matplotlib_cours.ipynb 1.51 MB
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{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "631fea4f-3022-471d-97c0-0888a78d2bea",
   "metadata": {},
   "outputs": [],
   "source": [
    "#%matplotlib widget\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7425925e-b520-4d87-bf6b-3152f60c19ca",
   "metadata": {},
   "source": [
    "# <center>**Cours**</center>\n",
    "\n",
    "<img src=\"./images/logo2_matplotlib.svg\" style=\"margin:0 auto;\">\n",
    "<div style=\"text-align:center\">\n",
    "    Bertrand Néron\n",
    "    <br>\n",
    "    <a src=\" https://research.pasteur.fr/en/team/bioinformatics-and-biostatistics-hub/\">Bioinformatics and Biostatistiqucs HUB</a>\n",
    "    <br />\n",
    "    © Institut Pasteur, 2021\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9f7ef4ec-9a15-4fbb-8c91-7784d6838499",
   "metadata": {},
   "source": [
    "# Motivation"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "90fe735b-9570-4b4b-8f1f-e6116de7b4de",
   "metadata": {},
   "source": [
    "# Installation\n",
    "\n",
    "* open a shell \n",
    "* activate the virtualenv (*source <prefix>/bin/activate*)\n",
    "and type:\n",
    "    \n",
    "```\n",
    "pip install matplotlib\n",
    "```\n",
    "\n",
    "*You may need root permission if you do not use a virtualenv.*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d2fcbe0d-6c5d-4cd5-a7cb-1de3c6168a1d",
   "metadata": {},
   "source": [
    "# Using matplotlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "abbbacce-63d9-435f-bb08-f54ff1c9143a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import matplotlib\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ee76e2e5-e737-451f-bd60-055f41923b93",
   "metadata": {},
   "source": [
    "# Concepts and Terminology"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8aa36c70-6bd7-4264-aa57-f83781c1c108",
   "metadata": {},
   "source": [
    "<img src=\"img/mplt_concept.png\"  width=\"600px\">\n",
    "\n",
    "> https://matplotlib.org/stable/tutorials/introductory/usage.html#parts-of-a-figure"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2fa77d5e-74ae-435f-b28a-a9dd8880dc5c",
   "metadata": {},
   "source": [
    "### Figure\n",
    "\n",
    "The figure is like a canvas where all you Axes (plots) where drawn.\n",
    "A figuer acn containes several Axes (plots) but to be useful should have at least one.\n",
    "The easiest way to create a new figure is with pyplot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "99a6eba9-6e9f-4697-9778-143163d2280a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()  # an empty figure with no axes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b16c62d1-dd07-488a-a018-3a81b7a2860d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax_lst = plt.subplots(2, 2)  # a figure with a 2x2 grid of Axes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bc55f943-cca6-4522-aec2-ca766995f8db",
   "metadata": {},
   "source": [
    "### Axes\n",
    "\n",
    "This is what you think of as ‘a plot’.\n",
    "* The Axes contains two (or three in the case of 3D) **Axis** objects\n",
    "* Each Axes has a title \n",
    "* Each Axes can contain a legend \n",
    "\n",
    "### Axis\n",
    "\n",
    "These are the number-line-like objects.\n",
    "\n",
    "### Labels\n",
