971,
0.0022880009562921896,
0.002211667121940966,
0.002136556428610232,
0.002063016062931652,
0.001991401241132745,
0.0019220695952266284,
0.0018553748874746612,
0.0017916602143080698,
0.0017312508815759083,
0.0016744471485203832,
0.0016215170479134688,
0.0015726894940765632,
0.0015281478889021167,
0.0014880244284612648,
0.0014523952993761695,
0.0014212769350372162,
0.001394623477255661,
0.0013723255595024164,
0.0013542104940861572,
0.0013400439082196115,
0.0013295328338263758,
0.001322330214221005,
0.0013180407486626453,
0.001316227954558602,
0.0013164222881732203,
0.0013181301294966647,
0.001320843406828311,
0.001324049612910829,
0.0013272419482260349,
0.0013299293192119092,
0.0013316459202701852,
0.0013319601387549512,
0.0013304825415418329,
0.0013268727297643856,
0.0013208448839767003,
0.0013121718641098256,
0.0013006877755752607,
0.001286288962927455,
0.0012689334436606226,
0.001248638844942996,
0.0012254789533693408,
0.001199579030250958,
0.0011711100808900967,
0.0011402822943328208,
0.0011073378892591237,
0.0010725436113643504,
0.0010361831276660125,
9.985495539285613E-4,
9.599383335493172E-4,
9.206406608771076E-4,
8.809376104373448E-4,
8.410950975393149E-4,
8.01359757009893E-4,
7.619557871475812E-4,
7.230827671886728E-4,
6.849144202590918E-4,
6.475982613757575E-4,
6.112560427156963E-4,
5.759848869307265E-4,
5.418589842531225E-4
],
"x": [
0.1667,
0.3229295499021526,
0.47915909980430527,
0.6353886497064578,
0.7916181996086105,
0.9478477495107631,
1.1040772994129158,
1.2603068493150684,
1.416536399217221,
1.5727659491193737,
1.7289954990215264,
1.885225048923679,
2.0414545988258315,
2.1976841487279843,
2.3539136986301368,
2.5101432485322897,
2.666372798434442,
2.8226023483365945,
2.9788318982387474,
3.1350614481409,
3.2912909980430527,
3.447520547945205,
3.603750097847358,
3.7599796477495104,
3.916209197651663,
4.072438747553815,
4.228668297455968,
4.38489784735812,
4.541127397260273,
4.697356947162426,
4.853586497064579,
5.009816046966731,
5.166045596868884,
5.3222751467710365,
5.4785046966731885,
5.634734246575341,
5.790963796477494,
5.947193346379647,
6.103422896281799,
6.259652446183952,
6.415881996086105,
6.572111545988257,
6.72834109589041,
6.884570645792563,
7.0408001956947155,
7.1970297455968675,
7.35325929549902,
7.509488845401173,
7.665718395303325,
7.821947945205478,
7.978177495107631,
8.134407045009784,
8.290636594911938,
8.44686614481409,
8.603095694716242,
8.759325244618395,
8.915554794520547,
9.0717843444227,
9.228013894324853,
9.384243444227005,
9.540472994129159,
9.69670254403131,
9.852932093933463,
10.009161643835617,
10.165391193737769,
10.32162074363992,
10.477850293542074,
10.634079843444226,
10.790309393346378,
10.946538943248532,
11.102768493150684,
11.258998043052838,
11.41522759295499,
11.571457142857142,
11.727686692759296,
11.883916242661448,
12.0401457925636,
12.196375342465753,
12.352604892367905,
12.508834442270057,
12.665063992172211,
12.821293542074363,
12.977523091976515,
13.133752641878669,
13.28998219178082,
13.446211741682975,
13.602441291585126,
13.758670841487278,
13.914900391389432,
14.071129941291584,
14.227359491193736,
14.38358904109589,
14.539818590998042,
14.696048140900194,
14.852277690802348,
15.0085072407045,
15.164736790606652,
15.320966340508805,
15.477195890410957,
15.633425440313111,
15.789654990215263,
15.945884540117415,
16.10211409001957,
16.25834363992172,
16.414573189823873,
16.570802739726023,
16.727032289628177,
16.88326183953033,
17.03949138943248,
17.195720939334635,
17.35195048923679,
17.50818003913894,
17.664409589041092,
17.820639138943246,
17.976868688845396,
18.13309823874755,
18.289327788649704,
18.445557338551858,
18.601786888454008,
18.75801643835616,
18.914245988258315,
19.070475538160466,
19.22670508806262,
19.382934637964773,
19.539164187866923,
19.695393737769077,
19.85162328767123,
20.00785283757338,
20.164082387475535,
20.32031193737769,
20.47654148727984,
20.632771037181993,
20.789000587084146,
20.945230136986297,
21.10145968688845,
21.257689236790604,
21.413918786692754,
21.570148336594908,
21.726377886497062,
21.882607436399212,
22.038836986301366,
22.19506653620352,
22.351296086105673,
22.507525636007824,
22.663755185909977,
22.81998473581213,
22.97621428571428,
23.132443835616435,
23.28867338551859,
23.44490293542074,
23.601132485322893,
23.757362035225047,
23.913591585127197,
24.06982113502935,
24.226050684931504,
24.382280234833654,
24.53850978473581,
24.694739334637962,
24.850968884540112,
25.007198434442266,
25.16342798434442,
25.31965753424657,
25.475887084148724,
25.632116634050877,
25.788346183953028,
25.94457573385518,
26.100805283757335,
26.25703483365949,
26.41326438356164,
26.569493933463793,
26.725723483365947,
26.881953033268097,
27.03818258317025,
27.194412133072404,
27.350641682974555,
27.50687123287671,
27.663100782778862,
27.819330332681012,
27.975559882583166,
28.13178943248532,
28.28801898238747,
28.444248532289624,
28.600478082191778,
28.756707632093928,
28.91293718199608,
29.069166731898235,
29.225396281800386,
29.38162583170254,
29.537855381604693,
29.694084931506843,
29.850314481408997,
30.00654403131115,
30.1627735812133,
30.319003131115455,
30.47523268101761,
30.631462230919762,
30.787691780821913,
30.943921330724066,
31.10015088062622,
31.25638043052837,
31.412609980430524,
31.568839530332678,
31.725069080234828,
31.881298630136982,
32.03752818003914,
32.19375772994129,
32.34998727984344,
32.50621682974559,
32.66244637964775,
32.8186759295499,
32.97490547945205,
33.131135029354205,
33.287364579256355,
33.443594129158505,
33.59982367906066,
33.75605322896281,
33.91228277886496,
34.06851232876712,
34.22474187866927,
34.38097142857142,
34.53720097847358,
34.69343052837573,
34.84966007827788,
35.005889628180036,
35.162119178082186,
35.318348727984336,
35.47457827788649,
35.630807827788644,
35.787037377690794,
35.94326692759295,
36.0994964774951,
36.25572602739726,
36.41195557729941,
36.56818512720156,
36.72441467710372,
36.88064422700587,
37.03687377690802,
37.193103326810174,
37.349332876712324,
37.505562426614475,
37.66179197651663,
37.81802152641878,
37.97425107632093,
38.13048062622309,
38.28671017612524,
38.44293972602739,
38.59916927592955,
38.7553988258317,
38.91162837573385,
39.067857925636005,
39.224087475538155,
39.380317025440306,
39.53654657534246,
39.69277612524461,
39.84900567514676,
40.00523522504892,
40.16146477495107,
40.31769432485322,
40.47392387475538,
40.63015342465753,
40.78638297455968,
40.942612524461836,
41.098842074363986,
41.25507162426614,
41.411301174168294,
41.567530724070444,
41.723760273972594,
41.87998982387475,
42.0362193737769,
42.19244892367905,
42.34867847358121,
42.50490802348336,
42.66113757338551,
42.81736712328767,
42.97359667318982,
43.12982622309197,
43.286055772994125,
43.442285322896275,
43.598514872798425,
43.75474442270058,
43.91097397260273,
44.06720352250488,
44.22343307240704,
44.37966262230919,
44.53589217221135,
44.6921217221135,
44.84835127201565,
45.004580821917806,
45.160810371819956,
45.317039921722106,
45.47326947162426,
45.629499021526414,
45.785728571428564,
45.94195812133072,
46.09818767123287,
46.25441722113502,
46.41064677103718,
46.56687632093933,
46.72310587084148,
46.87933542074364,
47.03556497064579,
47.19179452054794,
47.348024070450094,
47.504253620352245,
47.660483170254395,
47.81671272015655,
47.9729422700587,
48.12917181996085,
48.28540136986301,
48.44163091976516,
48.59786046966731,
48.75409001956947,
48.91031956947162,
49.06654911937377,
49.222778669275925,
49.379008219178075,
49.535237769080226,
49.69146731898238,
49.84769686888453,
50.00392641878668,
50.16015596868884,
50.31638551859099,
50.47261506849314,
50.6288446183953,
50.78507416829745,
50.9413037181996,
51.097533268101756,
51.253762818003906,
51.40999236790606,
51.566221917808214,
51.722451467710364,
51.878681017612514,
52.03491056751467,
52.19114011741682,
52.34736966731898,
52.50359921722113,
52.65982876712328,
52.81605831702544,
52.97228786692759,
53.12851741682974,
53.284746966731895,
53.440976516634045,
53.597206066536195,
53.75343561643835,
53.9096651663405,
54.06589471624265,
54.22212426614481,
54.37835381604696,
54.53458336594911,
54.69081291585127,
54.84704246575342,
55.00327201565557,
55.159501565557726,
55.315731115459876,
55.471960665362026,
55.62819021526418,
55.784419765166334,
55.940649315068484,
56.09687886497064,
56.25310841487279,
56.40933796477494,
56.5655675146771,
56.72179706457925,
56.8780266144814,
