From 9acb86b269bd61f65c7c014e148b3761017f2e6c Mon Sep 17 00:00:00 2001
From: Rashid Yangazov <129742127+RYangazov@users.noreply.github.com>
Date: Fri, 29 Mar 2024 13:00:27 +0100
Subject: [PATCH 1/4] Refactoring of choosing orientation. Move logic into init
method of LayerConfig.
---
.../auto_orientation_discretes.ipynb | 3413 +++++++++++++++++
docs/f-24b/auto_rotate.ipynb | 891 +++++
future_changes.md | 5 +
.../core/spec/config/DataConfigUtil.kt | 22 +
.../letsPlot/core/spec/config/LayerConfig.kt | 45 +
5 files changed, 4376 insertions(+)
create mode 100644 docs/dev/notebooks/auto_orientation_discretes.ipynb
create mode 100644 docs/f-24b/auto_rotate.ipynb
diff --git a/docs/dev/notebooks/auto_orientation_discretes.ipynb b/docs/dev/notebooks/auto_orientation_discretes.ipynb
new file mode 100644
index 00000000000..5981f0ce050
--- /dev/null
+++ b/docs/dev/notebooks/auto_orientation_discretes.ipynb
@@ -0,0 +1,3413 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "88b6cfbb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import pandas as pd\n",
+ "import random\n",
+ "from lets_plot import *\n",
+ "from lets_plot.mapping import as_discrete"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "a7fd8774",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ " \n",
+ " \n",
+ " "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "def dump_plot(plot, display=None):\n",
+ " import json\n",
+ "\n",
+ " try:\n",
+ " import clipboard\n",
+ " except:\n",
+ " clipboard = None\n",
+ " \n",
+ " from lets_plot._type_utils import standardize_dict\n",
+ " \n",
+ " plot_dict = standardize_dict(plot.as_dict())\n",
+ " plot_json = json.dumps(plot_dict, indent=2)\n",
+ " \n",
+ " if clipboard:\n",
+ " clipboard.copy('')\n",
+ " clipboard.copy(str(plot_json))\n",
+ " else:\n",
+ " if display is None:\n",
+ " display = True\n",
+ " \n",
+ " if display:\n",
+ " print(plot_json)\n",
+ "\n",
+ " return plot\n",
+ "\n",
+ "LetsPlot.setup_html()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "f51ee2cf",
+ "metadata": {},
+ "source": [
+ "## Regression Testing\n",
+ "Regression testing of geometries that may be affected by current changes."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "eeb35e19",
+ "metadata": {},
+ "source": [
+ "### Scatter Plots"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "2297d2f8",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "np.random.seed(42)\n",
+ "data = dict(\n",
+ " cond=np.repeat(['A','B'], 10),\n",
+ " xvar=[i + random.normalvariate(0, 3) for i in range(0,20)],\n",
+ " yvar=[i + random.normalvariate(0, 3) for i in range(0,20)]\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "id": "bb8a7928",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes(x='xvar', y='yvar')) + geom_point(shape=1),\n",
+ " ggplot(data, aes(x='yvar', y='xvar')) + geom_point(shape=1),\n",
+ " ggplot(data, aes(x='xvar', y='yvar')) + geom_point(shape=1) + geom_smooth(),\n",
+ " ggplot(data, aes(x='yvar', y='xvar')) + geom_point(shape=1) + geom_smooth()\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "id": "1d892d2d",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes(x='xvar', y='yvar', color='cond')) + geom_point(shape=1) + geom_smooth(se=False),\n",
+ " ggplot(data, aes(x='yvar', y='xvar', color='cond')) + geom_point(shape=1) + geom_smooth(se=False)\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "7531ddf4",
+ "metadata": {},
+ "source": [
+ "### Marginal Plots"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "id": "3247f51a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "np.random.seed(42)\n",
+ "cov0=[[1, -.8], [-.8, 1]] \n",
+ "cov1=[[ 10, .1], [.1, .1]]\n",
+ "\n",
+ "x0, y0 = np.random.multivariate_normal(mean=[-2,0], cov=cov0, size=200).T\n",
+ "x1, y1 = np.random.multivariate_normal(mean=[0,1], cov=cov1, size=200).T\n",
+ "\n",
+ "data = dict(\n",
+ " x = np.concatenate((x0,x1)),\n",
+ " y = np.concatenate((y0,y1)),\n",
+ " c = [\"A\"]*200 + [\"B\"]*200\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "id": "4cbc63a4",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes(\"x\", \"y\")) + geom_density2df(aes(fill=\"..level..\")) + coord_cartesian() \\\n",
+ " + ggmarginal(\"tr\", layer=geom_area(stat=\"density\")),\n",
+ " ggplot(data, aes(\"y\", \"x\")) + geom_density2df(aes(fill=\"..level..\")) + coord_cartesian() \\\n",
+ " + ggmarginal(\"tr\", layer=geom_area(stat=\"density\"))\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "15bd6c1d",
+ "metadata": {},
+ "source": [
+ "### `coord_flip()`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "id": "c52de749",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "np.random.seed(42)\n",
+ "n = 10\n",
+ "x = np.arange(n)\n",
+ "y = 1 + np.random.randint(5, size=10)\n",
+ "gggrid([\n",
+ " ggplot() + geom_bar(aes(x='x', y='y'), data={'x': x, 'y': y}, stat='identity'),\n",
