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   "cell_type": "markdown",
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    "# New `Scale` Functions with Parameter `aesthetic`\n",
    "\n",
    "- `scale_identity(aesthetic, *, ...)`\n",
    "- `scale_manual(aesthetic, values, *, ...)`\n",
    "- `scale_continuous(aesthetic, *, ...)`\n",
    "- `scale_gradient(aesthetic, *, ...)`\n",
    "- `scale_gradient2(aesthetic, *, ...)`\n",
    "- `scale_gradientn(aesthetic, *, ...)`\n",
    "- `scale_hue(aesthetic, *, ...)`\n",
    "- `scale_discrete(aesthetic, *, ...)`\n",
    "- `scale_grey(aesthetic, *, ...)`\n",
    "- `scale_brewer(aesthetic, *, ...)`\n",
    "- `scale_viridis(aesthetic, *, ...)`\n",
    "\n",
    "Comparing to familiar \"scale\" functions like `scale_color_gradient()` etc., the new set of functions\n",
    "adds more flexibility by allowing specifying an aesthetic or a list of aesthetics the scale is working with.\n",
    "\n",
    "For example, you can use just one function call to setup the same color palette for both, stroke and fill colors on plot:\n",
    "\n",
    "`scale_brewer(['color', 'fill'], palette='Set2')`\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-17T07:27:06.621569Z",
     "iopub.status.busy": "2024-04-17T07:27:06.621252Z",
     "iopub.status.idle": "2024-04-17T07:27:06.938730Z",
     "shell.execute_reply": "2024-04-17T07:27:06.938441Z"
    }
   },
   "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,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-17T07:27:06.940423Z",
     "iopub.status.busy": "2024-04-17T07:27:06.940193Z",
     "iopub.status.idle": "2024-04-17T07:27:06.942452Z",
     "shell.execute_reply": "2024-04-17T07:27:06.942282Z"
    }
   },
   "outputs": [
    {
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      "text/html": [
       "\n",
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       "                window.letsPlotCall = function(f) {\n",
       "                    window.letsPlotCallQueue.push(f);\n",
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       "                (function() {\n",
       "                    var script = document.createElement(\"script\");\n",
       "                    script.type = \"text/javascript\";\n",
       "                    script.src = \"https://cdn.jsdelivr.net/gh/JetBrains/lets-plot@v4.3.1/js-package/distr/lets-plot.min.js\";\n",
       "                    script.onload = function() {\n",
       "                        window.letsPlotCall = function(f) {f();};\n",
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       "                        window.letsPlotCall = function(f) {};    // noop\n",
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       "                        var div = document.createElement(\"div\");\n",
       "                        div.style.color = 'darkred';\n",
       "                        div.textContent = 'Error loading Lets-Plot JS';\n",
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       "                    };\n",
       "                    var e = document.getElementById(\"HoEaFb\");\n",
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       "            "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "LetsPlot.setup_html()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-17T07:27:06.955689Z",
     "iopub.status.busy": "2024-04-17T07:27:06.955579Z",
     "iopub.status.idle": "2024-04-17T07:27:07.096376Z",
     "shell.execute_reply": "2024-04-17T07:27:07.096065Z"
    }
   },
   "outputs": [],
   "source": [
    "mpg_df = pd.read_csv(\"https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/mpg.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. Plot with Default Colors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-17T07:27:07.097580Z",
     "iopub.status.busy": "2024-04-17T07:27:07.097482Z",
     "iopub.status.idle": "2024-04-17T07:27:07.149211Z",
     "shell.execute_reply": "2024-04-17T07:27:07.148867Z"
    }
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       "}\n",
       "}],\n",
       "\"metainfo_list\":[]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"DC5jax\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();\n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x74f9ccfac3d0>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = ggplot(mpg_df, aes(as_discrete('drv', order=-1), 'hwy')) + \\\n",
    "    geom_violin(aes(color='drv', fill='drv'), alpha=.5, size=2)\n",
    "p"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 2. Setup a Brewer Palette"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 2.1. Old School: for Each Aesthetic Separately"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-17T07:27:07.150873Z",
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     "iopub.status.idle": "2024-04-17T07:27:07.171425Z",
     "shell.execute_reply": "2024-04-17T07:27:07.171104Z"
    }
   },
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       "}\n",
       "}],\n",
       "\"metainfo_list\":[]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"HCWxRf\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();\n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x74f9ca844af0>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + scale_color_brewer(palette='Set2') + scale_fill_brewer(palette='Set2')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### 2.2. New: for Both Aesthetics at Once"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-04-17T07:27:07.172542Z",
     "iopub.status.busy": "2024-04-17T07:27:07.172437Z",
     "iopub.status.idle": "2024-04-17T07:27:07.193149Z",
     "shell.execute_reply": "2024-04-17T07:27:07.192964Z"
    }
   },
   "outputs": [
    {
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       "}\n",
       "}],\n",
       "\"metainfo_list\":[]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"krhX46\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();\n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.core.PlotSpec at 0x74f9ca8602e0>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p + scale_brewer(['color', 'fill'], palette='Set2')"
   ]
  }
 ],
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