C04.1 Seaborn (Fundamentos).ipynb

{
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"logo.png\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting seaborn\n",
      "  Downloading seaborn-0.11.0-py3-none-any.whl (283 kB)\n",
      "Requirement already satisfied: numpy>=1.15 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from seaborn) (1.19.2)\n",
      "Requirement already satisfied: pandas>=0.23 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from seaborn) (1.1.2)\n",
      "Collecting scipy>=1.0\n",
      "  Downloading scipy-1.5.2-cp37-cp37m-win_amd64.whl (31.2 MB)\n",
      "Requirement already satisfied: matplotlib>=2.2 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from seaborn) (3.3.2)\n",
      "Requirement already satisfied: python-dateutil>=2.7.3 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from pandas>=0.23->seaborn) (2.8.1)\n",
      "Requirement already satisfied: pytz>=2017.2 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from pandas>=0.23->seaborn) (2020.1)\n",
      "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from matplotlib>=2.2->seaborn) (2.4.7)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from matplotlib>=2.2->seaborn) (1.2.0)\n",
      "Requirement already satisfied: certifi>=2020.06.20 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from matplotlib>=2.2->seaborn) (2020.6.20)\n",
      "Requirement already satisfied: cycler>=0.10 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from matplotlib>=2.2->seaborn) (0.10.0)\n",
      "Requirement already satisfied: pillow>=6.2.0 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from matplotlib>=2.2->seaborn) (7.2.0)\n",
      "Requirement already satisfied: six>=1.5 in c:\\users\\hp master\\.conda\\envs\\scidata\\lib\\site-packages (from python-dateutil>=2.7.3->pandas>=0.23->seaborn) (1.14.0)\n",
      "Installing collected packages: scipy, seaborn\n",
      "Successfully installed scipy-1.5.2 seaborn-0.11.0\n"
     ]
    }
   ],
   "source": [
    "!pip install seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SepalLength</th>\n",
       "      <th>SepalWidth</th>\n",
       "      <th>PetalLength</th>\n",
       "      <th>PetalWidth</th>\n",
       "      <th>Class</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>Iris-setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   SepalLength  SepalWidth  PetalLength  PetalWidth        Class\n",
       "0          5.1         3.5          1.4         0.2  Iris-setosa\n",
       "1          4.9         3.0          1.4         0.2  Iris-setosa\n",
       "2          4.7         3.2          1.3         0.2  Iris-setosa\n",
       "3          4.6         3.1          1.5         0.2  Iris-setosa\n",
       "4          5.0         3.6          1.4         0.2  Iris-setosa"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Trabajaremos la tabla iris.\n",
    "#Esta es la manera usual del cargado de datos.\n",
    "\n",
    "iris_ = pd.read_csv(\"C:/Users/hp master/Documents/SciData/Py_CDD/iris_dataset.csv\")\n",
    "iris_.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cargando datos con Seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>sepal_length</th>\n",
       "      <th>sepal_width</th>\n",
       "      <th>petal_length</th>\n",
       "      <th>petal_width</th>\n",
       "      <th>species</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>5.1</td>\n",
       "      <td>3.5</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4.9</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4.7</td>\n",
       "      <td>3.2</td>\n",
       "      <td>1.3</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4.6</td>\n",
       "      <td>3.1</td>\n",
       "      <td>1.5</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>1.4</td>\n",
       "      <td>0.2</td>\n",
       "      <td>setosa</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   sepal_length  sepal_width  petal_length  petal_width species\n",
       "0           5.1          3.5           1.4          0.2  setosa\n",
       "1           4.9          3.0           1.4          0.2  setosa\n",
       "2           4.7          3.2           1.3          0.2  setosa\n",
       "3           4.6          3.1           1.5          0.2  setosa\n",
       "4           5.0          3.6           1.4          0.2  setosa"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "iris = sns.load_dataset(\"iris\")\n",
    "iris.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='sepal_length'>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#violinplot\n",
    "sns.violinplot(x = \"sepal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Estilos en Seaborn: Contextos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Styles: darkgrid, whitegrid, dark, white, and ticks\n",
    "sns.set_style(\"darkgrid\")\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cuadrículas en Seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"white\")\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)\n",
    "sns.despine(right=True, top=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## set_context y set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Contextos disponibles: paper, notebook, talk and poster\n",
    "sns.set_style(\"ticks\")\n",
    "sns.set_context(\"paper\")\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"ticks\")\n",
    "sns.set_context(\"poster\")\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style(\"whitegrid\")\n",
    "sns.set_context(\"poster\", font_scale = .5, rc={\"grid.linewidth\": 0.8})\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#El set context puede recibir varios parámetros de entrada\n",
    "sns.set_context(\"paper\", font_scale=1.8, rc={\"font.size\":5,\"axes.labelsize\":1.0})\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Parámetros por defecto definidos por el usuario\n",
    "sns.set(rc={\"font.size\":6,\"axes.labelsize\":6})\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Reset default params\n",
    "sns.set(palette='Set2')\n",
    "sns.set_context(\"notebook\")\n",
    "sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'font.size': 12.0,\n",
       " 'axes.labelsize': 12.0,\n",
       " 'axes.titlesize': 12.0,\n",
       " 'xtick.labelsize': 11.0,\n",
       " 'ytick.labelsize': 11.0,\n",
       " 'legend.fontsize': 11.0,\n",
       " 'axes.linewidth': 1.25,\n",
       " 'grid.linewidth': 1.0,\n",
       " 'lines.linewidth': 1.5,\n",
       " 'lines.markersize': 6.0,\n",
       " 'patch.linewidth': 1.0,\n",
       " 'xtick.major.width': 1.25,\n",
       " 'ytick.major.width': 1.25,\n",
       " 'xtick.minor.width': 1.0,\n",
       " 'ytick.minor.width': 1.0,\n",
       " 'xtick.major.size': 6.0,\n",
       " 'ytick.major.size': 6.0,\n",
       " 'xtick.minor.size': 4.0,\n",
       " 'ytick.minor.size': 4.0,\n",
       " 'legend.title_fontsize': 12.0}"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sns.plotting_context()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cambiar el tamaño del gráfico in Seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='species', ylabel='petal_length'>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axes = plt.subplots(figsize=(10,4))\n",
    "sns.stripplot(x=\"species\", y=\"petal_length\", data=iris, ax=axes)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1ac64100d48>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x = \"species\", y = \"petal_length\", data=iris, kind=\"bar\", height = 4, aspect=2, legend=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Rotar etiquetas en Seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1ac652c0b88>"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_context(\"poster\",font_scale = .5,)\n",
    "g = sns.catplot(x = \"species\", y = \"petal_length\", data=iris, kind=\"bar\", height=4, aspect=2)\n",
    "g.set_xticklabels(rotation=90)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##  xlim or ylim en Seaborn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x1ac65333748>"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = sns.catplot(x = \"species\", y = \"petal_length\", data=iris, kind=\"bar\", height=4, aspect=2, palette=\"Set2\", legend=False)\n",
    "g.set_xticklabels(rotation=90)\n",
    "g.set(ylim=(0, 12)) # alternative you can use : ax.set_ylim(0,10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Título"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Bar graph for species')"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "b = sns.boxplot(x = \"species\", y = \"petal_length\", data=iris)\n",
    "b.set_title('Bar graph for species')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Referencias\n",
    "\n",
    "- https://seaborn.pydata.org/generated/seaborn.color_palette.html\n",
    "\n",
    "- https://seaborn.pydata.org/tutorial/color_palettes.html"
   ]
  }
 ],
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