57.03425616438356,
57.19048571428571,
57.34671526418786,
57.502944814090014,
57.659174363992165,
57.815403913894315,
57.97163346379647,
58.12786301369862,
58.28409256360077,
58.44032211350293,
58.59655166340508,
58.75278121330723,
58.90901076320939,
59.06524031311154,
59.22146986301369,
59.377699412915845,
59.533928962817996,
59.690158512720146,
59.8463880626223,
60.00261761252445,
60.1588471624266,
60.31507671232876,
60.47130626223091,
60.62753581213307,
60.78376536203522,
60.93999491193737,
61.096224461839526,
61.252454011741676,
61.40868356164383,
61.564913111545984,
61.721142661448134,
61.877372211350284,
62.03360176125244,
62.18983131115459,
62.34606086105674,
62.5022904109589,
62.65851996086105,
62.8147495107632,
62.97097906066536,
63.12720861056751,
63.28343816046966,
63.439667710371815,
63.595897260273965,
63.752126810176115,
63.90835636007827,
64.06458590998042,
64.22081545988259,
64.37704500978474,
64.53327455968689,
64.68950410958904,
64.84573365949119,
65.00196320939335,
65.1581927592955,
65.31442230919765,
65.4706518590998,
65.62688140900195,
65.7831109589041,
65.93934050880627,
66.09557005870842,
66.25179960861057,
66.40802915851272,
66.56425870841487,
66.72048825831702,
66.87671780821918,
67.03294735812133,
67.18917690802348,
67.34540645792563,
67.50163600782778,
67.65786555772993,
67.8140951076321,
67.97032465753425,
68.1265542074364,
68.28278375733855,
68.4390133072407,
68.59524285714285,
68.75147240704501,
68.90770195694716,
69.06393150684931,
69.22016105675146,
69.37639060665362,
69.53262015655577,
69.68884970645793,
69.84507925636008,
70.00130880626223,
70.15753835616438,
70.31376790606653,
70.46999745596868,
70.62622700587085,
70.782456555773,
70.93868610567515,
71.0949156555773,
71.25114520547945,
71.4073747553816,
71.56360430528376,
71.71983385518591,
71.87606340508806,
72.03229295499021,
72.18852250489236,
72.34475205479453,
72.50098160469668,
72.65721115459883,
72.81344070450098,
72.96967025440313,
73.12589980430528,
73.28212935420744,
73.43835890410959,
73.59458845401174,
73.75081800391389,
73.90704755381604,
74.06327710371819,
74.21950665362036,
74.37573620352251,
74.53196575342466,
74.68819530332681,
74.84442485322896,
75.00065440313111,
75.15688395303327,
75.31311350293542,
75.46934305283757,
75.62557260273972,
75.78180215264187,
75.93803170254402,
76.09426125244619,
76.25049080234834,
76.40672035225049,
76.56294990215264,
76.71917945205479,
76.87540900195694,
77.0316385518591,
77.18786810176125,
77.3440976516634,
77.50032720156555,
77.6565567514677,
77.81278630136985,
77.96901585127202,
78.12524540117417,
78.28147495107632,
78.43770450097847,
78.59393405088062,
78.75016360078277,
78.90639315068493,
79.06262270058708,
79.21885225048923,
79.37508180039138,
79.53131135029354,
79.68754090019569,
79.84377045009785,
80.0,
0.3333,
0.47746183953033267,
0.6216236790606653,
0.7657855185909981,
0.9099473581213307,
1.0541091976516634,
1.198271037181996,
1.3424328767123286,
1.4865947162426614,
1.6307565557729942,
1.7749183953033267,
1.9190802348336593,
2.063242074363992,
2.207403913894325,
2.3515657534246572,
2.49572759295499,
2.639889432485323,
2.7840512720156556,
2.9282131115459884,
3.0723749510763207,
3.2165367906066535,
3.3606986301369863,
3.5048604696673187,
3.6490223091976515,
3.7931841487279843,
3.937345988258317,
4.08150782778865,
4.225669667318982,
4.369831506849315,
4.513993346379648,
4.658155185909981,
4.802317025440313,
4.946478864970646,
5.090640704500979,
5.234802544031312,
5.3789643835616445,
5.523126223091977,
5.667288062622309,
5.811449902152642,
5.955611741682975,
6.099773581213308,
6.24393542074364,
6.388097260273973,
6.532259099804306,
6.676420939334638,
6.820582778864971,
6.9647446183953035,
7.108906457925636,
7.253068297455969,
7.397230136986302,
7.541391976516635,
7.685553816046967,
7.8297156555773,
7.973877495107632,
8.118039334637965,
8.262201174168297,
8.406363013698629,
8.550524853228962,
8.694686692759294,
8.838848532289628,
8.98301037181996,
9.127172211350294,
9.271334050880625,
9.41549589041096,
9.559657729941291,
9.703819569471623,
9.847981409001957,
9.992143248532289,
10.136305088062622,
10.280466927592954,
10.424628767123288,
10.56879060665362,
10.712952446183953,
10.857114285714285,
11.001276125244617,
11.14543796477495,
11.289599804305283,
11.433761643835616,
11.577923483365948,
11.722085322896282,
11.866247162426614,
12.010409001956946,
12.15457084148728,
12.298732681017611,
12.442894520547945,
12.587056360078277,
12.73121819960861,
12.875380039138943,
13.019541878669274,
13.163703718199608,
13.30786555772994,
13.452027397260274,
13.596189236790606,
13.74035107632094,
13.884512915851271,
14.028674755381605,
14.172836594911937,
14.316998434442269,
14.461160273972602,
14.605322113502934,
14.749483953033268,
14.8936457925636,
15.037807632093934,
15.181969471624265,
15.3261313111546,
15.470293150684931,
15.614454990215263,
15.758616829745597,
15.902778669275929,
16.046940508806262,
16.191102348336596,
16.33526418786693,
16.47942602739726,
16.623587866927593,
16.767749706457927,
16.91191154598826,
17.05607338551859,
17.200235225048925,
17.34439706457926,
17.488558904109592,
17.632720743639922,
17.776882583170256,
17.92104442270059,
18.06520626223092,
18.209368101761253,
18.353529941291587,
18.49769178082192,
18.64185362035225,
18.786015459882584,
18.930177299412918,
19.074339138943248,
19.218500978473582,
19.362662818003916,
19.50682465753425,
19.65098649706458,
19.795148336594913,
19.939310176125247,
20.083472015655577,
20.22763385518591,
20.371795694716244,
20.515957534246578,
20.660119373776908,
20.80428121330724,
20.948443052837575,
21.09260489236791,
21.23676673189824,
21.380928571428573,
21.525090410958907,
21.669252250489237,
21.81341409001957,
21.957575929549904,
22.101737769080238,
22.245899608610568,
22.3900614481409,
22.534223287671235,
22.678385127201565,
22.8225469667319,
22.966708806262233,
23.110870645792566,
23.255032485322896,
23.39919432485323,
23.543356164383564,
23.687518003913894,
23.831679843444228,
23.97584168297456,
24.120003522504895,
24.264165362035225,
24.40832720156556,
24.552489041095892,
24.696650880626223,
24.840812720156556,
24.98497455968689,
25.129136399217224,
25.273298238747554,
25.417460078277887,
25.56162191780822,
25.70578375733855,
25.849945596868885,
25.99410743639922,
26.138269275929552,
26.282431115459882,
26.426592954990216,
26.57075479452055,
26.714916634050883,
26.859078473581214,
27.003240313111547,
27.14740215264188,
27.29156399217221,
27.435725831702545,
27.57988767123288,
27.724049510763212,
27.868211350293542,
28.012373189823876,
28.15653502935421,
28.30069686888454,
28.444858708414873,
28.589020547945207,
28.73318238747554,
28.87734422700587,
29.021506066536205,
29.16566790606654,
29.30982974559687,
29.453991585127202,
29.598153424657536,
29.74231526418787,
29.8864771037182,
30.030638943248533,
30.174800782778867,
30.3189626223092,
30.46312446183953,
30.607286301369864,
30.751448140900198,
30.895609980430528,
31.039771819960862,
31.183933659491196,
31.32809549902153,
31.47225733855186,
31.616419178082193,
31.760581017612527,
31.904742857142857,
32.04890469667319,
32.193066536203524,
32.33722837573386,
32.48139021526419,
32.62555205479452,
32.76971389432485,
32.913875733855186,
33.05803757338552,
33.20219941291585,
33.34636125244619,
33.49052309197652,
33.634684931506854,
33.77884677103718,
33.923008610567514,
34.06717045009785,
34.21133228962818,
34.355494129158515,
34.49965596868885,
34.64381780821918,
34.78797964774951,
34.93214148727984,
35.07630332681018,
35.22046516634051,
35.364627005870844,
35.50878884540118,
35.65295068493151,
35.79711252446184,
35.94127436399217,
36.085436203522505,
36.22959804305284,
36.37375988258317,
36.517921722113506,
36.66208356164384,
36.806245401174166,
36.9504072407045,
37.094569080234834,
37.23873091976517,
37.3828927592955,
37.527054598825835,
37.67121643835617,
37.815378277886495,
37.95954011741683,
38.10370195694716,
38.247863796477496,
38.39202563600783,
38.53618747553816,
38.6803493150685,
38.824511154598824,
38.96867299412916,
39.11283483365949,
39.256996673189825,
39.40115851272016,
39.54532035225049,
39.689482191780826,
39.83364403131115,
39.977805870841486,
40.12196771037182,
40.26612954990215,
40.41029138943249,
40.55445322896282,
40.698615068493154,
40.84277690802348,
40.986938747553815,
41.13110058708415,
41.27526242661448,
41.419424266144816,
41.56358610567515,
41.70774794520548,
41.85190978473582,
41.99607162426614,
