noj.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "172d9ba4-ca73-4e44-a36e-f2bdd93af00e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "nil"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(require '[tablecloth.api :as tc]\n",
    "         '[clojure.string :as str]\n",
    "         '[scicloj.kindly.v4.kind :as kind]\n",
    "         '[scicloj.tableplot.v1.plotly :as plotly]\n",
    "         '[scicloj.tableplot.v1.hanami :as hanami]\n",
    "         '[scicloj.kindly-advice.v1.api :as kindly-advice]\n",
    "         '[scicloj.kindly.v4.kind :as kind]\n",
    "         '[scicloj.kindly.v4.api :as kindly]\n",
    "         '[clojupyter.display :as display]\n",
    "         )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0904321f-3d8a-49dd-b400-71fd2ca0b6a4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/fetch-dataset"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defn fetch-dataset [dataset-name]\n",
    "  (-> dataset-name\n",
    "      (->> (format \"https://vincentarelbundock.github.io/Rdatasets/csv/%s.csv\"))\n",
    "      (tc/dataset {:key-fn (fn [k]\n",
    "                             (-> k\n",
    "                                 str/lower-case\n",
    "                                 (str/replace #\"\\.\" \"-\")\n",
    "                                 keyword))})\n",
    "      (tc/set-dataset-name dataset-name)))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "619fb938-c212-4dce-adfd-5a575a420ed5",
   "metadata": {},
   "source": [
    "# iris \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "663a70dc-ba24-47b0-9297-fca469090819",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "#'user/iris"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(defonce iris\n",
    "  (fetch-dataset \"datasets/iris\"))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "21dabc97-1f5b-4230-a256-e7e78801ef10",
   "metadata": {},
   "source": [
    "## :kind/dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "6a58f496-2f92-49b2-82d8-4c9db0c1f1c7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"kind-dataset\"><p>datasets/iris [150 6]:</p><table><thead><tr><th style=\"text-align:right;\">:rownames</th><th style=\"text-align:right;\">:sepal-length</th><th style=\"text-align:right;\">:sepal-width</th><th style=\"text-align:right;\">:petal-length</th><th style=\"text-align:right;\">:petal-width</th><th>:species</th></tr></thead><tbody><tr><td style=\"text-align:right;\">1</td><td style=\"text-align:right;\">5.1</td><td style=\"text-align:right;\">3.5</td><td style=\"text-align:right;\">1.4</td><td style=\"text-align:right;\">0.2</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">2</td><td style=\"text-align:right;\">4.9</td><td style=\"text-align:right;\">3.0</td><td style=\"text-align:right;\">1.4</td><td style=\"text-align:right;\">0.2</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">3</td><td style=\"text-align:right;\">4.7</td><td style=\"text-align:right;\">3.2</td><td style=\"text-align:right;\">1.3</td><td style=\"text-align:right;\">0.2</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">4</td><td style=\"text-align:right;\">4.6</td><td style=\"text-align:right;\">3.1</td><td style=\"text-align:right;\">1.5</td><td style=\"text-align:right;\">0.2</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">5</td><td style=\"text-align:right;\">5.0</td><td style=\"text-align:right;\">3.6</td><td style=\"text-align:right;\">1.4</td><td style=\"text-align:right;\">0.2</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">6</td><td style=\"text-align:right;\">5.4</td><td style=\"text-align:right;\">3.9</td><td style=\"text-align:right;\">1.7</td><td style=\"text-align:right;\">0.4</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">7</td><td style=\"text-align:right;\">4.6</td><td style=\"text-align:right;\">3.4</td><td style=\"text-align:right;\">1.4</td><td style=\"text-align:right;\">0.3</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">8</td><td