    "\n",
    "This the \"legend\" of Axis. There is 2 labels for 2D plots the ``x_label`` and ``y_label``\n",
    "\n",
    "### Ticks\n",
    "\n",
    "The ticks arethe marks on the axis and ticklabels (strings labeling the ticks).\n",
    "the is two kind of ticks, major and minor ticks.\n",
    "by default they are automaticaly generated by the axis.\n",
    "but they can be configured."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bf8fce4d-0271-4b5d-8c7a-f2d2a310aed8",
   "metadata": {},
   "source": [
    "# Coding styles\n",
    "\n",
    "When viewing matplotlib code, you will find different coding styles and usage patterns. \n",
    "* matlab style\n",
    "* object-oriented style\n",
    "\n",
    "These styles are perfectly valid and have their pros and cons.\n",
    "The only caveat is to avoid mixing the coding styles for your own code.\n",
    "\n",
    "matlab style is fine for small interface like in notebook,\n",
    "whereas to have even more control in application embeding matplotlib GUI the pyplot level may be dropped completely, leaving a purely object-oriented approach."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a717bf5e-194f-43a5-8b8c-46e04a129236",
   "metadata": {},
   "source": [
    "## pyplot functional style (*aka matlab style*)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "c61e6d40-84f4-4610-91d7-597a031b307f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'volts')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot([1, 2, 3])\n",
    "plt.title('hi mom')\n",
    "plt.grid(True)\n",
    "plt.xlabel('time')\n",
    "plt.ylabel('volts')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de91852f-663e-4156-b2fb-c4892333825c",
   "metadata": {},
   "source": [
    "## Object oriented style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "85e712cb-b2d1-4f4b-8d47-8ad388a745b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'volts')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots() # by default 1 row, 1 column, 1 axe\n",
    "ax.plot([1, 2, 3])\n",
    "ax.set_title('hi mom')\n",
    "ax.grid(True)\n",
    "ax.set_xlabel('time')\n",
    "ax.set_ylabel('volts')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "524e79fd-17b5-4d19-b417-eb46428b8e87",
   "metadata": {},
   "source": [
    "In this notebook we will use the *pyplot functional coding style*"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "47fb81f9-5bfd-4a97-b603-d6fa06b1084a",
   "metadata": {},
   "source": [
    "## Dive into matplotlib\n",
    "\n",
    "Now we are going to learn to use some compounds.\n",
    "To the demos belows we will need of *numpy* and *pandas* packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "57e41359-cf96-4bf3-ac6c-f7778bf46b43",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b7dfc1c5-8602-4d8e-8f75-4994b8508b5f",
   "metadata": {},
   "source": [
    "# Plot\n",
    "\n",
    "> https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3f3ce2b1-198f-41a5-80f1-fde2d7272bbd",
   "metadata": {},
   "source": [
    "## One variable"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "11b3d419-688e-47fc-882e-4cc5167283e5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        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>City</th>\n",
       "      <th>Year</th>\n",
       "      <th>Tmp</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Barcelona</td>\n",