+ " ggplot() + geom_bar(aes(x='x', y='y'), data={'x': x, 'y': y}, stat='identity') + coord_flip()\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "55bb8824",
+ "metadata": {},
+ "source": [
+ "### `geom_bar()`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "id": "959a5ec0",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data = {\n",
+ " 'code': ['a','b','c','d','e'],\n",
+ " 'value': [2, 5, 3, 8, -1],\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "id": "1a4077a0",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes('code', 'value')) + geom_bar(stat='identity'),\n",
+ " ggplot(data, aes('value', 'code')) + geom_bar(orientation='y', stat='identity'),\n",
+ " ggplot(data, aes('value', 'code')) + geom_bar(stat='identity'),\n",
+ " ggplot(data) + geom_bar(aes('value', 'code'), stat='identity'),\n",
+ " ggplot(data, aes('value', as_discrete('code'))) + geom_bar(stat='identity')\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e737e168",
+ "metadata": {},
+ "source": [
+ "### `geom_lollipop()`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "id": "27967418",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes('code', 'value')) + geom_lollipop(stat='identity'),\n",
+ " ggplot(data, aes('value', 'code')) + geom_lollipop(orientation='y', stat='identity'),\n",
+ " ggplot(data, aes('value', 'code')) + geom_lollipop(stat='identity'),\n",
+ " ggplot(data) + geom_lollipop(aes('value', 'code'), stat='identity'),\n",
+ " ggplot(data, aes('value', as_discrete('code'))) + geom_lollipop(stat='identity') \n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e3b7b6b7",
+ "metadata": {},
+ "source": [
+ "### `geom_boxplot()`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "id": "8e934911",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "n = 100\n",
+ "np.random.seed(42)\n",
+ "data = {\n",
+ " 'code': np.random.choice(list('abcde'), size=100),\n",
+ " 'value': np.random.normal(size=100),\n",
+ " 'value_str': [str(i) for i in np.random.normal(size=100)],\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "id": "df453671",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 13,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes('code', 'value')) + geom_boxplot(),\n",
+ " ggplot(data, aes('value', 'code')) + geom_boxplot(orientation='y'),\n",
+ " ggplot(data, aes('value', 'code')) + geom_boxplot(),\n",
+ " ggplot(data) + geom_boxplot(aes('value', 'code')),\n",
+ " ggplot(data, aes('value', as_discrete('code'))) + geom_boxplot() \n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "0dacca7a",
+ "metadata": {},
+ "source": [
+ "### `geom_violin()`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "id": "7db1d033",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 14,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes('code', 'value')) + geom_violin(),\n",
+ " ggplot(data, aes('value', 'code')) + geom_violin(orientation='y'),\n",
+ " ggplot(data, aes('value', 'code')) + geom_violin(),\n",
+ " ggplot(data) + geom_violin(aes('value', 'code')),\n",
+ " ggplot(data, aes('value', as_discrete('code'))) + geom_violin() \n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "e1d07a13",
+ "metadata": {},
+ "source": [
+ "### `geom_ydotplot()`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "id": "5a05e47f",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 15,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "p = gggrid([\n",
+ " ggplot(data, aes('code', 'value')) + geom_ydotplot(),\n",
+ " ggplot(data, aes('value', 'code')) + geom_ydotplot(orientation='y'),\n",
+ " ggplot(data, aes('value', 'code')) + geom_ydotplot(),\n",
+ " ggplot(data) + geom_ydotplot(aes('value', 'code')),\n",
+ " ggplot(data, aes('value', as_discrete('code'))) + geom_ydotplot() \n",
+ "])\n",
+ "dump_plot(p)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "632d6de8",
+ "metadata": {},
+ "source": [
+ "## Some Special Cases"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "92f95198",
+ "metadata": {},
+ "source": [
+ "### `geom_smooth()`\n",
+ "`geom_smooth()` needs `orientation=”y”` when we want to flip axis."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "id": "bb724b19",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "np.random.seed(42)\n",
+ "n = 100\n",
+ "x = np.linspace(-2, 2, n)\n",
+ "y = x ** 2 + np.random.normal(size=n)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "id": "d5bd40cb",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 17,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_point() + geom_smooth(deg=2, se=False),\n",
+ " ggplot({'x': x, 'y': y}, aes(x='y', y='x')) + geom_point() + geom_smooth(deg=2, se=False),\n",
+ " ggplot({'x': x, 'y': y}, aes(x='y', y='x')) + geom_point() + geom_smooth(deg=2, se=False, orientation=\"y\"),\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "aa2e0c86",
+ "metadata": {},
+ "source": [
+ "### Few Datasets"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "bbc0359b",