42.14023346379648,
42.28439530332681,
42.428557142857144,
42.57271898238748,
42.71688082191781,
42.861042661448145,
43.00520450097847,
43.149366340508806,
43.29352818003914,
43.43769001956947,
43.58185185909981,
43.72601369863014,
43.870175538160474,
44.0143373776908,
44.158499217221134,
44.30266105675147,
44.4468228962818,
44.590984735812135,
44.73514657534247,
44.8793084148728,
45.02347025440313,
45.16763209393346,
45.3117939334638,
45.45595577299413,
45.600117612524464,
45.7442794520548,
45.88844129158513,
46.03260313111546,
46.17676497064579,
46.320926810176125,
46.46508864970646,
46.60925048923679,
46.753412328767126,
46.89757416829746,
47.04173600782779,
47.18589784735812,
47.330059686888454,
47.47422152641879,
47.61838336594912,
47.762545205479455,
47.90670704500979,
48.050868884540115,
48.19503072407045,
48.33919256360078,
48.483354403131116,
48.62751624266145,
48.771678082191784,
48.91583992172212,
49.060001761252444,
49.20416360078278,
49.34832544031311,
49.492487279843445,
49.63664911937378,
49.78081095890411,
49.924972798434446,
50.06913463796477,
50.213296477495106,
50.35745831702544,
50.501620156555774,
50.64578199608611,
50.78994383561644,
50.934105675146775,
51.0782675146771,
51.222429354207435,
51.36659119373777,
51.5107530332681,
51.654914872798436,
51.79907671232877,
51.9432385518591,
52.08740039138944,
52.231562230919764,
52.3757240704501,
52.51988590998043,
52.664047749510765,
52.8082095890411,
52.95237142857143,
53.096533268101766,
53.24069510763209,
53.384856947162426,
53.52901878669276,
53.67318062622309,
53.81734246575343,
53.96150430528376,
54.105666144814094,
54.24982798434442,
54.393989823874755,
54.53815166340509,
54.68231350293542,
54.826475342465756,
54.97063718199609,
55.11479902152642,
55.25896086105675,
55.40312270058708,
55.54728454011742,
55.69144637964775,
55.835608219178084,
55.97977005870842,
56.12393189823875,
56.26809373776908,
56.41225557729941,
56.556417416829746,
56.70057925636008,
56.84474109589041,
56.98890293542075,
57.13306477495108,
57.27722661448141,
57.42138845401174,
57.565550293542074,
57.70971213307241,
57.85387397260274,
57.998035812133075,
58.14219765166341,
58.286359491193735,
58.43052133072407,
58.5746831702544,
58.71884500978474,
58.86300684931507,
59.007168688845404,
59.15133052837574,
59.295492367906064,
59.4396542074364,
59.58381604696673,
59.727977886497065,
59.8721397260274,
60.01630156555773,
60.160463405088066,
60.3046252446184,
60.44878708414873,
60.59294892367906,
60.737110763209394,
60.88127260273973,
61.02543444227006,
61.169596281800395,
61.31375812133073,
61.457919960861055,
61.60208180039139,
61.74624363992172,
61.890405479452056,
62.03456731898239,
62.17872915851272,
62.32289099804306,
62.467052837573384,
62.61121467710372,
62.75537651663405,
62.899538356164385,
63.04370019569472,
63.18786203522505,
63.332023874755386,
63.47618571428571,
63.620347553816046,
63.76450939334638,
63.90867123287671,
64.05283307240704,
64.19699491193738,
64.34115675146771,
64.48531859099803,
64.62948043052837,
64.7736422700587,
64.91780410958903,
65.06196594911937,
65.2061277886497,
65.35028962818004,
65.49445146771036,
65.6386133072407,
65.78277514677103,
65.92693698630137,
66.0710988258317,
66.21526066536202,
66.35942250489236,
66.50358434442269,
66.64774618395303,
66.79190802348336,
66.9360698630137,
67.08023170254403,
67.22439354207435,
67.3685553816047,
67.51271722113502,
67.65687906066536,
67.80104090019569,
67.94520273972603,
68.08936457925635,
68.23352641878668,
68.37768825831702,
68.52185009784735,
68.66601193737769,
68.81017377690802,
68.95433561643836,
69.09849745596868,
69.24265929549901,
69.38682113502935,
69.53098297455968,
69.67514481409002,
69.81930665362034,
69.96346849315069,
70.10763033268101,
70.25179217221134,
70.39595401174168,
70.540115851272,
70.68427769080235,
70.82843953033267,
70.97260136986301,
71.11676320939334,
71.26092504892367,
71.40508688845401,
71.54924872798433,
71.69341056751468,
71.837572407045,
71.98173424657534,
72.12589608610567,
72.270057925636,
72.41421976516634,
72.55838160469666,
72.702543444227,
72.84670528375733,
72.99086712328767,
73.135028962818,
73.27919080234832,
73.42335264187867,
73.56751448140899,
73.71167632093933,
73.85583816046966,
74.0
],
"survived": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
]
},
"sampling": "none",
"alpha": 0.3,
"inherit_aes": false,
"position": "identity",
"geom": "area",
"fill": "#a39999",
"data_meta": {
"series_annotations": [
{
"type": "str",
"column": "survived"
},
{
"type": "float",
"column": "x"
},
{
"type": "float",
"column": "density"
},
{
"type": "str",
"column": "&merged_groups"
}
]
}
}
],
"data_meta": {
"series_annotations": [
{
"type": "str",
"column": "survived"
},
{
"type": "str",
"column": "&merged_groups"
}
]
}
},
"apply_color_scheme": true,
"swing_enabled": true
}
},
"execution_count": 26,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 26
},
{
"cell_type": "code",
"source": [
"survivedByAge.groupBy { survived }"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:19:47.339628Z",
"start_time": "2025-05-28T10:19:47.242863Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived group Survived DataFrame [500 x 2] survived age Survived 0.166700 Survived 0.416700 Survived 0.666700 Survived 0.750000 Survived 0.750000
... showing only top 5 of 500 rows
Died DataFrame [809 x 2] survived age Died 0.333300 Died 0.750000 Died 1.000000 Died 1.000000 Died 1.000000
... showing only top 5 of 809 rows
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"survived\",\"group\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"FrameColumn\"}],\"nrow\":2,\"ncol\":2},\"kotlin_dataframe\":[{\"survived\":\"Survived\",\"group\":{\"data\":[{\"survived\":\"Survived\",\"age\":0.1667},{\"survived\":\"Survived\",\"age\":0.4167},{\"survived\":\"Survived\",\"age\":0.6667},{\"survived\":\"Survived\",\"age\":0.75},{\"survived\":\"Survived\",\"age\":0.75},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.8333},{\"survived\":\"Survived\",\"age\":0.9167},{\"survived\":\"Survived\",\"age\":0.9167},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":1.0},{\"survived\":\"Survived\",\"age\":2.0},{\"survived\":\"Survived\",\"age\":2.0},{\"survived\":\"Survived\",\"age\":2.0}],\"metadata\":{\"kind\":\"FrameColumn\",\"columns\":[\"survived\",\"age\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"ncol\":2,\"nrow\":500}}},{\"survived\":\"Died\",\"group\":{\"data\":[{\"survived\":\"Died\",\"age\":0.3333},{\"survived\":\"Died\",\"age\":0.75},{\"survived\":\"Died\",\"age\":1.0},{\"survived\":\"Died\",\"age\":1.0},{\"survived\":\"Died\",\"age\":1.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":2.0},{\"survived\":\"Died\",\"age\":3.0},{\"survived\":\"Died\",\"age\":3.0},{\"survived\":\"Died\",\"age\":4.0},{\"survived\":\"Died\",\"age\":4.0},{\"survived\":\"Died\",\"age\":4.0},{\"survived\":\"Died\",\"age\":5.0},{\"survived\":\"Died\",\"age\":6.0}],\"metadata\":{\"kind\":\"FrameColumn\",\"columns\":[\"survived\",\"age\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"ncol\":2,\"nrow\":809}}}]}"
},
"execution_count": 27,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 27
},
{
"cell_type": "code",
"source": [
"// A basic box plot\n",
"survivedByAge.plot {\n",
" boxplot(x = survived, y = age) {\n",
" boxes {\n",
" fillColor(Stat.x) {\n",
" scale = categorical(\n",
" \"Survived\" to JetBrainsColors.orange,\n",
" \"Died\" to JetBrainsColors.darkGrey,\n",
" )\n",
" }\n",
" }\n",
" }\n",
" layout {\n",
" size = 500 to 400\n",
" }\n",
"}"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:19:54.039953Z",
"start_time": "2025-05-28T10:19:53.550400Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Died \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 10 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 20 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 30 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 40 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 50 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 60 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 70 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 80 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" x \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" Died \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" "
],
"application/plot+json": {
"output_type": "lets_plot_spec",
"output": {
"mapping": {},
"data": {},
"ggsize": {