style=\"text-align:right;\">5.0</td><td style=\"text-align:right;\">3.4</td><td style=\"text-align:right;\">1.5</td><td style=\"text-align:right;\">0.2</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">9</td><td style=\"text-align:right;\">4.4</td><td style=\"text-align:right;\">2.9</td><td style=\"text-align:right;\">1.4</td><td style=\"text-align:right;\">0.2</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">10</td><td style=\"text-align:right;\">4.9</td><td style=\"text-align:right;\">3.1</td><td style=\"text-align:right;\">1.5</td><td style=\"text-align:right;\">0.1</td><td>setosa</td></tr><tr><td style=\"text-align:right;\">...</td><td style=\"text-align:right;\">...</td><td style=\"text-align:right;\">...</td><td style=\"text-align:right;\">...</td><td style=\"text-align:right;\">...</td><td>...</td></tr><tr><td style=\"text-align:right;\">140</td><td style=\"text-align:right;\">6.9</td><td style=\"text-align:right;\">3.1</td><td style=\"text-align:right;\">5.4</td><td style=\"text-align:right;\">2.1</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">141</td><td style=\"text-align:right;\">6.7</td><td style=\"text-align:right;\">3.1</td><td style=\"text-align:right;\">5.6</td><td style=\"text-align:right;\">2.4</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">142</td><td style=\"text-align:right;\">6.9</td><td style=\"text-align:right;\">3.1</td><td style=\"text-align:right;\">5.1</td><td style=\"text-align:right;\">2.3</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">143</td><td style=\"text-align:right;\">5.8</td><td style=\"text-align:right;\">2.7</td><td style=\"text-align:right;\">5.1</td><td style=\"text-align:right;\">1.9</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">144</td><td style=\"text-align:right;\">6.8</td><td style=\"text-align:right;\">3.2</td><td style=\"text-align:right;\">5.9</td><td style=\"text-align:right;\">2.3</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">145</td><td style=\"text-align:right;\">6.7</td><td style=\"text-align:right;\">3.3</td><td style=\"text-align:right;\">5.7</td><td style=\"text-align:right;\">2.5</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">146</td><td style=\"text-align:right;\">6.7</td><td style=\"text-align:right;\">3.0</td><td style=\"text-align:right;\">5.2</td><td style=\"text-align:right;\">2.3</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">147</td><td style=\"text-align:right;\">6.3</td><td style=\"text-align:right;\">2.5</td><td style=\"text-align:right;\">5.0</td><td style=\"text-align:right;\">1.9</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">148</td><td style=\"text-align:right;\">6.5</td><td style=\"text-align:right;\">3.0</td><td style=\"text-align:right;\">5.2</td><td style=\"text-align:right;\">2.0</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">149</td><td style=\"text-align:right;\">6.2</td><td style=\"text-align:right;\">3.4</td><td style=\"text-align:right;\">5.4</td><td style=\"text-align:right;\">2.3</td><td>virginica</td></tr><tr><td style=\"text-align:right;\">150</td><td style=\"text-align:right;\">5.9</td><td style=\"text-align:right;\">3.0</td><td style=\"text-align:right;\">5.1</td><td style=\"text-align:right;\">1.8</td><td>virginica</td></tr></tbody></table></div>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e88aa428-80e4-472a-80dc-1263bfc17415",
   "metadata": {},
   "source": [
    "## :kind/plotly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c57f8687-ff33-4b0d-9106-f480c4e3a7b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"height:500px;width:500px;\"><script