       "      <td>1995</td>\n",
       "      <td>62.019178</td>\n",
       "      <td>9.569756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Barcelona</td>\n",
       "      <td>1996</td>\n",
       "      <td>61.125956</td>\n",
       "      <td>9.420765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Barcelona</td>\n",
       "      <td>1997</td>\n",
       "      <td>62.612329</td>\n",
       "      <td>9.827235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Barcelona</td>\n",
       "      <td>1998</td>\n",
       "      <td>60.273973</td>\n",
       "      <td>19.750126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Barcelona</td>\n",
       "      <td>1999</td>\n",
       "      <td>61.204658</td>\n",
       "      <td>13.904526</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>Rome</td>\n",
       "      <td>2016</td>\n",
       "      <td>61.185246</td>\n",
       "      <td>15.914193</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>Rome</td>\n",
       "      <td>2017</td>\n",
       "      <td>61.377808</td>\n",
       "      <td>11.916595</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>Rome</td>\n",
       "      <td>2018</td>\n",
       "      <td>60.821370</td>\n",
       "      <td>20.327932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>Rome</td>\n",
       "      <td>2019</td>\n",
       "      <td>59.215068</td>\n",
       "      <td>23.514064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>Rome</td>\n",
       "      <td>2020</td>\n",
       "      <td>52.676119</td>\n",
       "      <td>6.224294</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>182 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          City  Year        Tmp        std\n",
       "0    Barcelona  1995  62.019178   9.569756\n",
       "1    Barcelona  1996  61.125956   9.420765\n",
       "2    Barcelona  1997  62.612329   9.827235\n",
       "3    Barcelona  1998  60.273973  19.750126\n",
       "4    Barcelona  1999  61.204658  13.904526\n",
       "..         ...   ...        ...        ...\n",
       "177       Rome  2016  61.185246  15.914193\n",
       "178       Rome  2017  61.377808  11.916595\n",
       "179       Rome  2018  60.821370  20.327932\n",
       "180       Rome  2019  59.215068  23.514064\n",
       "181       Rome  2020  52.676119   6.224294\n",
       "\n",
       "[182 rows x 4 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp = pd.read_csv(\"../data/fr_sp_it_temp.tsv\", sep=\"\\t\", header=0, index_col=0)\n",
    "temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "99d54202-c825-4dbc-8c25-b7631cb814e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        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>City</th>\n",
       "      <th>Year</th>\n",
       "      <th>Tmp</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>Paris</td>\n",
       "      <td>1995</td>\n",
       "      <td>53.742192</td>\n",
       "      <td>20.406326</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>Paris</td>\n",
       "      <td>1996</td>\n",
       "      <td>52.293169</td>\n",
       "      <td>15.207325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Paris</td>\n",
       "      <td>1997</td>\n",
       "      <td>55.580000</td>\n",