"width": 500.0,
"height": 400.0
},
"kind": "plot",
"scales": [
{
"aesthetic": "x",
"name": "survived",
"limits": [
null,
null
]
},
{
"aesthetic": "y",
"name": "age",
"limits": [
null,
null
]
},
{
"aesthetic": "x",
"discrete": true
},
{
"aesthetic": "fill",
"values": [
"#ff6632",
"#4c4c4c"
],
"limits": [
"Survived",
"Died"
]
},
{
"aesthetic": "x",
"discrete": true
},
{
"aesthetic": "y",
"limits": [
null,
null
]
}
],
"layers": [
{
"mapping": {
"x": "x",
"ymin": "min",
"lower": "lower",
"middle": "middle",
"upper": "upper",
"ymax": "max",
"fill": "x"
},
"stat": "identity",
"data": {
"min": [
0.1667,
5.0
],
"middle": [
29.8811345124283,
29.8811345124283
],
"max": [
58.0,
52.0
],
"lower": [
21.25,
23.0
],
"upper": [
36.0,
35.0
],
"x": [
"Survived",
"Died"
]
},
"sampling": "none",
"inherit_aes": false,
"position": "identity",
"geom": "boxplot",
"data_meta": {
"series_annotations": [
{
"type": "str",
"column": "x"
},
{
"type": "float",
"column": "min"
},
{
"type": "float",
"column": "lower"
},
{
"type": "float",
"column": "middle"
},
{
"type": "float",
"column": "upper"
},
{
"type": "float",
"column": "max"
}
]
}
},
{
"mapping": {
"x": "x",
"y": "y"
},
"stat": "identity",
"data": {
"x": [
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Survived",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died",
"Died"
],
"y": [
59.0,
60.0,
60.0,
60.0,
60.0,
62.0,
62.0,
63.0,
63.0,
64.0,
64.0,
76.0,
80.0,
0.3333,
0.75,
1.0,
1.0,
1.0,
2.0,
2.0,
2.0,
2.0,
2.0,
2.0,
2.0,
2.0,
3.0,
3.0,
4.0,
4.0,
4.0,
54.0,
54.0,
54.0,
54.0,
54.0,
55.0,
55.0,
55.0,
55.0,
55.5,
56.0,
56.0,
57.0,
57.0,
57.0,
57.0,
57.0,
58.0,
58.0,
59.0,
59.0,
60.0,
60.0,
60.0,
60.5,
61.0,
61.0,
61.0,
61.0,
61.0,
62.0,
62.0,
62.0,
63.0,
63.0,
64.0,
64.0,
64.0,
65.0,
65.0,
65.0,
66.0,
67.0,
70.0,
70.0,
70.5,
71.0,
71.0,
74.0
]
},
"sampling": "none",
"inherit_aes": false,
"position": "identity",
"geom": "point",
"data_meta": {
"series_annotations": [
{
"type": "str",
"column": "x"
},
{
"type": "float",
"column": "y"
}
]
}
}
]
},
"apply_color_scheme": true,
"swing_enabled": true
}
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 28
},
{
"cell_type": "markdown",
"metadata": {},
"source": "Seems like we have the same age distribution among survived and perished passengers."
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Categorical features with One Hot Encoding\n",
"\n",
"To prepare data for ML algorithms, we should replace all String values in categorical features with numbers.\n",
"There are a few ways of preprocessing categorical features, One Hot Encoding being one of them.\n",
"We will use the [`pivotMatches`](https://kotlin.github.io/dataframe/pivot.html#pivotmatches) operation to convert categorical columns into sets of nested `Boolean` columns per every unique value."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:21:52.257217Z",
"start_time": "2025-05-28T10:21:51.724220Z"
}
},
"source": [
"val pivoted = df1.pivotMatches { pclass and sex and embarked }\n",
"pivoted.head()"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived name age sibsp parch ticket fare cabin boat body homedest pclass sex embarked 1 2 3 other male female S AA C Q 1 Allen, Miss. Elisabeth Walton 29.000000 0.000000 0.000000 24160 211.337500 B5 2 null St Louis, MO true false false true false false true false false false 1 Allison, Master. Hudson Trevor 0.916700 1.000000 2.000000 113781 151.550000 C22 C26 11 null Montreal, PQ / Chesterville, ON true false false false true false false true false false 0 Allison, Miss. Helen Loraine 2.000000 1.000000 2.000000 113781 151.550000 C22 C26 null null Montreal, PQ / Chesterville, ON true false false false false true true false false false 0 Allison, Mr. Hudson Joshua Creighton 30.000000 1.000000 2.000000 113781 151.550000 C22 C26 null 135 Montreal, PQ / Chesterville, ON true false false false true false true false false false 0 Allison, Mrs. Hudson J C (Bessie Wald... 25.000000 1.000000 2.000000 113781 151.550000 C22 C26 null null Montreal, PQ / Chesterville, ON true false false false false true true false false false
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"survived\",\"name\",\"age\",\"sibsp\",\"parch\",\"ticket\",\"fare\",\"cabin\",\"boat\",\"body\",\"homedest\",\"pclass\",\"sex\",\"embarked\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ColumnGroup\"},{\"kind\":\"ColumnGroup\"},{\"kind\":\"ColumnGroup\"}],\"nrow\":5,\"ncol\":14},\"kotlin_dataframe\":[{\"survived\":1,\"name\":\"Allen, Miss. Elisabeth Walton\",\"age\":29.0,\"sibsp\":0.0,\"parch\":0.0,\"ticket\":\"24160\",\"fare\":211.3375,\"cabin\":\"B5\",\"boat\":\"2\",\"body\":null,\"homedest\":\"St Louis, MO\",\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sex\":{\"data\":{\"other\":true,\"male\":false,\"female\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":true,\"AA\":false,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}},{\"survived\":1,\"name\":\"Allison, Master. Hudson Trevor\",\"age\":0.9167,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"boat\":\"11\",\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\",\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sex\":{\"data\":{\"other\":false,\"male\":true,\"female\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":false,\"AA\":true,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}},{\"survived\":0,\"name\":\"Allison, Miss. Helen Loraine\",\"age\":2.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\",\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sex\":{\"data\":{\"other\":false,\"male\":false,\"female\":true},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":true,\"AA\":false,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}},{\"survived\":0,\"name\":\"Allison, Mr. Hudson Joshua Creighton\",\"age\":30.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"boat\":null,\"body\":135,\"homedest\":\"Montreal, PQ / Chesterville, ON\",\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sex\":{\"data\":{\"other\":false,\"male\":true,\"female\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":true,\"AA\":false,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}},{\"survived\":0,\"name\":\"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)\",\"age\":25.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\",\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sex\":{\"data\":{\"other\":false,\"male\":false,\"female\":true},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":true,\"AA\":false,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}}]}"
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 30
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:21:53.836768Z",
"start_time": "2025-05-28T10:21:53.287280Z"
}
},
"source": [
"val df2 = pivoted\n",
" // feature extraction\n",
" .select { cols(survived, pclass, sibsp, parch, age, fare, sex, embarked) }\n",
" .convert { valueCols() }.toDouble()\n",
"\n",
"df2.head()"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived pclass sibsp parch age fare sex embarked 1 2 3 other male female S AA C Q 1.000000 true false false 0.000000 0.000000 29.000000 211.337500 true false false true false false false 1.000000 true false false 1.000000 2.000000 0.916700 151.550000 false true false false true false false 0.000000 true false false 1.000000 2.000000 2.000000 151.550000 false false true true false false false 0.000000 true false false 1.000000 2.000000 30.000000 151.550000 false true false true false false false 0.000000 true false false 1.000000 2.000000 25.000000 151.550000 false false true true false false false
