{ "cells": [ { "cell_type": "markdown", "id": "social-orange", "metadata": {}, "source": [ "The `viridis` color maps are designed to be perceptually-uniform, both in regular form and also when converted to black-and-white.\n", "\n", "More info: https://bids.github.io/colormap/" ] }, { "cell_type": "code", "execution_count": 1, "id": "unknown-parker", "metadata": { "execution": { "iopub.execute_input": "2025-12-03T16:04:40.421649Z", "iopub.status.busy": "2025-12-03T16:04:40.419857Z", "iopub.status.idle": "2025-12-03T16:04:43.037891Z", "shell.execute_reply": "2025-12-03T16:04:43.037494Z" } }, "outputs": [ { "data": { "text/html": [ "
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miles per gallonnumber of cylindersengine displacement (cu. inches)engine horsepowervehicle weight (lbs.)time to accelerate (sec.)model yearorigin of carvehicle name
18.0000008307.000000130350412.00000070USchevrolet chevelle malibu
15.0000008350.000000165369311.50000070USbuick skylark 320
18.0000008318.000000150343611.00000070USplymouth satellite
\n", " \n", " \n", " " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "val mpg = DataFrame.readCSV(\"https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg2.csv\")\n", "mpg.head(3)" ] }, { "cell_type": "code", "execution_count": 4, "id": "affected-testament", "metadata": { "execution": { "iopub.execute_input": "2025-12-03T16:04:43.812763Z", "iopub.status.busy": "2025-12-03T16:04:43.812366Z", "iopub.status.idle": "2025-12-03T16:04:43.866884Z", "shell.execute_reply": "2025-12-03T16:04:43.866625Z" } }, "outputs": [], "source": [ "import org.jetbrains.letsPlot.intern.Plot\n", "\n", "fun pair(p0:Plot, p1:Plot):Figure {\n", " return gggrid(\n", " listOf(p0, p1),\n", " ncol = 2,\n", " fit = true\n", " ) + ggsize(1000, 300)\n", "}" ] }, { "cell_type": "code", "execution_count": 5, "id": "numeric-silver", "metadata": { "execution": { "iopub.execute_input": "2025-12-03T16:04:43.868922Z", "iopub.status.busy": "2025-12-03T16:04:43.868458Z", "iopub.status.idle": "2025-12-03T16:04:43.966817Z", "shell.execute_reply": "2025-12-03T16:04:43.966541Z" } }, "outputs": [], "source": [ "val pC = letsPlot(mpg.toMap()) + \n", " geomPoint(size = 7) {x = \"vehicle weight (lbs.)\"; y = \"miles per gallon\"; color = \"miles per gallon\"} + \n", " ggtitle(\"Continuous data\") + labs(color = \"MPG\")\n", "\n", "val pD = letsPlot(mpg.toMap()) + geomBar{x = \"origin of car\"; fill = \"origin of car\"} +\n", " ggtitle(\"Discrete data\") + labs(fill = \"\")" ] }, { "cell_type": "markdown", "id": "pretty-cemetery", "metadata": {}, "source": [ "### The \"viridis\" colormap is the default option.\n", "\n", "Adjust scales with `begin, end, alpha` and `direction` parameters." ] }, { "cell_type": "code", "execution_count": 6, "id": "cathedral-shark", "metadata": { "execution": { "iopub.execute_input": "2025-12-03T16:04:43.968690Z", "iopub.status.busy": "2025-12-03T16:04:43.968133Z", "iopub.status.idle": "2025-12-03T16:04:44.286236Z", "shell.execute_reply": "2025-12-03T16:04:44.286365Z" } }, "outputs": [ { "data": { "text/html": [ "
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