docs/f-24b/auto_rotate.ipynb

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   "metadata": {},
   "source": [
    "# Automatically Choose `orientation=\"y\"` When Aes Y Is Discrete"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ff95f57a",
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   "source": [
    "import pandas as pd\n",
    "\n",
    "from lets_plot import *\n",
    "from lets_plot.mapping import as_discrete"
   ]
  },
  {
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   "execution_count": 2,
   "id": "eae93dff",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>country</th>\n",
       "      <th>continent</th>\n",
       "      <th>year</th>\n",
       "      <th>lifeExp</th>\n",
       "      <th>pop</th>\n",
       "      <th>gdpPercap</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1952</td>\n",
       "      <td>28.801</td>\n",
       "      <td>8425333</td>\n",
       "      <td>779.445314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1957</td>\n",
       "      <td>30.332</td>\n",
       "      <td>9240934</td>\n",
       "      <td>820.853030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Afghanistan</td>\n",
       "      <td>Asia</td>\n",
       "      <td>1962</td>\n",
       "      <td>31.997</td>\n",
       "      <td>10267083</td>\n",
       "      <td>853.100710</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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       "       country continent  year  lifeExp       pop   gdpPercap\n",
       "0  Afghanistan      Asia  1952   28.801   8425333  779.445314\n",
       "1  Afghanistan      Asia  1957   30.332   9240934  820.853030\n",
       "2  Afghanistan      Asia  1962   31.997  10267083  853.100710"
      ]
     },
     "execution_count": 3,
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   ],
   "source": [
    "df = pd.read_csv('https://raw.githubusercontent.com/JetBrains/lets-plot-docs/master/data/gapminder.csv')\n",
    "albania_df = df.loc[df['country'] == 'Albania']\n",
    "df.head(3)"
   ]
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   "cell_type": "markdown",
   "id": "624bf284",
   "metadata": {},
   "source": [
    "#### 1. How Does Automatic Setting `orientation=\"y\"` Work"
   ]
  },
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   "cell_type": "code",
   "execution_count": 4,
   "id": "f1acbed4",
   "metadata": {},
   "outputs": [
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       "\"orientation\":\"y\",\n",
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       "\"continent\":[\"Asia\",\"Europe\",\"Africa\",\"Americas\",\"Oceania\"],\n",
       "\"pop\":[396.0,360.0,624.0,300.0,24.0]\n",
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   "source": [
    "gggrid([\n",
    "    ggplot(df, aes('continent', 'pop', fill='continent')) + geom_bar() + ggtitle('Default'),\n",
    "    ggplot(df, aes('pop', 'continent', fill='continent')) + geom_bar() + ggtitle('Automatic setting orientation=\"y\"')\n",
    "], ncol=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "91589cbd",
   "metadata": {},
   "source": [
    "#### 2. Marking by `as_discrete()`"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6fa6b5f2",
   "metadata": {},
   "source": [
    "If you're using continuous data for the Y-axis, the plot may be incorrect. Try marking the Y-axis data with the `as_discrete()` function, this will rotate your geom."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c28918fd",
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   "source": [
    "gggrid([\n",
    "    ggplot(albania_df) + geom_bar(aes('lifeExp', 'year'), stat='sum', size=0),\n",
    "    ggplot(albania_df) + geom_bar(aes('lifeExp', as_discrete('year')), stat='sum', size=0)\n",
    "], ncol=2)"
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   "cell_type": "markdown",
   "id": "47a2e97a",
   "metadata": {},
   "source": [
    "#### 3. Other Kinds of Geoms Support Automatic Choosing of Orientation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bbd7db96",
   "metadata": {},
   "source": [
    "Such manipulations with automatic rotation can be done for geoms `geom_boxplot()`, `geom_violin()`, `geom_bar()` and `geom_lollipop()`."
   ]
  },
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   "cell_type": "code",
   "execution_count": 6,
   "id": "593c52c6",
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       "},{\n",
       "\"data\":{\n",
       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"year\",\n",
       "\"y\":\"lifeExp\"\n",
       "},\n",
       "\"data_meta\":{\n",
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       "\"aes\":\"x\",\n",
       "\"annotation\":\"as_discrete\",\n",
       "\"parameters\":{\n",
       "\"label\":\"year\"\n",
       "}\n",
       "}]\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"geom\":\"lollipop\",\n",
       "\"stat\":\"sum\",\n",
       "\"mapping\":{\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"size\":2.0,\n",
       "\"data\":{\n",
       "\"..n..\":[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0],\n",
       "\"year\":[1952.0,1957.0,1962.0,1967.0,1972.0,1977.0,1982.0,1987.0,1992.0,1997.0,2002.0,2007.0],\n",
       "\"lifeExp\":[55.23,59.28,64.82,66.22,67.69,68.93,70.42,72.0,71.581,72.95,75.651,76.423]\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[]\n",
       "},{\n",
       "\"data\":{\n",
       "},\n",
       "\"mapping\":{\n",
       "\"x\":\"lifeExp\",\n",
       "\"y\":\"year\"\n",
       "},\n",
       "\"data_meta\":{\n",
       "\"mapping_annotations\":[{\n",
       "\"aes\":\"y\",\n",
       "\"annotation\":\"as_discrete\",\n",
       "\"parameters\":{\n",
       "\"label\":\"year\"\n",
       "}\n",
       "}]\n",
       "},\n",
       "\"kind\":\"plot\",\n",
       "\"scales\":[],\n",
       "\"layers\":[{\n",
       "\"geom\":\"lollipop\",\n",
       "\"stat\":\"sum\",\n",
       "\"mapping\":{\n",
       "},\n",
       "\"data_meta\":{\n",
       "},\n",
       "\"size\":2.0,\n",
       "\"orientation\":\"y\",\n",
       "\"data\":{\n",
       "\"..n..\":[1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0,1.0],\n",
       "\"year\":[1952.0,1957.0,1962.0,1967.0,1972.0,1977.0,1982.0,1987.0,1992.0,1997.0,2002.0,2007.0],\n",
       "\"lifeExp\":[55.23,59.28,64.82,66.22,67.69,68.93,70.42,72.0,71.581,72.95,75.651,76.423]\n",
       "}\n",
       "}],\n",
       "\"metainfo_list\":[]\n",
       "}]\n",
       "};\n",
       "           var plotContainer = document.getElementById(\"P3cbi2\");\n",
       "           window.letsPlotCall(function() {{\n",
       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();\n",
       "   </script>"
      ],
      "text/plain": [
       "<lets_plot.plot.subplots.SupPlotsSpec at 0x14e51a250>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gggrid([\n",
    "    ggplot(df, aes('continent', 'lifeExp', fill='continent')) + geom_boxplot(),\n",
    "    ggplot(df, aes('lifeExp', 'continent', fill='continent')) + geom_boxplot(),\n",
    "    ggplot(df, aes('continent', 'lifeExp', fill='continent')) + geom_violin(),\n",
    "    ggplot(df, aes('lifeExp', 'continent', fill='continent')) + geom_violin(),\n",
    "    ggplot(albania_df, aes(as_discrete('year'), 'lifeExp')) + geom_lollipop(stat='sum', size=2),\n",
    "    ggplot(albania_df, aes('lifeExp', as_discrete('year'))) + geom_lollipop(stat='sum', size=2),\n",
    "], ncol=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8867feb1",
   "metadata": {},
   "source": [
    "#### 4. `stat='boxplot'`,  `stat='boxplot_outlier'`, `stat_summary()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "13f2b318",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\"scales\":[],\n",
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       "           var plotContainer = document.getElementById(\"b8P8ii\");\n",
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       "               LetsPlot.buildPlotFromProcessedSpecs(plotSpec, -1, -1, plotContainer);\n",
       "           }});\n",
       "       })();\n",
       "   </script>"
      ],
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       "<lets_plot.plot.subplots.SupPlotsSpec at 0x177b6cc10>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gggrid([\n",
    "    ggplot(df, aes('continent', 'lifeExp')) + geom_pointrange(stat='boxplot'),\n",
    "    ggplot(df, aes('lifeExp', 'continent')) + geom_pointrange(stat='boxplot'),\n",
    "    ggplot(df, aes('continent', 'lifeExp')) + geom_pointrange(stat='boxplot_outlier'),\n",
    "    ggplot(df, aes('lifeExp', 'continent')) + geom_pointrange(stat='boxplot_outlier'),\n",
    "    ggplot(df, aes('continent', 'lifeExp')) + stat_summary(),\n",
    "    ggplot(df, aes('lifeExp', 'continent')) + stat_summary()\n",
    "], ncol=2)"
   ]
  }
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