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"survived\",\"pclass\",\"sibsp\",\"parch\",\"age\",\"fare\",\"sex\",\"embarked\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ColumnGroup\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ColumnGroup\"},{\"kind\":\"ColumnGroup\"}],\"nrow\":5,\"ncol\":8},\"kotlin_dataframe\":[{\"survived\":1.0,\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sibsp\":0.0,\"parch\":0.0,\"age\":29.0,\"fare\":211.3375,\"sex\":{\"data\":{\"other\":true,\"male\":false,\"female\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":true,\"AA\":false,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}},{\"survived\":1.0,\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sibsp\":1.0,\"parch\":2.0,\"age\":0.9167,\"fare\":151.55,\"sex\":{\"data\":{\"other\":false,\"male\":true,\"female\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":false,\"AA\":true,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}},{\"survived\":0.0,\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sibsp\":1.0,\"parch\":2.0,\"age\":2.0,\"fare\":151.55,\"sex\":{\"data\":{\"other\":false,\"male\":false,\"female\":true},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":true,\"AA\":false,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}},{\"survived\":0.0,\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sibsp\":1.0,\"parch\":2.0,\"age\":30.0,\"fare\":151.55,\"sex\":{\"data\":{\"other\":false,\"male\":true,\"female\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":true,\"AA\":false,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}},{\"survived\":0.0,\"pclass\":{\"data\":{\"1\":true,\"2\":false,\"3\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"1\",\"2\",\"3\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"sibsp\":1.0,\"parch\":2.0,\"age\":25.0,\"fare\":151.55,\"sex\":{\"data\":{\"other\":false,\"male\":false,\"female\":true},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"other\",\"male\",\"female\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}},\"embarked\":{\"data\":{\"S\":true,\"AA\":false,\"C\":false,\"Q\":false},\"metadata\":{\"kind\":\"ColumnGroup\",\"columns\":[\"S\",\"AA\",\"C\",\"Q\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Boolean\"}]}}}]}"
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 31
},
{
"cell_type": "code",
"source": [
"df2.corr { survived and sibsp and parch and age and fare }.withItself()"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:22:12.540994Z",
"start_time": "2025-05-28T10:22:12.381666Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" column survived sibsp parch age fare survived 1.000000 -0.027825 0.082660 -0.050199 0.244208 sibsp -0.027825 1.000000 0.373587 -0.190747 0.160224 parch 0.082660 0.373587 1.000000 -0.130872 0.221522 age -0.050199 -0.190747 -0.130872 1.000000 0.171521 fare 0.244208 0.160224 0.221522 0.171521 1.000000
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"column\",\"survived\",\"sibsp\",\"parch\",\"age\",\"fare\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":5,\"ncol\":6},\"kotlin_dataframe\":[{\"column\":\"survived\",\"survived\":1.0,\"sibsp\":-0.02782511923058273,\"parch\":0.0826595703861011,\"age\":-0.050198983636982906,\"fare\":0.24420775279437662},{\"column\":\"sibsp\",\"survived\":-0.02782511923058273,\"sibsp\":1.0,\"parch\":0.3735871906264913,\"age\":-0.19074715633383899,\"fare\":0.16022419622116035},{\"column\":\"parch\",\"survived\":0.0826595703861011,\"sibsp\":0.3735871906264913,\"parch\":1.0,\"age\":-0.1308719630307398,\"fare\":0.2215218879995723},{\"column\":\"age\",\"survived\":-0.050198983636982906,\"sibsp\":-0.19074715633383899,\"parch\":-0.1308719630307398,\"age\":1.0,\"fare\":0.17152056539956614},{\"column\":\"fare\",\"survived\":0.24420775279437662,\"sibsp\":0.16022419622116035,\"parch\":0.2215218879995723,\"age\":0.17152056539956614,\"fare\":1.0}]}"
},
"execution_count": 32,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 32
},
{
"cell_type": "code",
"source": [
"val correlationTable = df2\n",
" .corr { survived and sibsp and parch and age and fare }.withItself()\n",
" .gather { allAfter(\"column\") }.into(\"row\", \"value\")\n",
"correlationTable"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:22:18.785973Z",
"start_time": "2025-05-28T10:22:18.261051Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" column row value survived survived 1.000000 survived sibsp -0.027825 survived parch 0.082660 survived age -0.050199 survived fare 0.244208 sibsp survived -0.027825 sibsp sibsp 1.000000 sibsp parch 0.373587 sibsp age -0.190747 sibsp fare 0.160224 parch survived 0.082660 parch sibsp 0.373587 parch parch 1.000000 parch age -0.130872 parch fare 0.221522 age survived -0.050199 age sibsp -0.190747 age parch -0.130872 age age 1.000000 age fare 0.171521
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"column\",\"row\",\"value\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":25,\"ncol\":3},\"kotlin_dataframe\":[{\"column\":\"survived\",\"row\":\"survived\",\"value\":1.0},{\"column\":\"survived\",\"row\":\"sibsp\",\"value\":-0.02782511923058273},{\"column\":\"survived\",\"row\":\"parch\",\"value\":0.0826595703861011},{\"column\":\"survived\",\"row\":\"age\",\"value\":-0.050198983636982906},{\"column\":\"survived\",\"row\":\"fare\",\"value\":0.24420775279437662},{\"column\":\"sibsp\",\"row\":\"survived\",\"value\":-0.02782511923058273},{\"column\":\"sibsp\",\"row\":\"sibsp\",\"value\":1.0},{\"column\":\"sibsp\",\"row\":\"parch\",\"value\":0.3735871906264913},{\"column\":\"sibsp\",\"row\":\"age\",\"value\":-0.19074715633383899},{\"column\":\"sibsp\",\"row\":\"fare\",\"value\":0.16022419622116035},{\"column\":\"parch\",\"row\":\"survived\",\"value\":0.0826595703861011},{\"column\":\"parch\",\"row\":\"sibsp\",\"value\":0.3735871906264913},{\"column\":\"parch\",\"row\":\"parch\",\"value\":1.0},{\"column\":\"parch\",\"row\":\"age\",\"value\":-0.1308719630307398},{\"column\":\"parch\",\"row\":\"fare\",\"value\":0.2215218879995723},{\"column\":\"age\",\"row\":\"survived\",\"value\":-0.050198983636982906},{\"column\":\"age\",\"row\":\"sibsp\",\"value\":-0.19074715633383899},{\"column\":\"age\",\"row\":\"parch\",\"value\":-0.1308719630307398},{\"column\":\"age\",\"row\":\"age\",\"value\":1.0},{\"column\":\"age\",\"row\":\"fare\",\"value\":0.17152056539956614}]}"
},
"execution_count": 33,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 33
},
{
"cell_type": "code",
"source": [
"fun scaleContinuousColorGradientN() =\n",
" continuousColorGradientN(\n",
" gradientColors = listOf(\n",
" JetBrainsColors.orange,\n",
" JetBrainsColors.lightGrey,\n",
" JetBrainsColors.darkGrey,\n",
" ),\n",
" domainMin = -1.0,\n",
" domainMax = 1.0,\n",
" )"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:27:47.130780Z",
"start_time": "2025-05-28T10:27:47.068329Z"
}
},
"outputs": [],
"execution_count": 35
},
{
"cell_type": "code",
"source": [
"correlationTable.plot {\n",
" tiles {\n",
" x(row) { axis.name = \"\" }\n",
" y(column) { axis.name = \"\" }\n",
" fillColor(value) { scale = scaleContinuousColorGradientN() }\n",
" }\n",
"}"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:27:48.267717Z",
"start_time": "2025-05-28T10:27:47.970392Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" sibsp \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" parch \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" fare \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" sibsp \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" parch \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" fare \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" value \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" -1.0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" -0.5 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0.0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0.5 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 1.0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" "
],
"application/plot+json": {
"output_type": "lets_plot_spec",
"output": {
"mapping": {},
"data": {
"column": [
"survived",
"survived",
"survived",
"survived",
"survived",
"sibsp",
"sibsp",
"sibsp",
"sibsp",
"sibsp",
"parch",
"parch",
"parch",
"parch",
"parch",
"age",
"age",
"age",
"age",
"age",
"fare",
"fare",
"fare",
"fare",
"fare"
],
"row": [
"survived",
"sibsp",
"parch",
"age",
"fare",
"survived",
"sibsp",
"parch",
"age",
"fare",
"survived",
"sibsp",
"parch",
"age",
"fare",
"survived",
"sibsp",
"parch",
"age",
"fare",
"survived",
"sibsp",
"parch",
"age",
"fare"
],
"value": [
1.0,
-0.02782511923058273,
0.0826595703861011,
-0.050198983636982906,
0.24420775279437662,
-0.02782511923058273,
1.0,
0.3735871906264913,
-0.19074715633383899,
0.16022419622116035,
0.0826595703861011,
0.3735871906264913,
1.0,
-0.1308719630307398,
0.2215218879995723,
-0.050198983636982906,
-0.19074715633383899,
-0.1308719630307398,
1.0,
0.17152056539956614,
0.24420775279437662,
0.16022419622116035,
0.2215218879995723,
0.17152056539956614,
1.0
]
},
"kind": "plot",
"scales": [
{
"aesthetic": "x",
"discrete": true,
"name": ""
},
{
"aesthetic": "y",
"discrete": true,
"name": ""
},
{
"aesthetic": "fill",
"scale_mapper_kind": "color_gradientn",
"limits": [
-1.0,
1.0
],
"colors": [
"#ff6632",
"#a6a6a6",
"#4c4c4c"
]
}
],
"layers": [
{
"mapping": {
"x": "row",
"y": "column",
"fill": "value"
},
"stat": "identity",
"sampling": "none",
"inherit_aes": false,
"position": "identity",
"geom": "tile"
}
],
"data_meta": {
"series_annotations": [
{
"type": "str",
"column": "row"
},
{
"type": "str",
"column": "column"
},
{
"type": "float",
"column": "value"
}
]
}
},
"apply_color_scheme": true,
"swing_enabled": true
}
},
"execution_count": 36,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 36
},
{
"cell_type": "code",
"source": [
"correlationTable.plot {\n",
" points {\n",
" size(value) {\n",
" legend {\n",
" breaks(emptyList())\n",
" }\n",
" }\n",
" symbol = Symbol.SQUARE\n",
" x(row) {\n",
" axis.name = \"\"\n",
" }\n",
" y(column) {\n",
" axis.name = \"\"\n",
" }\n",
" color(value) { scale = scaleContinuousColorGradientN() }\n",
" }\n",
" layout {\n",
" style {\n",
" panel.grid {\n",
" majorLine {\n",
" blank = true\n",
" }\n",
" }\n",
" }\n",
" size = 500 to 350\n",
" }\n",
"}"
],
"metadata": {
"collapsed": false,
"ExecuteTime": {
"end_time": "2025-05-28T10:28:36.815484Z",
"start_time": "2025-05-28T10:28:36.534198Z"
}
},
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" sibsp \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" parch \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" fare \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" sibsp \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" parch \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" age \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" fare \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" value \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" -1.0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" -0.5 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0.0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 0.5 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" 1.0 \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" "
],
"application/plot+json": {
"output_type": "lets_plot_spec",
"output": {
"mapping": {},
"data": {
"column": [
"survived",
"survived",
"survived",
"survived",
"survived",
"sibsp",
"sibsp",
"sibsp",
"sibsp",
"sibsp",
"parch",
"parch",
"parch",
"parch",
"parch",
"age",
"age",
"age",
"age",
"age",
"fare",
"fare",
"fare",
"fare",
"fare"
],
"row": [
"survived",
"sibsp",
"parch",
"age",
"fare",
"survived",
"sibsp",
"parch",
"age",
"fare",
"survived",
"sibsp",
"parch",
"age",
"fare",
"survived",
"sibsp",
"parch",
"age",
"fare",
"survived",
"sibsp",
"parch",
"age",
"fare"
],
"value": [
1.0,
-0.02782511923058273,
0.0826595703861011,
-0.050198983636982906,
0.24420775279437662,
-0.02782511923058273,
1.0,
0.3735871906264913,
-0.19074715633383899,
0.16022419622116035,
0.0826595703861011,
0.3735871906264913,
1.0,
-0.1308719630307398,
0.2215218879995723,
-0.050198983636982906,
-0.19074715633383899,
-0.1308719630307398,
1.0,
0.17152056539956614,
0.24420775279437662,
0.16022419622116035,
0.2215218879995723,
0.17152056539956614,
1.0
]
},
"ggsize": {
"width": 500.0,
"height": 350.0
},
"kind": "plot",
"scales": [
{
"aesthetic": "size",
"breaks": [],
"limits": [
null,
null
]
},
{
"aesthetic": "x",
"discrete": true,
"name": ""
},
{
"aesthetic": "y",
"discrete": true,
"name": ""
},
{
"aesthetic": "color",
"scale_mapper_kind": "color_gradientn",
"limits": [
-1.0,
1.0
],
"colors": [
"#ff6632",
"#a6a6a6",
"#4c4c4c"
]
}
],
"layers": [
{
"mapping": {
"size": "value",
"x": "row",
"y": "column",
"color": "value"
},
"stat": "identity",
"shape": 15.0,
"sampling": "none",
"inherit_aes": false,
"position": "identity",
"geom": "point"
}
],
"theme": {
"axis_ontop": false,
"axis_ontop_y": false,
"axis_ontop_x": false,
"panel_grid_major": {
"blank": true
}
},
"data_meta": {
"series_annotations": [
{
"type": "float",
"column": "value"
},
{
"type": "str",
"column": "row"
},
{
"type": "str",
"column": "column"
}
]
}
},
"apply_color_scheme": true,
"swing_enabled": true
}
},
"execution_count": 37,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 37
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Creation of new features\n",
"\n",
"We suggest combining both the **Sibsp** and **parch** features into a single new feature named **FamilyNumber** by simply summing them up."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:29:35.998766Z",
"start_time": "2025-05-28T10:29:35.802141Z"
}
},
"source": [
"val familyDF = df1\n",
" .add(\"familyNumber\") { sibsp + parch }\n",
"\n",
"familyDF.head()"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" pclass survived name sex age sibsp parch ticket fare cabin embarked boat body homedest familyNumber 1 1 Allen, Miss. Elisabeth Walton other 29.000000 0.000000 0.000000 24160 211.337500 B5 S 2 null St Louis, MO 0.000000 1 1 Allison, Master. Hudson Trevor male 0.916700 1.000000 2.000000 113781 151.550000 C22 C26 AA 11 null Montreal, PQ / Chesterville, ON 3.000000 1 0 Allison, Miss. Helen Loraine female 2.000000 1.000000 2.000000 113781 151.550000 C22 C26 S null null Montreal, PQ / Chesterville, ON 3.000000 1 0 Allison, Mr. Hudson Joshua Creighton male 30.000000 1.000000 2.000000 113781 151.550000 C22 C26 S null 135 Montreal, PQ / Chesterville, ON 3.000000 1 0 Allison, Mrs. Hudson J C (Bessie Wald... female 25.000000 1.000000 2.000000 113781 151.550000 C22 C26 S null null Montreal, PQ / Chesterville, ON 3.000000
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"pclass\",\"survived\",\"name\",\"sex\",\"age\",\"sibsp\",\"parch\",\"ticket\",\"fare\",\"cabin\",\"embarked\",\"boat\",\"body\",\"homedest\",\"familyNumber\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int?\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":5,\"ncol\":15},\"kotlin_dataframe\":[{\"pclass\":1,\"survived\":1,\"name\":\"Allen, Miss. Elisabeth Walton\",\"sex\":\"other\",\"age\":29.0,\"sibsp\":0.0,\"parch\":0.0,\"ticket\":\"24160\",\"fare\":211.3375,\"cabin\":\"B5\",\"embarked\":\"S\",\"boat\":\"2\",\"body\":null,\"homedest\":\"St Louis, MO\",\"familyNumber\":0.0},{\"pclass\":1,\"survived\":1,\"name\":\"Allison, Master. Hudson Trevor\",\"sex\":\"male\",\"age\":0.9167,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"AA\",\"boat\":\"11\",\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\",\"familyNumber\":3.0},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Miss. Helen Loraine\",\"sex\":\"female\",\"age\":2.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\",\"familyNumber\":3.0},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Mr. Hudson Joshua Creighton\",\"sex\":\"male\",\"age\":30.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":135,\"homedest\":\"Montreal, PQ / Chesterville, ON\",\"familyNumber\":3.0},{\"pclass\":1,\"survived\":0,\"name\":\"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)\",\"sex\":\"female\",\"age\":25.0,\"sibsp\":1.0,\"parch\":2.0,\"ticket\":\"113781\",\"fare\":151.55,\"cabin\":\"C22 C26\",\"embarked\":\"S\",\"boat\":null,\"body\":null,\"homedest\":\"Montreal, PQ / Chesterville, ON\",\"familyNumber\":3.0}]}"
},
"execution_count": 38,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 38
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:30:07.106789Z",
"start_time": "2025-05-28T10:30:07.043468Z"
}
},
"source": [
"familyDF.corr { familyNumber }.with { survived }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" column survived familyNumber 0.026876
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"column\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":1,\"ncol\":2},\"kotlin_dataframe\":[{\"column\":\"familyNumber\",\"survived\":0.02687643412533192}]}"
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 40
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:30:09.716646Z",
"start_time": "2025-05-28T10:30:09.606851Z"
}
},
"source": [
"familyDF.corr { familyNumber }.with { age }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" column age familyNumber -0.196996
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"column\",\"age\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":1,\"ncol\":2},\"kotlin_dataframe\":[{\"column\":\"familyNumber\",\"age\":-0.19699624168458799}]}"
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 41
},
{
"cell_type": "markdown",
"metadata": {},
"source": "It looks like the new feature has no influence on the **survived** column, but it has a strong negative correlation with **age**."