+ "metadata": {},
+ "source": [
+ "If we have some dataset in the `ggplot()` context, then we can use data from it in `geom_boxplot()`. And, in this case, we can use variable names from the `ggplot()` context even if we set another context in `geom_boxplot()`."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 18,
+ "id": "baf88e20",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "np.random.seed(42)\n",
+ "data = {\n",
+ " 'code': np.random.choice(list('abcde'), size=100),\n",
+ " 'value': np.random.normal(size=100),\n",
+ " 'value_str': [str(i) for i in np.random.normal(size=100)],\n",
+ "}\n",
+ "data_num = {\n",
+ " 'number': np.random.choice(list('qwxyz'), size=100),\n",
+ " 'volume': np.random.normal(size=100),\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 19,
+ "id": "956932a3",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 19,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes('value', 'code')) + geom_boxplot(aes('number', 'volume'), data = data_num),\n",
+ " ggplot(data, aes('value', 'code')) + geom_boxplot(aes('value', 'code'), data = data_num)\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b9a2bded",
+ "metadata": {},
+ "source": [
+ "### `stat_summary(geom='crossbar')`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 20,
+ "id": "f0976fe8",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 20,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot(data, aes('code', 'value')) + stat_summary(geom='crossbar'),\n",
+ " ggplot(data, aes('value', 'code')) + stat_summary(geom='crossbar') \n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "f949d6de",
+ "metadata": {},
+ "source": [
+ "### Discrete Both Axes"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 21,
+ "id": "0aba6fbb",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "x = ['a', 'a', 'b', 'b']\n",
+ "y = ['x','x', 'x', 'y']"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "fa99080f",
+ "metadata": {},
+ "source": [
+ "For `stat_sum()` and `geom_point()`, rotation does not work for both discrete axes."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 22,
+ "id": "14e36676",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 22,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + stat_sum(),\n",
+ " ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_point(orientation=\"y\")\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5a761ca2",
+ "metadata": {},
+ "source": [
+ "The lollipop can be drawing when both axes are discrete. But this case is not usual for a lollipop."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 23,
+ "id": "f5ccf129",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 23,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "x = ['a', 'a', 'a', 'b', 'b']\n",
+ "y = ['x','x', 'x', 'y', 'y']\n",
+ "gggrid([\n",
+ " ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_lollipop(stat='count'),\n",
+ " ggplot({'x': x, 'y': y}, aes(x='x')) + geom_lollipop(stat='count'),\n",
+ " ggplot({'x': x, 'y': y}, aes(y='y')) + geom_lollipop(stat='count'), \n",
+ " ggplot({'x': x, 'y': y}, aes(y='y')) + geom_lollipop(stat='count', orientation='x'), \n",
+ " ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_lollipop(stat='count', orientation='y') \n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "c5b003f3",
+ "metadata": {},
+ "source": [
+ "### `stat='boxplot'`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "id": "70805e17",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "n = 50\n",
+ "np.random.seed(42)\n",
+ "x = np.random.uniform(size=n)\n",
+ "c = np.random.choice(['a', 'b', 'c'], size=n)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "id": "e27e1ed0",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 25,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "p1 = ggplot({'x': x, 'c': c}) + \\\n",
+ " geom_crossbar(aes(x='c', y='x', color='c'), \\\n",
+ " stat='boxplot') + \\\n",
+ " geom_point(aes(x='c', y='x', color='c'), \\\n",
+ " size=4, shape=21, fill='white',\n",
+ " position=position_jitterdodge(seed=42))\n",
+ "p2 = ggplot({'x': x, 'c': c}) + \\\n",
+ " geom_crossbar(aes(x='x', y='c', color='c'), \\\n",
+ " stat='boxplot') + \\\n",
+ " geom_point(aes(x='x', y='c', color='c'), \\\n",
+ " size=4, shape=21, fill='white',\n",
+ " position=position_jitterdodge(seed=42))\n",
+ "gggrid([p1, p2])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "id": "0986ea7d",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "n = 100\n",
+ "np.random.seed(42)\n",
+ "x = np.random.choice(['a', 'b', 'c'], size=n)\n",
+ "y = np.random.normal(size=n)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 27,
+ "id": "e687f5c9",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 27,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_pointrange(stat='boxplot'),\n",