       "      <td>12.745185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>Paris</td>\n",
       "      <td>1998</td>\n",
       "      <td>50.317534</td>\n",
       "      <td>27.794295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Paris</td>\n",
       "      <td>1999</td>\n",
       "      <td>54.565753</td>\n",
       "      <td>13.990209</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2000</td>\n",
       "      <td>54.337705</td>\n",
       "      <td>10.345685</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2001</td>\n",
       "      <td>53.944932</td>\n",
       "      <td>12.074808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2002</td>\n",
       "      <td>52.743014</td>\n",
       "      <td>18.722075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2003</td>\n",
       "      <td>54.562192</td>\n",
       "      <td>13.721165</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2004</td>\n",
       "      <td>53.585246</td>\n",
       "      <td>11.761756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2005</td>\n",
       "      <td>53.407671</td>\n",
       "      <td>14.983372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2006</td>\n",
       "      <td>54.199726</td>\n",
       "      <td>13.030266</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2007</td>\n",
       "      <td>53.572055</td>\n",
       "      <td>12.962494</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2008</td>\n",
       "      <td>52.381694</td>\n",
       "      <td>15.655254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2009</td>\n",
       "      <td>53.061096</td>\n",
       "      <td>14.640168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2010</td>\n",
       "      <td>51.648219</td>\n",
       "      <td>13.601742</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2011</td>\n",
       "      <td>55.001918</td>\n",
       "      <td>10.339226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2012</td>\n",
       "      <td>53.256557</td>\n",
       "      <td>11.453752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2013</td>\n",
       "      <td>52.088493</td>\n",
       "      <td>14.922241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2014</td>\n",
       "      <td>53.650411</td>\n",
       "      <td>11.968851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2015</td>\n",
       "      <td>53.434973</td>\n",
       "      <td>15.680118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2016</td>\n",
       "      <td>51.122951</td>\n",
       "      <td>21.198085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2017</td>\n",
       "      <td>54.367945</td>\n",
       "      <td>11.949198</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2018</td>\n",
       "      <td>45.773151</td>\n",
       "      <td>36.811172</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2019</td>\n",
       "      <td>52.208219</td>\n",
       "      <td>22.722815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Paris</td>\n",
       "      <td>2020</td>\n",
       "      <td>49.320149</td>\n",
       "      <td>7.458857</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      City  Year        Tmp        std\n",
       "130  Paris  1995  53.742192  20.406326\n",
       "131  Paris  1996  52.293169  15.207325\n",
       "132  Paris  1997  55.580000  12.745185\n",