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Titles\n",
"Let's try to extract something from the names. A lot of strings in the name column contain special titles, like Done, Mr, Mrs and so on."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:30:39.277144Z",
"start_time": "2025-05-28T10:30:38.969832Z"
}
},
"source": [
"val titledDF = df\n",
" .select { survived and name }\n",
" .add(\"title\") {\n",
" name.split(\".\")[0].split(\",\")[1].trim()\n",
" }\n",
"titledDF.head(100)"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived name title 1 Allen, Miss. Elisabeth Walton Miss 1 Allison, Master. Hudson Trevor Master 0 Allison, Miss. Helen Loraine Miss 0 Allison, Mr. Hudson Joshua Creighton Mr 0 Allison, Mrs. Hudson J C (Bessie Wald... Mrs 1 Anderson, Mr. Harry Mr 1 Andrews, Miss. Kornelia Theodosia Miss 0 Andrews, Mr. Thomas Jr Mr 1 Appleton, Mrs. Edward Dale (Charlotte... Mrs 0 Artagaveytia, Mr. Ramon Mr 0 Astor, Col. John Jacob Col 1 Astor, Mrs. John Jacob (Madeleine Tal... Mrs 1 Aubart, Mme. Leontine Pauline Mme 1 Barber, Miss. Ellen "Nellie" Miss 1 Barkworth, Mr. Algernon Henry Wilson Mr 0 Baumann, Mr. John D Mr 0 Baxter, Mr. Quigg Edmond Mr 1 Baxter, Mrs. James (Helene DeLaudenie... Mrs 1 Bazzani, Miss. Albina Miss 0 Beattie, Mr. Thomson Mr
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"survived\",\"name\",\"title\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"}],\"nrow\":100,\"ncol\":3},\"kotlin_dataframe\":[{\"survived\":1,\"name\":\"Allen, Miss. Elisabeth Walton\",\"title\":\"Miss\"},{\"survived\":1,\"name\":\"Allison, Master. Hudson Trevor\",\"title\":\"Master\"},{\"survived\":0,\"name\":\"Allison, Miss. Helen Loraine\",\"title\":\"Miss\"},{\"survived\":0,\"name\":\"Allison, Mr. Hudson Joshua Creighton\",\"title\":\"Mr\"},{\"survived\":0,\"name\":\"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)\",\"title\":\"Mrs\"},{\"survived\":1,\"name\":\"Anderson, Mr. Harry\",\"title\":\"Mr\"},{\"survived\":1,\"name\":\"Andrews, Miss. Kornelia Theodosia\",\"title\":\"Miss\"},{\"survived\":0,\"name\":\"Andrews, Mr. Thomas Jr\",\"title\":\"Mr\"},{\"survived\":1,\"name\":\"Appleton, Mrs. Edward Dale (Charlotte Lamson)\",\"title\":\"Mrs\"},{\"survived\":0,\"name\":\"Artagaveytia, Mr. Ramon\",\"title\":\"Mr\"},{\"survived\":0,\"name\":\"Astor, Col. John Jacob\",\"title\":\"Col\"},{\"survived\":1,\"name\":\"Astor, Mrs. John Jacob (Madeleine Talmadge Force)\",\"title\":\"Mrs\"},{\"survived\":1,\"name\":\"Aubart, Mme. Leontine Pauline\",\"title\":\"Mme\"},{\"survived\":1,\"name\":\"Barber, Miss. Ellen \\\"Nellie\\\"\",\"title\":\"Miss\"},{\"survived\":1,\"name\":\"Barkworth, Mr. Algernon Henry Wilson\",\"title\":\"Mr\"},{\"survived\":0,\"name\":\"Baumann, Mr. John D\",\"title\":\"Mr\"},{\"survived\":0,\"name\":\"Baxter, Mr. Quigg Edmond\",\"title\":\"Mr\"},{\"survived\":1,\"name\":\"Baxter, Mrs. James (Helene DeLaudeniere Chaput)\",\"title\":\"Mrs\"},{\"survived\":1,\"name\":\"Bazzani, Miss. Albina\",\"title\":\"Miss\"},{\"survived\":0,\"name\":\"Beattie, Mr. Thomson\",\"title\":\"Mr\"}]}"
},
"execution_count": 42,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 42
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:31:05.817959Z",
"start_time": "2025-05-28T10:31:05.769398Z"
}
},
"source": [
"titledDF.valueCounts { title }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" title count Mr 757 Miss 260 Mrs 197 Master 61 Dr 8 Rev 8 Col 4 Major 2 Mlle 2 Ms 2 Mme 1 Capt 1 Lady 1 Sir 1 Dona 1 Jonkheer 1 the Countess 1 Don 1
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"title\",\"count\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}],\"nrow\":18,\"ncol\":2},\"kotlin_dataframe\":[{\"title\":\"Mr\",\"count\":757},{\"title\":\"Miss\",\"count\":260},{\"title\":\"Mrs\",\"count\":197},{\"title\":\"Master\",\"count\":61},{\"title\":\"Dr\",\"count\":8},{\"title\":\"Rev\",\"count\":8},{\"title\":\"Col\",\"count\":4},{\"title\":\"Major\",\"count\":2},{\"title\":\"Mlle\",\"count\":2},{\"title\":\"Ms\",\"count\":2},{\"title\":\"Mme\",\"count\":1},{\"title\":\"Capt\",\"count\":1},{\"title\":\"Lady\",\"count\":1},{\"title\":\"Sir\",\"count\":1},{\"title\":\"Dona\",\"count\":1},{\"title\":\"Jonkheer\",\"count\":1},{\"title\":\"the Countess\",\"count\":1},{\"title\":\"Don\",\"count\":1}]}"
},
"execution_count": 43,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 43
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The new **Title** column contains some rare titles and some titles with typos.\n",
"Let's clean the data and merge all rare titles into one category."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:33:12.945456Z",
"start_time": "2025-05-28T10:33:12.784091Z"
}
},
"source": [
"val rareTitles = listOf(\n",
" \"Dona\", \"Lady\", \"the Countess\", \"Capt\", \"Col\", \"Don\",\n",
" \"Dr\", \"Major\", \"Rev\", \"Sir\", \"Jonkheer\",\n",
")\n",
"\n",
"val cleanedTitledDF = titledDF.update { title }.with {\n",
" when {\n",
" it == \"Mlle\" -> \"Miss\"\n",
" it == \"Ms\" -> \"Miss\"\n",
" it == \"Mme\" -> \"Mrs\"\n",
" it in rareTitles -> \"Rare Title\"\n",
" else -> it\n",
" }\n",
"}"
],
"outputs": [],
"execution_count": 44
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:33:24.948520Z",
"start_time": "2025-05-28T10:33:24.852076Z"
}
},
"source": [
"cleanedTitledDF.valueCounts { title }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" title count Mr 757 Miss 264 Mrs 198 Master 61 Rare Title 29
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"title\",\"count\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}],\"nrow\":5,\"ncol\":2},\"kotlin_dataframe\":[{\"title\":\"Mr\",\"count\":757},{\"title\":\"Miss\",\"count\":264},{\"title\":\"Mrs\",\"count\":198},{\"title\":\"Master\",\"count\":61},{\"title\":\"Rare Title\",\"count\":29}]}"
},
"execution_count": 45,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 45
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Now it looks awesome, and we have only five different titles!\n",
"Let's see how it correlates with the survival rate."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:33:57.317737Z",
"start_time": "2025-05-28T10:33:56.945450Z"
}
},
"source": [
"val correlations = cleanedTitledDF\n",
" .pivotMatches { title }\n",
" .corr { title }.with { survived }\n",
"correlations"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" title survived Miss 0.306069 Master 0.057318 Mr -0.528775 Mrs 0.352536 Rare Title -0.000915
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"title\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":5,\"ncol\":2},\"kotlin_dataframe\":[{\"title\":\"Miss\",\"survived\":0.30606871573905226},{\"title\":\"Master\",\"survived\":0.0573179698378937},{\"title\":\"Mr\",\"survived\":-0.5287747518050332},{\"title\":\"Mrs\",\"survived\":0.3525356336629826},{\"title\":\"Rare Title\",\"survived\":-9.149409567074339E-4}]}"
},
"execution_count": 46,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 46
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:34:08.120556Z",
"start_time": "2025-05-28T10:34:07.954473Z"
}
},
"source": [
"correlations\n",
" .update { title }.with { it.substringAfter('_') }\n",
" .filter { title != \"survived\" }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" title survived Miss 0.306069 Master 0.057318 Mr -0.528775 Mrs 0.352536 Rare Title -0.000915
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"title\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":5,\"ncol\":2},\"kotlin_dataframe\":[{\"title\":\"Miss\",\"survived\":0.30606871573905226},{\"title\":\"Master\",\"survived\":0.0573179698378937},{\"title\":\"Mr\",\"survived\":-0.5287747518050332},{\"title\":\"Mrs\",\"survived\":0.3525356336629826},{\"title\":\"Rare Title\",\"survived\":-9.149409567074339E-4}]}"
},
"execution_count": 47,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 47
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"The women with the title **Miss** and **Mrs** had the same chances of survival,\n",
"but this cannot be said for the men.\n",
"\n",
"If you had the title **Mr**, you were in bad luck on Titanic.\n",
"\n",
"**Rare title** is really rare and doesn't play a big role."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:35:33.581752Z",
"start_time": "2025-05-28T10:35:33.343580Z"
}
},
"source": [
"val groupedCleanedTitledDF = cleanedTitledDF\n",
" .valueCounts { title and survived }\n",
" .sortBy { title and survived }\n",
"groupedCleanedTitledDF"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" title survived count Master 0 30 Master 1 31 Miss 0 85 Miss 1 179 Mr 0 634 Mr 1 123 Mrs 0 42 Mrs 1 156 Rare Title 0 18 Rare Title 1 11
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"title\",\"survived\",\"count\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}],\"nrow\":10,\"ncol\":3},\"kotlin_dataframe\":[{\"title\":\"Master\",\"survived\":0,\"count\":30},{\"title\":\"Master\",\"survived\":1,\"count\":31},{\"title\":\"Miss\",\"survived\":0,\"count\":85},{\"title\":\"Miss\",\"survived\":1,\"count\":179},{\"title\":\"Mr\",\"survived\":0,\"count\":634},{\"title\":\"Mr\",\"survived\":1,\"count\":123},{\"title\":\"Mrs\",\"survived\":0,\"count\":42},{\"title\":\"Mrs\",\"survived\":1,\"count\":156},{\"title\":\"Rare Title\",\"survived\":0,\"count\":18},{\"title\":\"Rare Title\",\"survived\":1,\"count\":11}]}"
},
"execution_count": 48,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 48
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Surname analysis\n",
"It's alluring to dig deeper into families, and home destinations and we could start analyzing these from the surnames that can be easily extracted from the **Name** feature."