charset=\"utf-8\" src=\"https://cdn.plot.ly/plotly-2.35.2.min.js\"></script><script>Plotly.newPlot(document.currentScript.parentElement, [{\"y\":[5.1,4.9,4.7,4.6,5.0,5.4,4.6,5.0,4.4,4.9,5.4,4.8,4.8,4.3,5.8,5.7,5.4,5.1,5.7,5.1,5.4,5.1,4.6,5.1,4.8,5.0,5.0,5.2,5.2,4.7,4.8,5.4,5.2,5.5,4.9,5.0,5.5,4.9,4.4,5.1,5.0,4.5,4.4,5.0,5.1,4.8,5.1,4.6,5.3,5.0],\"r\":null,\"name\":\"setosa\",\"marker\":{\"color\":\"#1B9E77\",\"size\":10},\"fill\":null,\"mode\":\"markers\",\"width\":null,\"type\":\"scatter\",\"theta\":null,\"z\":null,\"lon\":null,\"lat\":null,\"x\":[3.5,3.0,3.2,3.1,3.6,3.9,3.4,3.4,2.9,3.1,3.7,3.4,3.0,3.0,4.0,4.4,3.9,3.5,3.8,3.8,3.4,3.7,3.6,3.3,3.4,3.0,3.4,3.5,3.4,3.2,3.1,3.4,4.1,4.2,3.1,3.2,3.5,3.6,3.0,3.4,3.5,2.3,3.2,3.5,3.8,3.0,3.8,3.2,3.7,3.3],\"text\":null},{\"y\":[7.0,6.4,6.9,5.5,6.5,5.7,6.3,4.9,6.6,5.2,5.0,5.9,6.0,6.1,5.6,6.7,5.6,5.8,6.2,5.6,5.9,6.1,6.3,6.1,6.4,6.6,6.8,6.7,6.0,5.7,5.5,5.5,5.8,6.0,5.4,6.0,6.7,6.3,5.6,5.5,5.5,6.1,5.8,5.0,5.6,5.7,5.7,6.2,5.1,5.7],\"r\":null,\"name\":\"versicolor\",\"marker\":{\"color\":\"#D95F02\",\"size\":10},\"fill\":null,\"mode\":\"markers\",\"width\":null,\"type\":\"scatter\",\"theta\":null,\"z\":null,\"lon\":null,\"lat\":null,\"x\":[3.2,3.2,3.1,2.3,2.8,2.8,3.3,2.4,2.9,2.7,2.0,3.0,2.2,2.9,2.9,3.1,3.0,2.7,2.2,2.5,3.2,2.8,2.5,2.8,2.9,3.0,2.8,3.0,2.9,2.6,2.4,2.4,2.7,2.7,3.0,3.4,3.1,2.3,3.0,2.5,2.6,3.0,2.6,2.3,2.7,3.0,2.9,2.9,2.5,2.8],\"text\":null},{\"y\":[6.3,5.8,7.1,6.3,6.5,7.6,4.9,7.3,6.7,7.2,6.5,6.4,6.8,5.7,5.8,6.4,6.5,7.7,7.7,6.0,6.9,5.6,7.7,6.3,6.7,7.2,6.2,6.1,6.4,7.2,7.4,7.9,6.4,6.3,6.1,7.7,6.3,6.4,6.0,6.9,6.7,6.9,5.8,6.8,6.7,6.7,6.3,6.5,6.2,5.9],\"r\":null,\"name\":\"virginica\",\"marker\":{\"color\":\"#7570B3\",\"size\":10},\"fill\":null,\"mode\":\"markers\",\"width\":null,\"type\":\"scatter\",\"theta\":null,\"z\":null,\"lon\":null,\"lat\":null,\"x\":[3.3,2.7,3.0,2.9,3.0,3.0,2.5,2.9,2.5,3.6,3.2,2.7,3.0,2.5,2.8,3.2,3.0,3.8,2.6,2.2,3.2,2.8,2.8,2.7,3.3,3.2,2.8,3.0,2.8,3.0,2.8,3.8,2.8,2.8,2.6,3.0,3.4,3.1,3.0,3.1,3.1,3.1,2.7,3.2,3.3,3.0,2.5,3.0,3.4,3.0],\"text\":null}]);</script></div>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "(-> iris\n",
    "    (plotly/layer-point {:=x :sepal-width\n",
    "                         :=y :sepal-length\n",
    "                         :=color :species\n",
    "                         :=mark-size 10})\n",
    "    plotly/plot\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2910f17-0f13-4456-95cf-e8504b2d37b5",
   "metadata": {},
   "source": [
    "## :kind/md"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "ec7ce230-a18c-4b52-89ff-91bc275de322",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/markdown": [
       "**bold**"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(kind/md \"**bold**\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "efe3ae60-bba4-4cfb-a9ed-382c2bfc23b1",
   "metadata": {},
   "source": [
    "##  :kind/vega-lite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "626087db-1628-477f-9b9a-1770d002a93d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "background": "floralwhite",
       "data": {
        "format": {
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"
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(-> iris\n",
    "    (hanami/plot hanami/point-chart\n",
    "                 {:=x :sepal-width\n",
    "                  :=y :sepal-length\n",
    "                  :=color :species\n",
    "                  :=mark-size 200}))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aff26dd4-b172-4acc-bd91-9ea0f9b58bd2",
   "metadata": {},
   "source": [
    "## :kind/tex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "592d21bb-cf45-4471-97b5-6e263136716b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$\\sin{x}$"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "(kind/tex \"$\\\\sin{x}$\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "1648c21b-c39d-43c0-971d-ceac3a9acba8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[#clojupyter.misc.display.Latex{:latex \"$\\\\sin{x}$\"} #clojupyter.misc.display.Latex{:latex \"$\\\\cos{x}$\"}]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[\n",
    "(display/latex \"$\\\\sin{x}$\")\n",
    " (display/latex \"$\\\\cos{x}$\")\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41fcaea6-25ba-4a9b-95d2-1a4072adcb58",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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