       "133  Paris  1998  50.317534  27.794295\n",
       "134  Paris  1999  54.565753  13.990209\n",
       "135  Paris  2000  54.337705  10.345685\n",
       "136  Paris  2001  53.944932  12.074808\n",
       "137  Paris  2002  52.743014  18.722075\n",
       "138  Paris  2003  54.562192  13.721165\n",
       "139  Paris  2004  53.585246  11.761756\n",
       "140  Paris  2005  53.407671  14.983372\n",
       "141  Paris  2006  54.199726  13.030266\n",
       "142  Paris  2007  53.572055  12.962494\n",
       "143  Paris  2008  52.381694  15.655254\n",
       "144  Paris  2009  53.061096  14.640168\n",
       "145  Paris  2010  51.648219  13.601742\n",
       "146  Paris  2011  55.001918  10.339226\n",
       "147  Paris  2012  53.256557  11.453752\n",
       "148  Paris  2013  52.088493  14.922241\n",
       "149  Paris  2014  53.650411  11.968851\n",
       "150  Paris  2015  53.434973  15.680118\n",
       "151  Paris  2016  51.122951  21.198085\n",
       "152  Paris  2017  54.367945  11.949198\n",
       "153  Paris  2018  45.773151  36.811172\n",
       "154  Paris  2019  52.208219  22.722815\n",
       "155  Paris  2020  49.320149   7.458857"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "paris = temp[temp.City == 'Paris']\n",
    "paris"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "b13ce1af-fcba-41a4-8270-15b18bbe6f9b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8a5a144be0>]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(paris['Tmp'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ebb4469b-dd16-4047-8833-f9c01b234f46",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "ae6a2a70-d851-49a1-a8dc-3c73d6041b51",
   "metadata": {},
   "source": [
    "## Two variables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f9d20f59-c49b-442a-a882-c899590ce5ec",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8a5a07c7c0>]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(paris['Year'],paris['Tmp'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "bb79414d-cce0-4fa3-9ae1-4cbf55207e66",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8a59fe71f0>]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(paris['Year'],paris['Tmp'],\n",
    "         marker='o')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "6e5b03a8-1502-4ecc-8a0c-623a4bc0932e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8a59fc0cd0>]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXAAAAD7CAYAAABzGc+QAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjQuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/MnkTPAAAACXBIWXMAAAsTAAALEwEAmpwYAAATMUlEQVR4nO3df6zddX3H8eebAtoxsLDedtJSi1PqTFwFr4QIkzFjq8hso5kzUYeia2bMxsws0qn/uBirLM6ZLJsdg2AmUxPbynQC3TpiFofj1oIFoQikblzQgtLJsiq0vPfH+V45vd57zzn3nm/P93PO85Hc3O/5nB98Ppx+X/f7fX8/3+83MhNJUnlOGHQHJEnzY4BLUqEMcEkqlAEuSYUywCWpUAa4JBWqqwCPiAMRsS8i7oyIibb2P4qI+yLinoj4ZH3dlCRNd2IPr70kMx+fehARlwAbgLWZ+bOIWNb33kmSZtVLgE/3XmBrZv4MIDMPdnrD0qVLc/Xq1Qv4T0rS6NmzZ8/jmTk2vb3bAE/g1ohI4LOZuQ04B/jNiPgY8FPgA5l5x1wfsnr1aiYmJuZ6iSRpmoj4/kzt3Qb4RZk5WZVJdkXEfdV7zwAuAF4JfCkiXpjTzs2PiE3AJoBVq1bNt/+SpGm6OoiZmZPV74PADuB84GFge7b8J/AMsHSG927LzPHMHB8b+4U9AEnSPHUM8Ig4JSJOnVoG1gF3AzuBS6r2c4CTgcdn+RhJUp91U0JZDuyIiKnX35iZN0fEycB1EXE38BRw+fTyiSSpPh0DPDMfAtbO0P4U8PY6OiVJ6mwh0wiHxs69k1xzy34eOXSYM5csZvP6NWw8d8WguyVJcxr5AN+5d5It2/dx+OmjAEweOsyW7fsADHFJjTby10K55pb9Pw/vKYefPso1t+wfUI8kqTsjH+CPHDrcU7skNcXIB/iZSxb31C5JTTHyAb55/RoWn7TomLbFJy1i8/o1A+qRJHVn5A9iTh2odBaKpNKMfIBDK8QNbEmlGfkSiiSVygCXpEIZ4JJUKANckgrlQUypEF6zR9MZ4FIBvGaPZmIJRSqA1+zRTAxwqQBes0czMcClAnjNHs3EAJcK4DV7NBMPYkoF8Jo9mokBLhXCa/ZoOksoklQot8CPg2E4AWMYxiANGwO8ZsNwAsYwjEEaRpZQajYMJ2AMwxikYWSA12wYTsAYhjFIw8gSSs3OXLKYyRmCbq4TMJpWb57PGKRBaNq6Uze3wGvW6wkYU/XmyUOHSZ6tN+/cO3kcejszTyJRCZq47tTNAK/ZxnNX8PE3vYwVSxYTwIoli/n4m14261ZBE+vNvY5BGoQmrjt1s4RyHPRyAkZT681NO4lk1HaV1VlT1506uQXeMF60qLNR3FVWZ6O47hjgDWO9ubNR3FVWZ6O47lhCaRgvWtTZKO4qq7NRXHe6CvCIOAA8CRwFjmTmeNtzfwr8BTCWmY/X0clR07R6c9M4rVGzGbV1p5cSyiWZ+fJp4X0WsA74r773TF3buXeSC7fu5uyrv8aFW3cPfS14FHeVpZkstITyl8BVwFf60BfNwyhep2QUd5WlmXQb4AncGhEJfDYzt0XEBmAyM++KiFnfGBGbgE0Aq1atWmh/Nc1cB/SGOdBGbVdZmkm3AX5RZk5GxDJgV0TcB/wZrfLJnDJzG7ANYHx8POfdU83IA3rS6OoqwDNzsvp9MCJ2ABcDZwNTW98rgW9HxPmZ+YN+dtATNubmAT1pdHU8iBkRp0TEqVPLtLa678jMZZm5OjNXAw8D59UR3p6wMTcP6Emjq5st8OXAjmpL+0Tgxsy8udZeVUa1vtsLD+hpUNw7HryOAZ6ZDwFrO7xmdb861M76bneaeEDPlXu4jeLspyZq9Kn0o3htg2HQxNLXqM2Vr5uXM2iGRge49d0yNW3lbuIflNK5d9wMjQ5wr0Ndpqat3E37gzIM5rt37J5QfzX+YlZNrO9qbk27jVzT/qAMg83r1xxTA4fOe8fWzfuv0VvgKlPTbiPnsZT+m8/esXtC/df4LXCVp9epjXVPF53P1qI663Xv2D2h/jPAVYsm3UZuVOfKN20qp2cN958BroE7Hiv2qB1LaWK92T2h/rMGroFzumj/NbHe7Kyy/nMLXAM3qiWOOjW13jxqe0J1M8DVCMOwYjep5my9eTRYQpH6oGlne1qWGg0GuNQHTas5W28eDZZQpD5oYs15GMpSmptb4FIfeLanBsEAl/rAmrMGwRLKCGrSbIlh4VRIDYIBPmKaeIbesLDmrOPNEsqIadpsCUnzZ4CPmCbOlpA0Pwb4iHG2hDQ8DPAR42wJaXh4EHPEOFtCGh4G+AhytoQ0HAxwaQbOlVcJhi7AXfG0UM6VVymG6iBm0y7pqTI5V16lGKot8Lrvbq7R4Fx5zaZpe/hDtQXuiqd+cK68ZtLEPfyhCnBXPPWDc+U1kyaW1oYqwF3x1A+jejebnXsnuXDrbs6++mtcuHW3x46maeIeflc18Ig4ADwJHAWOZOZ4RFwD/A7wFPAg8K7MPFRTP7viSSrql1GbK+/Mm86aeKPoXg5iXpKZj7c93gVsycwjEfEJYAvwwb72bh5GbcWT+sEJAJ1tXr/mmD9yMPg9/HmXUDLz1sw8Uj28HVjZny5JOt6aWB5omiaW1rrdAk/g1ohI4LOZuW3a81cAX5zpjRGxCdgEsGrVqvn2U1KNmlgeaKKm7eF3uwV+UWaeB7weeF9EvHrqiYj4EHAE+PxMb8zMbZk5npnjY2NjC+6wpP5zAkCZutoCz8zJ6vfBiNgBnA98IyLeCVwGvCYzs7ZeSqqVEwDK1DHAI+IU4ITMfLJaXgd8NCJeB1wFXJyZ/1dzPyXVrGnlAXXWzRb4cmBHREy9/sbMvDkiHgCeA+yqnrs9M/+wtp5KQ6Zpp2WrPB0DPDMfAtbO0P6iWnokjQDnXasfhupMTKkUTTwtW+UxwKUBcN61+sEAlwbAC6+pHwxwaQCcd61+GKobOkilcN61+sEAlwbEeddaKEsoklQoA1ySCmWAS1KhrIFLaiwvNzA3A1xSI3m5gc4soUhqJC830JkBLqmRvNxAZwa4pEbycgOdGeCSGsnLDXTmQUxJjeTlBjozwCU1lpcbmJslFEkqlAEuSYUywCWpUAa4JBXKAJekQhngklQoA1ySCmWAS1KhPJFnHrxGsaQmMMB75DWKJTWFJZQeeY1iSU1hgPfIaxRLagoDvEdeo1hSUxjgPfIaxZKaoquDmBFxAHgSOAocyczxiDgD+CKwGjgAvCUzn6inm83hNYolNUVkZucXtQJ8PDMfb2v7JPDjzNwaEVcDp2fmB+f6nPHx8ZyYmFhglyVptETEnswcn96+kBLKBuCGavkGYOMCPkuS1KNuAzyBWyNiT0RsqtqWZ+aj1fIPgOV9750kaVbdnshzUWZORsQyYFdE3Nf+ZGZmRMxYi6kCfxPAqlWrFtRZSdKzutoCz8zJ6vdBYAdwPvDDiHg+QPX74Czv3ZaZ45k5PjY21p9eS5I6B3hEnBIRp04tA+uAu4GbgMurl10OfKWuTkqSflE3JZTlwI6ImHr9jZl5c0TcAXwpIt4NfB94S33dlCRN1zHAM/MhYO0M7T8CXlNHpyRJnXkmpiQVygCXpEIZ4JJUKANckgplgEtSobylmiTVqM576BrgklSTuu+hawlFkmpS9z10DXBJqknd99A1wCWpJnXfQ9cAl6Sa1H0PXQ9iSlJN6r6HrgEuSTXaeO6K2m56bglFkgplgEtSoQxwSSqUAS5JhTLAJalQBrgkFcoAl6RCGeCSVCgDXJIKZYBLUqEMcEkqlAEuSYUywCWpUAa4JBXKAJekQhngklQoA1ySCmWAS1Khug7wiFgUEXsj4qvV49dExLcj4s6I+PeIeFF93ZQkTdfLFviVwL1tj/8GeFtmvhy4EfhwH/slSeqgqwCPiJXAG4Br25oTOK1afh7wSH+7JkmaS7d3pf80cBVwalvbe4B/jojDwE+AC/rbNUnSXDpugUfEZcDBzNwz7an3A5dm5krgeuBTs7x/U0RMRMTEY489tuAOS5JauimhXAi8MSIOAF8AfjsivgaszcxvVa/5IvCqmd6cmdsyczwzx8fGxvrRZ0kSXQR4Zm7JzJWZuRp4K7Ab2AA8LyLOqV72Wo49wClJqlm3NfBjZOaRiPgD4MsR8QzwBHBFX3smSZpTTwGembcBt1XLO4Ad/e+SJKkbnokpSYUywCWpUAa4JBXKAJekQhngklQoA1ySCmWAS1KhDHBJKpQBLkmFMsAlqVAGuCQVygCXpEIZ4JJUKANckgplgEtSoQxwSSqUAS5JhTLAJalQBrgkFcoAl6RCGeCSVCgDXJIKZYBLUqEMcEkqlAEuSYUywCWpUAa4JBXKAJekQhngklQoA1ySCmWAS1KhDHBJKlTXAR4RiyJib0R8tXocEfGxiLg/Iu6NiD+ur5uSpOlO7OG1VwL3AqdVj98JnAW8JDOfiYhlfe6bJGkOXW2BR8RK4A3AtW3N7wU+mpnPAGTmwf53T5I0m25LKJ8GrgKeaWv7NeD3ImIiIr4eES+e6Y0Rsal6zcRjjz22sN5Kkn6uY4BHxGXAwczcM+2p5wA/zcxx4O+A62Z6f2Zuy8zxzBwfGxtbcIclSS3d1MAvBN4YEZcCzwVOi4h/AB4Gtlev2QFcX08XJakeO/dOcs0t+3nk0GHOXLKYzevXsPHcFYPuVtc6boFn5pbMXJmZq4G3Arsz8+3ATuCS6mUXA/fX1UlJ6redeyfZsn0fk4cOk8DkocNs2b6PnXsnB921ri1kHvhW4M0RsQ/4OPCe/nRJkup3zS37Ofz00WPaDj99lGtu2T+gHvWul2mEZOZtwG3V8iFaM1MkqTiPHDrcU3sTeSampJF05pLFPbU3kQEuaSRtXr+GxSctOqZt8UmL2Lx+zYB61LueSiiSNCymZpuUPAvFAJc0sjaeu6KowJ7OEookFcoAl6RCGeCSVCgDXJIKZYBLUqEiM4/ffyziMeD783z7UuDxPnanBI55NDjm0bCQMb8gM3/hcq7HNcAXIiImqkvXjgzHPBoc82ioY8yWUCSpUAa4JBWqpADfNugODIBjHg2OeTT0fczF1MAlSccqaQtcktRmoAEeEddFxMGIuLutbW1E/EdE7IuIf4qI06r2kyPi+qr9roj4rbb33BYR+yPizupn2fEfTWcRcVZE/FtEfDci7omIK6v2MyJiV0R8r/p9etUeEfGZiHggIr4TEee1fdbl1eu/FxGXD2pMnfR5zEfbvuObBjWmTuYx5pdU/+Z/FhEfmPZZr6v+bT8QEVcPYjzd6POYD1Tr+Z0RMTGI8XRjHmN+W/Vvel9EfDMi1rZ91vy+58wc2A/wauA84O62tjuAi6vlK4A/r5bfB1xfLS8D9gAnVI9vA8YHOZYux/t84Lxq+VRa9xF9KfBJ4Oqq/WrgE9XypcDXgQAuAL5VtZ8BPFT9Pr1aPn3Q46tzzNVz/zvo8dQ05mXAK4GPAR9o+5xFwIPAC4GTgbuAlw56fHWOuXruALB00GOqYcyvmlpPgde3rc/z/p4HugWemd8Afjyt+RzgG9XyLuDN1fJLgd3V+w4Ch4Ci5pFm5qOZ+e1q+UngXmAFsAG4oXrZDcDGankD8LlsuR1YEhHPB9YDuzLzx5n5BK3/T687fiPpXh/HXIxex5yZBzPzDuDpaR91PvBAZj6UmU8BX6g+o3H6OOZizGPM36zWV4DbgZXV8ry/5ybWwO/h2c7/LnBWtXwX8MaIODEizgZe0fYcwPXVLtdHIiKOX3fnJyJWA+cC3wKWZ+aj1VM/AJZXyyuA/25728NV22ztjbbAMQM8NyImIuL2iNhYf48Xrssxz2aYv+e5JHBrROyJiE319LK/5jHmd9Pa04QFfM9NvKHDFcBnIuIjwE3AU1X7dcCvAxO0Tsf/JjB1S+m3ZeZkRJwKfBl4B/C549rrHkTEL9Pq559k5k/a/95kZkbE0E0N6tOYX1B9zy8EdkfEvsx8sKYuL5jf87zHfFH1PS8DdkXEfdXeeiP1OuaIuIRWgF+00P9247bAM/O+zFyXma8A/pFWbYjMPJKZ78/Ml2fmBmAJrZoTmTlZ/X4SuJHWLkkjRcRJtL7sz2fm9qr5h1Nlgur3wap9kmP3MlZWbbO1N1Kfxtz+PT9E67jHubV3fp56HPNshvl7nlXb93wQ2MHwrM9ExG8A1wIbMvNHVfO8v+fGBXj1V5eIOAH4MPC31eNfiohTquXXAkcy87tVSWVp1X4ScBlw94wfPmBVaefvgXsz81NtT90ETM0kuRz4Slv770fLBcD/VLtmtwDrIuL06gj3uqqtcfo15mqsz6k+cylwIfDd4zKIHs1jzLO5A3hxRJwdEScDb60+o3H6NeaIOKXak6Za39cxJOtzRKwCtgPvyMz7214//++530dme/mhtYX9KK0DGQ/T2q24ktaW9f3AVp492Wg1sJ/WgYJ/obU7DXAKrRkp36FVP/8rYNEgxzXHeC+iVd/7DnBn9XMp8CvAvwLfq8Z2RvX6AP6a1l7IPtpm2tAqNT1Q/bxr0GOre8y0juDvo3UsZB/w7kGPrY9j/tXq3/9PaB2cfxg4rXru0mpdeBD40KDHVveYac3EuKv6uWfIxnwt8ETbayfaPmte37NnYkpSoRpXQpEkdccAl6RCGeCSVCgDXJIKZYBLUqEMcEkqlAEuSYUywCWpUP8PuBv7Z2ufBecAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(paris['Year'],paris['Tmp'],\n",
    "         marker='o',\n",
    "        linestyle=''\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "5942e686-e65c-40d4-a58e-54828f4186b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8a59f25c40>]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(paris['Year'],paris['Tmp'],\n",
    "         marker='s',\n",
    "         color='red',\n",
    "        linestyle='--'\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "540467bb-46ff-444c-b575-6abe145a20b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f8a59e97160>]"
      ]
     },
     "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": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(paris['Year'],paris['Tmp'],\n",
    "         marker='v',\n",
    "         color='brown',\n",
    "        linestyle='-.'\n",
    "        )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ece2ad49-59c4-4f40-b65d-bd8e228598b8",
   "metadata": {},
   "source": [
    "all available linestyles, markers and colors are described in https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.plot.html"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "08767e1e-c7e1-48d6-908a-72d91fafb7d2",
   "metadata": {},
   "source": [
    "## Several plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "bac9a02e-8301-4885-b34a-8d91fff234e4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8a59e71b20>"
      ]
     },
     "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": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bdx = temp[temp.City == 'Bordeaux']\n",
    "plt.plot(paris['Year'], paris['Tmp'], label='Paris')\n",
    "plt.plot(bdx['Year'], bdx['Tmp'], label='Bordeaux')\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "7e9383b8-3ace-4042-a0f5-91071e56257b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Average Temperature')"
      ]
     },
     "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": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for city, df in temp.groupby('City'):\n",
    "    plt.plot(df['Year'], df['Tmp'], label=city)\n",
    "\n",
    "plt.legend(ncol=2)\n",
    "plt.xlabel(\"Year\")\n",
    "plt.ylabel(\"Tp in °F\")\n",
    "plt.title(\"Average Temperature\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "70924d07-7d98-4f8d-8bcf-de595c44be3e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8a5851e6a0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "paris_max = paris['Tmp'] + paris['std']\n",
    "paris_min = paris['Tmp'] - paris['std']\n",
    "\n",
    "plt.plot(paris['Year'], paris['Tmp'], label= \"Paris\" )\n",
    "\n",
    "plt.fill_between(paris['Year'], \n",
    "         paris_max, \n",
    "         y2=paris_min,\n",
    "         alpha=0.5        \n",
    "        )\n",
    "\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aa620f3b-ced6-4ed3-9f4c-73abbdc86841",
   "metadata": {},
   "source": [
    "## xlabel and ylabel\n",
    "\n",
    "> https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.xlabel.html\n",
    "> https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.ylabel.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d241268f-7265-424c-9d5c-aa554cb2aa16",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8a59d67b20>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "paris_max = paris['Tmp'] + paris['std']\n",
    "paris_min = paris['Tmp'] - paris['std']\n",
    "\n",
    "plt.plot(paris['Year'], paris['Tmp'], label= \"Paris\" )\n",
    "\n",
    "plt.fill_between(paris['Year'], \n",
    "         paris_max, \n",
    "         y2=paris_min,\n",
    "         color=\"orange\",        \n",
    "         alpha=0.5        \n",
    "        )\n",
    "plt.xlabel('Year')\n",
    "plt.ylabel('Temp in °F')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "48c27e9b-6a4c-4751-8d65-2b18ebc4bce6",
   "metadata": {},
   "source": [
    "## Legend\n",
    "\n",
    "> https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.legend.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "6c674b4b-0107-44ab-92f0-30800cce309e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f8a58482640>"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],