]
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:39:01.897503Z",
"start_time": "2025-05-28T10:39:01.606417Z"
}
},
"source": [
"val surnameDF = df1\n",
" .select { survived and name }\n",
" .add(\"surname\") {\n",
" name.split(\".\")[0].split(\",\")[0].trim()\n",
" }\n",
"surnameDF.head()"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" survived name surname 1 Allen, Miss. Elisabeth Walton Allen 1 Allison, Master. Hudson Trevor Allison 0 Allison, Miss. Helen Loraine Allison 0 Allison, Mr. Hudson Joshua Creighton Allison 0 Allison, Mrs. Hudson J C (Bessie Wald... Allison
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"survived\",\"name\",\"surname\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"}],\"nrow\":5,\"ncol\":3},\"kotlin_dataframe\":[{\"survived\":1,\"name\":\"Allen, Miss. Elisabeth Walton\",\"surname\":\"Allen\"},{\"survived\":1,\"name\":\"Allison, Master. Hudson Trevor\",\"surname\":\"Allison\"},{\"survived\":0,\"name\":\"Allison, Miss. Helen Loraine\",\"surname\":\"Allison\"},{\"survived\":0,\"name\":\"Allison, Mr. Hudson Joshua Creighton\",\"surname\":\"Allison\"},{\"survived\":0,\"name\":\"Allison, Mrs. Hudson J C (Bessie Waldo Daniels)\",\"surname\":\"Allison\"}]}"
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 49
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:39:06.494112Z",
"start_time": "2025-05-28T10:39:06.382904Z"
}
},
"source": [
"surnameDF.valueCounts { surname }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" surname count Andersson 11 Sage 11 Asplund 8 Goodwin 8 Davies 7 Brown 6 Carter 6 Fortune 6 Smith 6 Ford 6 Johnson 6 Panula 6 Rice 6 Skoog 6 Ryerson 5 Williams 5 Kelly 5 Lefebre 5 Palsson 5 Thomas 5
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"surname\",\"count\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Int\"}],\"nrow\":875,\"ncol\":2},\"kotlin_dataframe\":[{\"surname\":\"Andersson\",\"count\":11},{\"surname\":\"Sage\",\"count\":11},{\"surname\":\"Asplund\",\"count\":8},{\"surname\":\"Goodwin\",\"count\":8},{\"surname\":\"Davies\",\"count\":7},{\"surname\":\"Brown\",\"count\":6},{\"surname\":\"Carter\",\"count\":6},{\"surname\":\"Fortune\",\"count\":6},{\"surname\":\"Smith\",\"count\":6},{\"surname\":\"Ford\",\"count\":6},{\"surname\":\"Johnson\",\"count\":6},{\"surname\":\"Panula\",\"count\":6},{\"surname\":\"Rice\",\"count\":6},{\"surname\":\"Skoog\",\"count\":6},{\"surname\":\"Ryerson\",\"count\":5},{\"surname\":\"Williams\",\"count\":5},{\"surname\":\"Kelly\",\"count\":5},{\"surname\":\"Lefebre\",\"count\":5},{\"surname\":\"Palsson\",\"count\":5},{\"surname\":\"Thomas\",\"count\":5}]}"
},
"execution_count": 50,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 50
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:39:10.135306Z",
"start_time": "2025-05-28T10:39:10.058231Z"
}
},
"source": [
"surnameDF.surname.countDistinct()"
],
"outputs": [
{
"data": {
"text/plain": [
"875"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 51
},
{
"cell_type": "code",
"metadata": {
"ExecuteTime": {
"end_time": "2025-05-28T10:39:15.528427Z",
"start_time": "2025-05-28T10:39:14.865640Z"
}
},
"source": [
"val firstSymbol by column()\n",
"\n",
"df1\n",
" .add(firstSymbol) {\n",
" name.split(\".\")[0].split(\",\")[0].trim().first().toString()\n",
" }\n",
" .pivotMatches(firstSymbol)\n",
" .corr { firstSymbol }.with { survived }"
],
"outputs": [
{
"data": {
"text/html": [
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" firstSymbol survived A -0.017914 B 0.050554 C 0.009037 D 0.051711 E -0.034629 F 0.000400 G -0.044483 H 0.042187 I -0.008329 J -0.026790 K -0.014219 L -0.021071 M 0.019041 N 0.028698 O 0.000128 P -0.058996 R -0.021941 S -0.020043 T 0.052264 U -0.021737
\n",
" \n",
" \n",
" "
],
"application/kotlindataframe+json": "{\"$version\":\"2.1.1\",\"metadata\":{\"columns\":[\"firstSymbol\",\"survived\"],\"types\":[{\"kind\":\"ValueColumn\",\"type\":\"kotlin.String\"},{\"kind\":\"ValueColumn\",\"type\":\"kotlin.Double\"}],\"nrow\":27,\"ncol\":2},\"kotlin_dataframe\":[{\"firstSymbol\":\"A\",\"survived\":-0.01791352622509756},{\"firstSymbol\":\"B\",\"survived\":0.050553943254341316},{\"firstSymbol\":\"C\",\"survived\":0.009037371118975828},{\"firstSymbol\":\"D\",\"survived\":0.05171064357839075},{\"firstSymbol\":\"E\",\"survived\":-0.03462861880002389},{\"firstSymbol\":\"F\",\"survived\":4.002707178710613E-4},{\"firstSymbol\":\"G\",\"survived\":-0.044483069276203296},{\"firstSymbol\":\"H\",\"survived\":0.04218724210575963},{\"firstSymbol\":\"I\",\"survived\":-0.008329183461658642},{\"firstSymbol\":\"J\",\"survived\":-0.026790134975567197},{\"firstSymbol\":\"K\",\"survived\":-0.014218719831367379},{\"firstSymbol\":\"L\",\"survived\":-0.021070982850893608},{\"firstSymbol\":\"M\",\"survived\":0.019040748971095155},{\"firstSymbol\":\"N\",\"survived\":0.02869766040895532},{\"firstSymbol\":\"O\",\"survived\":1.2837933079428644E-4},{\"firstSymbol\":\"P\",\"survived\":-0.05899571294487214},{\"firstSymbol\":\"R\",\"survived\":-0.021940537137738973},{\"firstSymbol\":\"S\",\"survived\":-0.020042889901563117},{\"firstSymbol\":\"T\",\"survived\":0.05226413426840335},{\"firstSymbol\":\"U\",\"survived\":-0.0217373635753353}]}"
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"execution_count": 52
},
{
"metadata": {},
"cell_type": "code",
"outputs": [],
"execution_count": null,
"source": ""
}
],
"metadata": {
"kernelspec": {
"display_name": "Kotlin",
"language": "kotlin",
"name": "kotlin"
},
"language_info": {
"codemirror_mode": "text/x-kotlin",
"file_extension": ".kt",
"mimetype": "text/x-kotlin",
"name": "kotlin",
"nbconvert_exporter": "",
"pygments_lexer": "kotlin",
"version": "1.8.20-Beta"
},
"ktnbPluginMetadata": {
"projectLibraries": []
}
},
"nbformat": 4,
"nbformat_minor": 1
}