+ " ggplot({'x': x, 'y': y}, aes(x='y', y='x')) + geom_pointrange(stat='boxplot')\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "6604561b",
+ "metadata": {},
+ "source": [
+ "### `stat='boxplot_outlier'`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 28,
+ "id": "c7b7a899",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 28,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([\n",
+ " ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_pointrange(stat='boxplot_outlier'),\n",
+ " ggplot({'x': x, 'y': y}, aes(x='y', y='x')) + geom_pointrange(stat='boxplot_outlier')\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "57f10f16",
+ "metadata": {},
+ "source": [
+ "### `stat_summary()`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 29,
+ "id": "6bdc4826",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 29,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "p1 = ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + \\\n",
+ " stat_summary(position=position_nudge(x=-.1), color=\"red\") + \\\n",
+ " stat_summary(fun='mq', fun_min='lq', fun_max='uq', quantiles=[.1, .5, .9], \\\n",
+ " position=position_nudge(x=.1), color=\"blue\")\n",
+ "p2 = p=ggplot({'x': x, 'y': y}, aes(x='y', y='x')) + \\\n",
+ " stat_summary(position=position_nudge(x=-.1), color=\"red\") + \\\n",
+ " stat_summary(fun='mq', fun_min='lq', fun_max='uq', quantiles=[.1, .5, .9], \\\n",
+ " position=position_nudge(x=.1), color=\"blue\")\n",
+ "gggrid([p1, p2])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "a44e0244",
+ "metadata": {},
+ "source": [
+ "### `stat='ydensity'`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 30,
+ "id": "3248a6b1",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 30,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([ \n",
+ " ggplot({'x': x, 'y': y}, aes('x', 'y')) + geom_crossbar(aes(ymin='..y..', ymax='..y..', width='..violinwidth..'), stat='ydensity'),\n",
+ " ggplot({'x': x, 'y': y}, aes('y', 'x')) + geom_crossbar(aes(ymin='..y..', ymax='..y..', width='..violinwidth..'), stat='ydensity', orientation='y'),\n",
+ " ggplot({'x': x, 'y': y}, aes('y', 'x')) + geom_crossbar(aes(ymin='..y..', ymax='..y..', width='..violinwidth..'), stat='ydensity')\n",
+ "])"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "5296f46a",
+ "metadata": {},
+ "source": [
+ "### `stat='ydotplot'`"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 31,
+ "id": "9d820d5e",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "n = 100\n",
+ "np.random.seed(42)\n",
+ "x = np.random.choice(['a'], size=n)\n",
+ "y = np.random.normal(size=n)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 32,
+ "id": "08d6ea01",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " "
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 32,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gggrid([ \n",
+ " ggplot({'x': x, 'y': y}, aes(x='x', y='y')) + geom_crossbar(aes(ymin='..y..', ymax='..y..', width='..count..'), stat='ydotplot'),\n",
+ " ggplot({'x': x, 'y': y}, aes(x='y', y='x')) + geom_crossbar(aes(ymin='..y..', ymax='..y..', width='..count..'), stat='ydotplot', orientation='y'),\n",
+ " ggplot({'x': x, 'y': y}, aes(x='y', y='x')) + geom_crossbar(aes(ymin='..y..', ymax='..y..', width='..count..'), stat='ydotplot')\n",
+ "])"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.10.11"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/f-24b/auto_rotate.ipynb b/docs/f-24b/auto_rotate.ipynb
new file mode 100644
index 00000000000..c517f0a8b89
--- /dev/null
+++ b/docs/f-24b/auto_rotate.ipynb
@@ -0,0 +1,891 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "id": "e00d3551",
+ "metadata": {},
+ "source": [
+ "# Automatically Choose `orientation=\"y\"` When Aes Y Is Discrete"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "id": "ff95f57a",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "\n",
+ "from lets_plot import *\n",
+ "from lets_plot.mapping import as_discrete"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "id": "eae93dff",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ " \n",
+ " \n",
+ " "
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "LetsPlot.setup_html()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "id": "26cdc00e",
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " country | \n",
+ " continent | \n",
+ " year | \n",
+ " lifeExp | \n",
+ " pop | \n",
+ " gdpPercap | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " | 0 | \n",
+ " Afghanistan | \n",
+ " Asia | \n",
+ " 1952 | \n",
+ " 28.801 | \n",
+ " 8425333 | \n",
+ " 779.445314 | \n",
+ "
\n",
+ " \n",
+ " | 1 | \n",
+ " Afghanistan | \n",
+ " Asia | \n",
+ " 1957 | \n",
+ " 30.332 | \n",
+ " 9240934 | \n",
+ " 820.853030 | \n",
+ "
\n",
+ " \n",
+ " | 2 | \n",
+ " Afghanistan | \n",
+ " Asia | \n",
+ " 1962 | \n",
+ " 31.997 | \n",
+ " 10267083 | \n",
+ " 853.100710 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "