WorldClim - Projected Climatologies GRAPHS_21.03.10.ipynb

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    "# WorldClim data : Historical & future Climatologies (1970-2100) - GRAPHS\n",
    "## 4 SSP scenarios and 9 Global Climatic Models (Precipitation or Temperature)\n",
    "- Data: https://www.worldclim.org/data/index.html\n",
    "- author: Loïc Duffar https://github.com/loicduffar\n",
    "\n",
    "This python notebook uses data from the wordclim web site to compute the evolution of future precipitation on a given watershed (average of the pixels inside the polygon). The ouputs are stored in an excel file.\n",
    "\n",
    "NOTA: The code can handle precipitation or average temperature\n",
    "\n",
    "### How to PROCEED ?\n",
    "The data files must be divided into different sub-folders:\n",
    "- a folder containing the 12 tif files of historical monthly interannual averages (1 file per month of the year)\n",
    "- a folder with 4 sub-folders for the various future periods (1921-1940, 1961-1981, 1981-2100). Each folder contains 4 tif files for each model (and each file contains 12 bands for the the different months).\n",
    "\n",
    "Then run cells in order:\n",
    "- <a href=#section01>1)</a> Historical Climatology 1970-2000 (interannual monthly mean)\n",
    "- <a href=#section02>2)</a> Future Climatology\n",
    "- <a href=#section03>3)</a> Multi index by Model, Scenario and Period\n",
    "- <a href=#section04>4)</a> Concatenate historical and future climatology in a single dataframe\n",
    "- <a href=#section05>5)</a> Plot annual evolution of annual climatology in future, according to all SSP scenarios and all GCM\n",
    "- <a href=#section06>6)</a> Plot future evolution for each month, according to 4 SSP scenarios and 9 GCMs\n",
    "- <a href=#section07>7)</a> Store statistics in a dataframe\n",
    "- <a href=#section08>8)</a> Plot montly projections (all SSP scenarios and GCMs)\n",
    "- <a href=#section09>9)</a> Store all outputs in an excel file"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  <a name=section01></a>1) Historical Climatology 1970-2000\n",
    "Customize the code below with...\n",
    "- folder path for historical tif files (it can be precipitation or temperature), \n",
    "- folder path for output files, \n",
    "- path of the polygon file (folder and file name) for the calculation of the mean water depth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Process started. Please wait the ending message ... \n",
      "Process completed in  0:00:02.509809\n"
     ]
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>Annual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1970-2000 Mean</th>\n",
       "      <td>19.4</td>\n",
       "      <td>19.8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.2</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.6</td>\n",
       "      <td>22.7</td>\n",
       "      <td>22.5</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>19.8</td>\n",
       "      <td>21.3</td>\n",
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       "                   1     2     3     4     5     6     7     8     9    10  \\\n",
       "1970-2000 Mean  19.4  19.8  20.7  21.2  21.8  22.2  22.6  22.7  22.5  22.0   \n",
       "\n",
       "                  11    12  Annual  \n",
       "1970-2000 Mean  20.9  19.8    21.3  "
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Created on March 2021\n",
    "@author: Loïc Duffar\n",
    "\"\"\"\n",
    "import os\n",
    "import glob2\n",
    "import rasterstats\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import datetime\n",
    "\n",
    "# +++++++ Customization\n",
    "variable= 'Temperature'\n",
    "file_prefix= 'wc2.1_5m_' # e.g. 'wc2.1_5m_'\n",
    "# ....... Folder with Historical tif files (FOLDER WITHOUT \"\\\" CHARACTER AT THE END !!!)\n",
    "fld_in = r'X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat Monde\\WorldClim\\Historical Climatologies 1970-2000\\wc2.1_5m'\n",
    "# ....... folder path for the output files (WITHOUT \"\\\" CHARACTER AT THE END !!!)\n",
    "fld_out = r'C:\\Users\\duffar\\Documents\\A\\ETUDES\\2021 Yaque del Sur'\n",
    "# ....... Polygon file (shape file) for plotting and average computation (path INCLUDING folder)\n",
    "polygon_file = r'C:\\Users\\DUFFAR\\Documents\\A\\ETUDES\\2021 Yaque del Sur\\Carto\\Subcuencas_YaqueSur.shp'\n",
    "historical_period = '1970-2000'\n",
    "\n",
    "# +++++++ initialisation\n",
    "annual_label= 'Annual'\n",
    "baseline_label= historical_period + ' Mean'\n",
    "if variable.upper()== 'PRECIPITATION':\n",
    "    file_prefix = file_prefix + 'prec'\n",
    "    unit= 'mm'\n",
    "elif variable.upper()== 'TEMPERATURE':\n",
    "    file_prefix = file_prefix + 't'\n",
    "    unit= '°C'\n",
    "        \n",
    "# +++++++ Polygon averaged\n",
    "print('Process started. Please wait the ending message ... ')\n",
    "start= datetime.datetime.now()# Start Timer\n",
    "\n",
    "results = []\n",
    "# Loop on raster files (1 file per month)\n",
    "\n",
    "for month in range(1, 13):\n",
    "    if variable.upper()== 'PRECIPITATION':\n",
    "        file = os.path.join(fld_in, file_prefix + '_' + \"{:0>2d}\".format(month) + '.tif')\n",
    "    elif variable.upper()== 'TEMPERATURE':\n",
    "        file = os.path.join(fld_in, file_prefix + 'avg_' + \"{:0>2d}\".format(month) + '.tif')   \n",
    "    res = rasterstats.zonal_stats(polygon_file, file, stats=['mean'])\n",
    "    results.append(round(res[0]['mean'], 1))\n",
    "\n",
    "df = pd.Series(results, index= range(1, 13), name= baseline_label).to_frame().transpose()\n",
    "sns.set_theme()\n",
    "df.transpose().plot(xticks= range(1, 13), grid= True,title= \"Historical Climatology month (1970-2000)\", ylabel= unit, legend= False)\n",
    "file_historical = 'WorldClim - historical.png'\n",
    "plt.savefig(os.path.join(fld_out, file_historical), ) # bbox_inches= 'tight' argument optionnel pour limiter la largeur des marges au minimum nécessaire\n",
    "if variable.upper()== 'PRECIPITATION':\n",
    "    df[annual_label] = df.sum(axis= 1)\n",
    "elif variable.upper()== 'TEMPERATURE':\n",
    "    df[annual_label] = df.mean(axis= 1)\n",
    "df_historical= df.copy()\n",
    "print(\"Process completed in \", datetime.datetime.now()-start)\n",
    "display(df_historical)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=section02></a>2) Future Climatologies\n",
    "NOTA: Customize the file prefix to handle precipitation or average temperature\n",
    "\n",
    "Customize the code below with....\n",
    "- folder path tif files for future data (folder containing 4 sub-folders for the 4 future periods)\n",
    "- Prefix of the file name (begining of the file name, depending on the parameter, on the version of wordclim data, and on the resolution of the rasters)\n",
    "- List of the models e.g. ['BCC-CSM2-MR', 'CNRM-CM6-1', ....] (left-middle of the file name)\n",
    "- List of the SSP scenarios e.g. ['ssp126', 'ssp245', 'ssp370', 'ssp585'] (right-middle of the file name)\n",
    "- List of the future periods e.g. ['2021-2040', '2041-2060', '2061-2080', '2081-2100'] (end of the file name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Process started. Please wait the ending message ... \n",
      "Period -------------- 2021-2040\n",
      "Period -------------- 2041-2060\n",
      "Period -------------- 2061-2080\n",
      "Period -------------- 2081-2100\n",
      "Process completed in  0:00:18.586722\n"
     ]
    },
    {
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       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>Annual</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2021-2040 ssp126 BCC-CSM2-MR</th>\n",
       "      <td>20.2</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-2040 ssp245 BCC-CSM2-MR</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-2040 ssp370 BCC-CSM2-MR</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.8</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-2040 ssp585 BCC-CSM2-MR</th>\n",
       "      <td>20.4</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.5</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060 ssp126 BCC-CSM2-MR</th>\n",
       "      <td>20.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                 1     2     3     4     5     6     7     8  \\\n",
       "2021-2040 ssp126 BCC-CSM2-MR  20.2  20.7  21.4  22.1  22.6  23.0  23.3  23.4   \n",
       "2021-2040 ssp245 BCC-CSM2-MR  20.3  20.7  21.4  22.0  22.6  23.1  23.5  23.6   \n",
       "2021-2040 ssp370 BCC-CSM2-MR  20.3  20.8  21.6  22.1  22.7  23.1  23.3  23.6   \n",
       "2021-2040 ssp585 BCC-CSM2-MR  20.4  20.9  21.5  22.3  22.7  23.2  23.5  23.6   \n",
       "2041-2060 ssp126 BCC-CSM2-MR  20.5  20.9  21.7  22.2  22.8  23.1  23.4  23.6   \n",
       "\n",
       "                                 9    10    11    12  Annual  \n",
       "2021-2040 ssp126 BCC-CSM2-MR  23.3  22.8  21.8  20.7    22.1  \n",
       "2021-2040 ssp245 BCC-CSM2-MR  23.5  22.9  21.8  20.9    22.2  \n",
       "2021-2040 ssp370 BCC-CSM2-MR  23.5  23.0  21.9  20.8    22.2  \n",
       "2021-2040 ssp585 BCC-CSM2-MR  23.6  22.9  22.0  20.9    22.3  \n",
       "2041-2060 ssp126 BCC-CSM2-MR  23.4  22.9  22.0  20.8    22.3  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Created on January 2021\n",
    "@author: Loïc Duffar\n",
    "\"\"\"\n",
    "import math\n",
    "import datetime\n",
    "\n",
    "# +++++++ Customization\n",
    "# ....... folder path for the tif files (WITHOUT \"\\\" CHARACTER AT THE END !!!)\n",
    "fld_in = r'X:\\1-COMMUN\\DIS\\Documentation\\Hydrologie\\Documentation externe\\Climat Monde\\WorldClim\\Future data 2021-2100'\n",
    "# ....... Polygon file (shape file) for plotting and average computation (path INCLUDING folder)\n",
    "polygon_file = r'C:\\Users\\DUFFAR\\Documents\\A\\ETUDES\\2021 Yaque del Sur\\Carto\\Subcuencas_YaqueSur.shp'\n",
    "\n",
    "# ....... Composition of the tif file names\n",
    "gcm_list = ['BCC-CSM2-MR']#, 'CNRM-CM6-1', 'CNRM-ESM2-1', 'CanESM5', 'GFDL-ESM4', 'IPSL-CM6A-LR', 'MIROC-ES2L', 'MIROC6', 'MRI-ESM2-0']\n",
    "ssp_list = ['ssp126', 'ssp245', 'ssp370', 'ssp585']\n",
    "ssp_list_long = ['ssp1-2.6', 'ssp2-4.5', 'ssp3-7.0', 'ssp5-8.5']\n",
    "period_list = ['2021-2040', '2041-2060', '2061-2080', '2081-2100']\n",
    "\n",
    "# +++++++ Process\n",
    "print('Process started. Please wait the ending message ... ')\n",
    "\n",
    "start= datetime.datetime.now()# Start Timer\n",
    "series = []\n",
    "for period in period_list:\n",
    "    path = fld_in + '/' + period\n",
    "    print('Period --------------', period)\n",
    "    for gcm in gcm_list:\n",
    "        for scenario in ssp_list:\n",
    "            if variable.upper()== 'PRECIPITATION':\n",
    "                file = os.path.join(path, '_'.join([file_prefix, gcm, scenario, period]) + '.tif')\n",
    "            elif variable.upper()== 'TEMPERATURE':\n",
    "                file = os.path.join(path, '_'.join([file_prefix + 'min', gcm, scenario, period]) + '.tif')\n",
    "                file2 = os.path.join(path, '_'.join([file_prefix + 'max', gcm, scenario, period]) + '.tif')\n",
    "            if not os.path.exists(file):\n",
    "                serie= pd.Series([math.nan for i in range(1, 13)], index= range(1, 13), name= ' '.join([period, scenario, gcm]))\n",
    "            else:\n",
    "                results = []\n",
    "                # Loop over months (1 month by file band)\n",
    "                for band in range(1, 13):\n",
    "                    if variable.upper()== 'PRECIPITATION':\n",
    "                        res = rasterstats.zonal_stats(polygon_file, file, stats=['mean'], band= band)[0]['mean']\n",
    "                    elif variable.upper()== 'TEMPERATURE':\n",
    "                        res= rasterstats.zonal_stats(polygon_file, file, stats=['mean'], band= band)[0]['mean']\n",
    "                        res= res + rasterstats.zonal_stats(polygon_file, file2, stats=['mean'], band= band)[0]['mean']\n",
    "                        res= res / 2\n",
    "                    results.append(round(res, 1))\n",
    "                serie = pd.Series(results, index= range(1, 13), name= ' '.join([period, scenario, gcm]))\n",
    "            series.append(serie)\n",
    "\n",
    "df = pd.DataFrame(series)\n",
    "if variable.upper()== 'PRECIPITATION':\n",
    "    df[annual_label] = df.sum(axis= 1, skipna= False)\n",
    "elif variable.upper()== 'TEMPERATURE':\n",
    "    df[annual_label] = df.mean(axis= 1, skipna= False).round(1)\n",
    "\n",
    "print(\"Process completed in \", datetime.datetime.now()-start)\n",
    "df_future= df.copy()\n",
    "display(df_future.head())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=section03></a>3) Create multi index for the dataframe (by Model, Scenario and Period)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>Annual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Model</th>\n",
       "      <th>Scenario</th>\n",
       "      <th>Period</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">BCC-CSM2-MR</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp126</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.2</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>20.6</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>22.1</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ssp245</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                    1     2     3     4     5     6     7  \\\n",
       "Model        Scenario Period                                                \n",
       " BCC-CSM2-MR ssp126   2021-2040  20.2  20.7  21.4  22.1  22.6  23.0  23.3   \n",
       "                      2041-2060  20.5  20.9  21.7  22.2  22.8  23.1  23.4   \n",
       "                      2061-2080  20.6  20.9  21.8  22.3  22.9  23.3  23.6   \n",
       "                      2081-2100  20.3  20.9  21.7  22.2  22.7  23.2  23.5   \n",
       "             ssp245   2021-2040  20.3  20.7  21.4  22.0  22.6  23.1  23.5   \n",
       "\n",
       "                                    8     9    10    11    12  Annual  \n",
       "Model        Scenario Period                                           \n",
       " BCC-CSM2-MR ssp126   2021-2040  23.4  23.3  22.8  21.8  20.7    22.1  \n",
       "                      2041-2060  23.6  23.4  22.9  22.0  20.8    22.3  \n",
       "                      2061-2080  23.7  23.6  23.1  22.1  21.0    22.4  \n",
       "                      2081-2100  23.5  23.5  23.0  21.9  20.8    22.3  \n",
       "             ssp245   2021-2040  23.6  23.5  22.9  21.8  20.9    22.2  "
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Created on January 2021\n",
    "@author: Loïc Duffar\n",
    "\"\"\"\n",
    "df_future['Period']= df.index.str[0:9]\n",
    "df_future['Scenario']= df.index.str[10:16]\n",
    "df_future['Model']= df.index.str[16:]\n",
    "df_future.set_index(keys= ['Model', 'Scenario', 'Period'], drop= True, inplace=True)\n",
    "df_future.sort_index(inplace= True)\n",
    "df_future.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=section04></a>4) Concatenate historical and future precipitation in a single dataframe, and save it in an excel file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>Annual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Model</th>\n",
       "      <th>Scenario</th>\n",
       "      <th>Period</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Historical</th>\n",
       "      <th>1970-2000</th>\n",
       "      <td>19.4</td>\n",
       "      <td>19.8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.2</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.6</td>\n",
       "      <td>22.7</td>\n",
       "      <td>22.5</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>19.8</td>\n",
       "      <td>21.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"16\" valign=\"top\">BCC-CSM2-MR</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp126</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.2</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>20.6</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>22.1</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp245</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.6</td>\n",
       "      <td>21.2</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>22.3</td>\n",
       "      <td>21.2</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.2</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>21.3</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.3</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.8</td>\n",
       "      <td>23.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp370</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.8</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.3</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.5</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.6</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.3</td>\n",
       "      <td>24.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.1</td>\n",
       "      <td>23.2</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.9</td>\n",
       "      <td>25.2</td>\n",
       "      <td>25.5</td>\n",
       "      <td>25.5</td>\n",
       "      <td>24.8</td>\n",
       "      <td>23.9</td>\n",
       "      <td>22.7</td>\n",
       "      <td>24.1</td>\n",
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       "      <td>21.5</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.3</td>\n",
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       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
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       "      <td>23.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.2</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.9</td>\n",
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       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.8</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.9</td>\n",
       "      <td>25.0</td>\n",
       "      <td>24.4</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.3</td>\n",
       "      <td>23.7</td>\n",
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       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>22.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.7</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.8</td>\n",
       "      <td>25.1</td>\n",
       "      <td>25.3</td>\n",
       "      <td>25.7</td>\n",
       "      <td>25.7</td>\n",
       "      <td>25.1</td>\n",
       "      <td>24.0</td>\n",
       "      <td>22.9</td>\n",
       "      <td>24.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "                                      1     2     3     4     5     6     7  \\\n",
       "Model        Scenario   Period                                                \n",
       "             Historical 1970-2000  19.4  19.8  20.7  21.2  21.8  22.2  22.6   \n",
       " BCC-CSM2-MR ssp126     2021-2040  20.2  20.7  21.4  22.1  22.6  23.0  23.3   \n",
       "                        2041-2060  20.5  20.9  21.7  22.2  22.8  23.1  23.4   \n",
       "                        2061-2080  20.6  20.9  21.8  22.3  22.9  23.3  23.6   \n",
       "                        2081-2100  20.3  20.9  21.7  22.2  22.7  23.2  23.5   \n",
       "             ssp245     2021-2040  20.3  20.7  21.4  22.0  22.6  23.1  23.5   \n",
       "                        2041-2060  20.6  21.2  22.0  22.5  23.0  23.5  23.8   \n",
       "                        2061-2080  21.0  21.6  22.3  22.7  23.4  23.7  23.9   \n",
       "                        2081-2100  21.3  21.8  22.6  23.1  23.6  24.1  24.3   \n",
       "             ssp370     2021-2040  20.3  20.8  21.6  22.1  22.7  23.1  23.3   \n",
       "                        2041-2060  21.0  21.3  22.3  22.8  23.3  23.7  24.0   \n",
       "                        2061-2080  21.6  22.0  22.8  23.4  23.9  24.3  24.6   \n",
       "                        2081-2100  22.1  22.6  23.4  23.9  24.5  24.9  25.2   \n",
       "             ssp585     2021-2040  20.4  20.9  21.5  22.3  22.7  23.2  23.5   \n",
       "                        2041-2060  21.0  21.4  22.1  22.9  23.4  23.8  24.0   \n",
       "                        2061-2080  21.8  22.1  23.1  23.5  24.1  24.5  24.8   \n",
       "                        2081-2100  22.4  22.9  23.7  24.2  24.8  25.1  25.3   \n",
       "\n",
       "                                      8     9    10    11    12  Annual  \n",
       "Model        Scenario   Period                                           \n",
       "             Historical 1970-2000  22.7  22.5  22.0  20.9  19.8    21.3  \n",
       " BCC-CSM2-MR ssp126     2021-2040  23.4  23.3  22.8  21.8  20.7    22.1  \n",
       "                        2041-2060  23.6  23.4  22.9  22.0  20.8    22.3  \n",
       "                        2061-2080  23.7  23.6  23.1  22.1  21.0    22.4  \n",
       "                        2081-2100  23.5  23.5  23.0  21.9  20.8    22.3  \n",
       "             ssp245     2021-2040  23.6  23.5  22.9  21.8  20.9    22.2  \n",
       "                        2041-2060  23.8  23.7  23.2  22.3  21.2    22.6  \n",
       "                        2061-2080  24.1  24.2  23.6  22.6  21.4    22.9  \n",
       "                        2081-2100  24.5  24.4  23.8  23.0  21.8    23.2  \n",
       "             ssp370     2021-2040  23.6  23.5  23.0  21.9  20.8    22.2  \n",
       "                        2041-2060  24.2  24.1  23.6  22.6  21.5    22.9  \n",
       "                        2061-2080  24.8  24.8  24.1  23.2  22.1    23.5  \n",
       "                        2081-2100  25.5  25.5  24.8  23.9  22.7    24.1  \n",
       "             ssp585     2021-2040  23.6  23.6  22.9  22.0  20.9    22.3  \n",
       "                        2041-2060  24.2  24.2  23.6  22.6  21.6    22.9  \n",
       "                        2061-2080  24.9  25.0  24.4  23.4  22.3    23.7  \n",
       "                        2081-2100  25.7  25.7  25.1  24.0  22.9    24.3  "
      ]
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     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Created on January 2021\n",
    "@author: Loïc Duffar\n",
    "\"\"\"\n",
    "df_historical= df_historical.copy()\n",
    "df_historical['Model']= ''\n",
    "df_historical['Scenario']= 'Historical'\n",
    "df_historical['Period']= historical_period\n",
    "df_historical.set_index(keys= ['Model', 'Scenario', 'Period'], inplace= True, drop= True)\n",
    "df_total= df_future.append(df_historical)\n",
    "df_total= df_total.sort_index()\n",
    "display(df_total)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=section05></a>5) Plot future evolution of annual precipitation/temperature (all scenarios and all GCMs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "Plotly version:  4.14.1\n"
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       "                            \n",
       "var gd = document.getElementById('44f8b9bc-5b8a-4b84-b009-8438433c88ec');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Created on January 2021\n",
    "@author: Loïc Duffar\n",
    "\"\"\"\n",
    "import plotly.graph_objects as go\n",
    "import plotly\n",
    "print('Plotly version: ', plotly.__version__)\n",
    "\n",
    "#============== Customization\n",
    "#------------ Name of the dataframe column to plot (e.g. annual or one of month number 1-12) \n",
    "month_or_year = annual_label\n",
    "\n",
    "#============== Process\n",
    "rgba_list= ['rgba(10, 10, 150, 0.2)', 'rgba(255, 10, 10, 0.1)', 'rgba(10, 150, 10, 0.1)', 'rgba(200, 200, 0, 0.2)']\n",
    "rgb_list= ['rgb(10, 10, 150)', 'rgb(150, 10, 10)', 'rgb(10, 150, 10)', 'rgb(250, 170, 60)']\n",
    "\n",
    "x = [historical_period] + ['2021-2040', '2041-2060', '2061-2080', '2081-2100']\n",
    "fig = go.Figure()\n",
    "    \n",
    "for scenario, scenario_long, rgb, rgba in zip(ssp_list, ssp_list_long, rgb_list, rgba_list):\n",
    "    test= (df_total.index.get_level_values('Scenario') == scenario) | (df_total.index.get_level_values('Scenario') =='Historical')\n",
    "    group = df_total[test ][month_or_year].groupby(by= ['Period'])\n",
    "    ymedian= group.median() \n",
    "    ymin= group.min()\n",
    "    ymax= group.max()\n",
    "\n",
    "    fig.add_trace(\n",
    "        go.Scatter(\n",
    "                    name= scenario_long + ' Median of ' + str(len(gcm_list)) + ' GCMs',\n",
    "                    x= x,\n",
    "                    y= ymedian,\n",
    "                    mode= 'lines',\n",
    "                    line= dict(color= rgb),\n",
    "                    legendgroup= scenario,\n",
    "                ))\n",
    "\n",
    "    fig.add_trace(\n",
    "        go.Scatter(\n",
    "                    name= scenario_long + ' Min.',\n",
    "                    x= x,\n",
    "                    y= ymin,\n",
    "                    mode= 'lines',\n",
    "                    line= dict(width= 0),\n",
    "                    legendgroup= scenario,            \n",
    "                    hoverlabel= dict(bgcolor= rgb, font_color='white'),\n",
    "                    showlegend= False,\n",
    "                    marker= dict(color= \"#444\"),\n",
    "#                     fillcolor= rgba,\n",
    "#                     fill= 'tonexty',\n",
    "                    ))\n",
    "    fig.add_trace(\n",
    "        go.Scatter(\n",
    "                    name= scenario_long + ' Min.Max.',\n",
    "                    x= x,\n",
    "                    y= ymax,\n",
    "                    mode= 'lines',\n",
    "                    line= dict(width= 0),\n",
    "                    legendgroup= scenario,            \n",
    "                    hoverlabel= dict(bgcolor= rgb, font_color='white'),\n",
    "                    showlegend= True,\n",
    "                    marker= dict(color= \"#444\"),\n",
    "                    fillcolor= rgba,\n",
    "                    fill= 'tonexty',\n",
    "                    ))\n",
    "\n",
    "if variable.upper()== 'PRECIPITATION':\n",
    "    ylegend= 0.05\n",
    "    yanchor= \"bottom\"\n",
    "elif variable.upper()== 'TEMPERATURE':\n",
    "    ylegend= 0.95\n",
    "    yanchor= \"top\"\n",
    "fig.update_layout(\n",
    "    height= 700, width= 1000,\n",
    "    yaxis_title= unit,\n",
    "    title= 'Evolution of future ' + variable + ' Climatology, according to ' + str(len(ssp_list)) + ' scenarios and ' + str(len(gcm_list)) + ' GCMs',\n",
    "#    hovermode= \"x\",\n",
    "    yaxis_range= [df_total.min().max(), df_total.max().max()],\n",
    "    legend=dict(yanchor= yanchor,\n",
    "                y= ylegend,\n",
    "                xanchor= 'left',\n",
    "                x= 0.05),\n",
    "    template= \"plotly\", # \"plotly\", \"plotly_white\", \"plotly_dark\", \"ggplot2\", \"seaborn\", \"simple_white\", \"none\"\n",
    "#    paper_bgcolor='rgba(0,0,0,0)',\n",
    "#    plot_bgcolor='rgba(0,0,0,0)',\n",
    "    )\n",
    "file_future_by_year= 'WorldClim - future by year.png'\n",
    "fig.write_image(os.path.join(fld_out, file_future_by_year))# needs installation of \"plotly-orca\" or \"kaleido\"\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=section06></a>6) Plot future evolution for each month (all scenarios and all GCMs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
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       "                            \n",
       "var gd = document.getElementById('c558b072-03c2-441d-abdf-9298f65a8388');\n",
       "var x = new MutationObserver(function (mutations, observer) {{\n",
       "        var display = window.getComputedStyle(gd).display;\n",
       "        if (!display || display === 'none') {{\n",
       "            console.log([gd, 'removed!']);\n",
       "            Plotly.purge(gd);\n",
       "            observer.disconnect();\n",
       "        }}\n",
       "}});\n",
       "\n",
       "// Listen for the removal of the full notebook cells\n",
       "var notebookContainer = gd.closest('#notebook-container');\n",
       "if (notebookContainer) {{\n",
       "    x.observe(notebookContainer, {childList: true});\n",
       "}}\n",
       "\n",
       "// Listen for the clearing of the current output cell\n",
       "var outputEl = gd.closest('.output');\n",
       "if (outputEl) {{\n",
       "    x.observe(outputEl, {childList: true});\n",
       "}}\n",
       "\n",
       "                        })                };                });            </script>        </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import plotly.subplots as ps\n",
    "\n",
    "fig = ps.make_subplots(rows= 4, cols= 3,\n",
    "                       shared_xaxes=True,\n",
    "                       vertical_spacing=0.05,\n",
    "                       subplot_titles= range(1, 13)\n",
    "                      )\n",
    "\n",
    "month= 0\n",
    "for rw in range(1, 5):\n",
    "    for cl in range(1, 4):\n",
    "        showlegend= True if month== 0 else False\n",
    "        month = month + 1\n",
    "        for scenario, scenario_long, rgb, rgba in zip(ssp_list, ssp_list_long, rgb_list, rgba_list):\n",
    "            test= (df_total.index.get_level_values('Scenario') == scenario) | (df_total.index.get_level_values('Scenario') =='Historical')\n",
    "            group = df_total[test ][month].groupby(by= 'Period')\n",
    "\n",
    "            fig.add_trace(\n",
    "                go.Scatter(\n",
    "                    name= scenario_long + ' (' + str(len(gcm_list)) + ' GCMs median)',\n",
    "                    x= x,\n",
    "                    y= group.median(),\n",
    "                    mode= 'lines',\n",
    "                    line= dict(color= rgb),\n",
    "                    legendgroup= scenario,\n",
    "                    showlegend= showlegend,\n",
    "#                    yaxis= dict(range= [df_total[test ][month].min(), df_total[test ][month].max()]),\n",
    "                        ),\n",
    "                    row= rw, col= cl\n",
    "                    )\n",
    "\n",
    "fig.update_layout(\n",
    "    height= 800, width= 1000,\n",
    "    yaxis_title= unit,\n",
    "    title= 'Evolution of future Monthly ' + variable +  ' Climatology, according to ' + str(len(ssp_list)) + ' scenarios (median of ' + str(len(gcm_list)) + ' GCMs)',\n",
    "    template= \"plotly\", # \"plotly\", \"plotly_white\", \"plotly_dark\", \"ggplot2\", \"seaborn\", \"simple_white\", \"none\"\n",
    "    hovermode= \"x\",\n",
    "#    yaxis_range= [df_total.min().max(), df_total.max().max()],\n",
    "#    legend= dict(orientation= 'h', yanchor= \"top\", y= -0.1, xanchor= \"left\", x= 0.05),\n",
    "    showlegend= True,\n",
    "    )\n",
    "for ax in fig['layout']:\n",
    "    if ax[:5]== 'yaxis':\n",
    "        if ax[5:] in ['1', '4', '7', '10']:\n",
    "            fig['layout'][ax]['title']= unit\n",
    "file_future_by_month= 'WorldClim - future by month.png'\n",
    "fig.write_image(os.path.join(fld_out, file_future_by_month))# needs installation of \"plotly-orca\" or \"kaleido\"\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=section07></a>7) Create a dataframe with statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "scrolled": true
   },
   "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></th>\n",
       "      <th></th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>Annual</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Model</th>\n",
       "      <th>Scenario</th>\n",
       "      <th>Period</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"16\" valign=\"top\">Max</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp126</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.2</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>20.6</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>22.1</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp245</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.6</td>\n",
       "      <td>21.2</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>22.3</td>\n",
       "      <td>21.2</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.2</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>21.3</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.3</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.8</td>\n",
       "      <td>23.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp370</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.8</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.3</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.5</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.6</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.3</td>\n",
       "      <td>24.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.1</td>\n",
       "      <td>23.2</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.9</td>\n",
       "      <td>25.2</td>\n",
       "      <td>25.5</td>\n",
       "      <td>25.5</td>\n",
       "      <td>24.8</td>\n",
       "      <td>23.9</td>\n",
       "      <td>22.7</td>\n",
       "      <td>24.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp585</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.4</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.5</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.2</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.8</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.9</td>\n",
       "      <td>25.0</td>\n",
       "      <td>24.4</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.3</td>\n",
       "      <td>23.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>22.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.7</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.8</td>\n",
       "      <td>25.1</td>\n",
       "      <td>25.3</td>\n",
       "      <td>25.7</td>\n",
       "      <td>25.7</td>\n",
       "      <td>25.1</td>\n",
       "      <td>24.0</td>\n",
       "      <td>22.9</td>\n",
       "      <td>24.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"16\" valign=\"top\">Median</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp126</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.2</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>20.6</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>22.1</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp245</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.6</td>\n",
       "      <td>21.2</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>22.3</td>\n",
       "      <td>21.2</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.2</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>21.3</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.3</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.8</td>\n",
       "      <td>23.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp370</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.8</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.3</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.5</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.6</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.3</td>\n",
       "      <td>24.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.1</td>\n",
       "      <td>23.2</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.9</td>\n",
       "      <td>25.2</td>\n",
       "      <td>25.5</td>\n",
       "      <td>25.5</td>\n",
       "      <td>24.8</td>\n",
       "      <td>23.9</td>\n",
       "      <td>22.7</td>\n",
       "      <td>24.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp585</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.4</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.5</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.2</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.8</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.9</td>\n",
       "      <td>25.0</td>\n",
       "      <td>24.4</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.3</td>\n",
       "      <td>23.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>22.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.7</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.8</td>\n",
       "      <td>25.1</td>\n",
       "      <td>25.3</td>\n",
       "      <td>25.7</td>\n",
       "      <td>25.7</td>\n",
       "      <td>25.1</td>\n",
       "      <td>24.0</td>\n",
       "      <td>22.9</td>\n",
       "      <td>24.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"16\" valign=\"top\">Min</th>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp126</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.2</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.7</td>\n",
       "      <td>22.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.5</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>20.6</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>22.1</td>\n",
       "      <td>21.0</td>\n",
       "      <td>22.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.7</td>\n",
       "      <td>22.2</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp245</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.7</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>22.9</td>\n",
       "      <td>21.8</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>20.6</td>\n",
       "      <td>21.2</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>22.3</td>\n",
       "      <td>21.2</td>\n",
       "      <td>22.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.7</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.2</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>21.3</td>\n",
       "      <td>21.8</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.3</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.8</td>\n",
       "      <td>23.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp370</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.3</td>\n",
       "      <td>20.8</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.0</td>\n",
       "      <td>21.9</td>\n",
       "      <td>20.8</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.3</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.3</td>\n",
       "      <td>23.7</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.1</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.5</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.6</td>\n",
       "      <td>22.0</td>\n",
       "      <td>22.8</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.3</td>\n",
       "      <td>24.6</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.1</td>\n",
       "      <td>23.2</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>22.1</td>\n",
       "      <td>22.6</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.9</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.9</td>\n",
       "      <td>25.2</td>\n",
       "      <td>25.5</td>\n",
       "      <td>25.5</td>\n",
       "      <td>24.8</td>\n",
       "      <td>23.9</td>\n",
       "      <td>22.7</td>\n",
       "      <td>24.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">ssp585</th>\n",
       "      <th>2021-2040</th>\n",
       "      <td>20.4</td>\n",
       "      <td>20.9</td>\n",
       "      <td>21.5</td>\n",
       "      <td>22.3</td>\n",
       "      <td>22.7</td>\n",
       "      <td>23.2</td>\n",
       "      <td>23.5</td>\n",
       "      <td>23.6</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.9</td>\n",
       "      <td>22.0</td>\n",
       "      <td>20.9</td>\n",
       "      <td>22.3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2041-2060</th>\n",
       "      <td>21.0</td>\n",
       "      <td>21.4</td>\n",
       "      <td>22.1</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.4</td>\n",
       "      <td>23.8</td>\n",
       "      <td>24.0</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.2</td>\n",
       "      <td>23.6</td>\n",
       "      <td>22.6</td>\n",
       "      <td>21.6</td>\n",
       "      <td>22.9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2061-2080</th>\n",
       "      <td>21.8</td>\n",
       "      <td>22.1</td>\n",
       "      <td>23.1</td>\n",
       "      <td>23.5</td>\n",
       "      <td>24.1</td>\n",
       "      <td>24.5</td>\n",
       "      <td>24.8</td>\n",
       "      <td>24.9</td>\n",
       "      <td>25.0</td>\n",
       "      <td>24.4</td>\n",
       "      <td>23.4</td>\n",
       "      <td>22.3</td>\n",
       "      <td>23.7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2081-2100</th>\n",
       "      <td>22.4</td>\n",
       "      <td>22.9</td>\n",
       "      <td>23.7</td>\n",
       "      <td>24.2</td>\n",
       "      <td>24.8</td>\n",
       "      <td>25.1</td>\n",
       "      <td>25.3</td>\n",
       "      <td>25.7</td>\n",
       "      <td>25.7</td>\n",
       "      <td>25.1</td>\n",
       "      <td>24.0</td>\n",
       "      <td>22.9</td>\n",
       "      <td>24.3</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              1     2     3     4     5     6     7     8  \\\n",
       "Model  Scenario Period                                                      \n",
       "Max    ssp126   2021-2040  20.2  20.7  21.4  22.1  22.6  23.0  23.3  23.4   \n",
       "                2041-2060  20.5  20.9  21.7  22.2  22.8  23.1  23.4  23.6   \n",
       "                2061-2080  20.6  20.9  21.8  22.3  22.9  23.3  23.6  23.7   \n",
       "                2081-2100  20.3  20.9  21.7  22.2  22.7  23.2  23.5  23.5   \n",
       "       ssp245   2021-2040  20.3  20.7  21.4  22.0  22.6  23.1  23.5  23.6   \n",
       "                2041-2060  20.6  21.2  22.0  22.5  23.0  23.5  23.8  23.8   \n",
       "                2061-2080  21.0  21.6  22.3  22.7  23.4  23.7  23.9  24.1   \n",
       "                2081-2100  21.3  21.8  22.6  23.1  23.6  24.1  24.3  24.5   \n",
       "       ssp370   2021-2040  20.3  20.8  21.6  22.1  22.7  23.1  23.3  23.6   \n",
       "                2041-2060  21.0  21.3  22.3  22.8  23.3  23.7  24.0  24.2   \n",
       "                2061-2080  21.6  22.0  22.8  23.4  23.9  24.3  24.6  24.8   \n",
       "                2081-2100  22.1  22.6  23.4  23.9  24.5  24.9  25.2  25.5   \n",
       "       ssp585   2021-2040  20.4  20.9  21.5  22.3  22.7  23.2  23.5  23.6   \n",
       "                2041-2060  21.0  21.4  22.1  22.9  23.4  23.8  24.0  24.2   \n",
       "                2061-2080  21.8  22.1  23.1  23.5  24.1  24.5  24.8  24.9   \n",
       "                2081-2100  22.4  22.9  23.7  24.2  24.8  25.1  25.3  25.7   \n",
       "Median ssp126   2021-2040  20.2  20.7  21.4  22.1  22.6  23.0  23.3  23.4   \n",
       "                2041-2060  20.5  20.9  21.7  22.2  22.8  23.1  23.4  23.6   \n",
       "                2061-2080  20.6  20.9  21.8  22.3  22.9  23.3  23.6  23.7   \n",
       "                2081-2100  20.3  20.9  21.7  22.2  22.7  23.2  23.5  23.5   \n",
       "       ssp245   2021-2040  20.3  20.7  21.4  22.0  22.6  23.1  23.5  23.6   \n",
       "                2041-2060  20.6  21.2  22.0  22.5  23.0  23.5  23.8  23.8   \n",
       "                2061-2080  21.0  21.6  22.3  22.7  23.4  23.7  23.9  24.1   \n",
       "                2081-2100  21.3  21.8  22.6  23.1  23.6  24.1  24.3  24.5   \n",
       "       ssp370   2021-2040  20.3  20.8  21.6  22.1  22.7  23.1  23.3  23.6   \n",
       "                2041-2060  21.0  21.3  22.3  22.8  23.3  23.7  24.0  24.2   \n",
       "                2061-2080  21.6  22.0  22.8  23.4  23.9  24.3  24.6  24.8   \n",
       "                2081-2100  22.1  22.6  23.4  23.9  24.5  24.9  25.2  25.5   \n",
       "       ssp585   2021-2040  20.4  20.9  21.5  22.3  22.7  23.2  23.5  23.6   \n",
       "                2041-2060  21.0  21.4  22.1  22.9  23.4  23.8  24.0  24.2   \n",
       "                2061-2080  21.8  22.1  23.1  23.5  24.1  24.5  24.8  24.9   \n",
       "                2081-2100  22.4  22.9  23.7  24.2  24.8  25.1  25.3  25.7   \n",
       "Min    ssp126   2021-2040  20.2  20.7  21.4  22.1  22.6  23.0  23.3  23.4   \n",
       "                2041-2060  20.5  20.9  21.7  22.2  22.8  23.1  23.4  23.6   \n",
       "                2061-2080  20.6  20.9  21.8  22.3  22.9  23.3  23.6  23.7   \n",
       "                2081-2100  20.3  20.9  21.7  22.2  22.7  23.2  23.5  23.5   \n",
       "       ssp245   2021-2040  20.3  20.7  21.4  22.0  22.6  23.1  23.5  23.6   \n",
       "                2041-2060  20.6  21.2  22.0  22.5  23.0  23.5  23.8  23.8   \n",
       "                2061-2080  21.0  21.6  22.3  22.7  23.4  23.7  23.9  24.1   \n",
       "                2081-2100  21.3  21.8  22.6  23.1  23.6  24.1  24.3  24.5   \n",
       "       ssp370   2021-2040  20.3  20.8  21.6  22.1  22.7  23.1  23.3  23.6   \n",
       "                2041-2060  21.0  21.3  22.3  22.8  23.3  23.7  24.0  24.2   \n",
       "                2061-2080  21.6  22.0  22.8  23.4  23.9  24.3  24.6  24.8   \n",
       "                2081-2100  22.1  22.6  23.4  23.9  24.5  24.9  25.2  25.5   \n",
       "       ssp585   2021-2040  20.4  20.9  21.5  22.3  22.7  23.2  23.5  23.6   \n",
       "                2041-2060  21.0  21.4  22.1  22.9  23.4  23.8  24.0  24.2   \n",
       "                2061-2080  21.8  22.1  23.1  23.5  24.1  24.5  24.8  24.9   \n",
       "                2081-2100  22.4  22.9  23.7  24.2  24.8  25.1  25.3  25.7   \n",
       "\n",
       "                              9    10    11    12  Annual  \n",
       "Model  Scenario Period                                     \n",
       "Max    ssp126   2021-2040  23.3  22.8  21.8  20.7    22.1  \n",
       "                2041-2060  23.4  22.9  22.0  20.8    22.3  \n",
       "                2061-2080  23.6  23.1  22.1  21.0    22.4  \n",
       "                2081-2100  23.5  23.0  21.9  20.8    22.3  \n",
       "       ssp245   2021-2040  23.5  22.9  21.8  20.9    22.2  \n",
       "                2041-2060  23.7  23.2  22.3  21.2    22.6  \n",
       "                2061-2080  24.2  23.6  22.6  21.4    22.9  \n",
       "                2081-2100  24.4  23.8  23.0  21.8    23.2  \n",
       "       ssp370   2021-2040  23.5  23.0  21.9  20.8    22.2  \n",
       "                2041-2060  24.1  23.6  22.6  21.5    22.9  \n",
       "                2061-2080  24.8  24.1  23.2  22.1    23.5  \n",
       "                2081-2100  25.5  24.8  23.9  22.7    24.1  \n",
       "       ssp585   2021-2040  23.6  22.9  22.0  20.9    22.3  \n",
       "                2041-2060  24.2  23.6  22.6  21.6    22.9  \n",
       "                2061-2080  25.0  24.4  23.4  22.3    23.7  \n",
       "                2081-2100  25.7  25.1  24.0  22.9    24.3  \n",
       "Median ssp126   2021-2040  23.3  22.8  21.8  20.7    22.1  \n",
       "                2041-2060  23.4  22.9  22.0  20.8    22.3  \n",
       "                2061-2080  23.6  23.1  22.1  21.0    22.4  \n",
       "                2081-2100  23.5  23.0  21.9  20.8    22.3  \n",
       "       ssp245   2021-2040  23.5  22.9  21.8  20.9    22.2  \n",
       "                2041-2060  23.7  23.2  22.3  21.2    22.6  \n",
       "                2061-2080  24.2  23.6  22.6  21.4    22.9  \n",
       "                2081-2100  24.4  23.8  23.0  21.8    23.2  \n",
       "       ssp370   2021-2040  23.5  23.0  21.9  20.8    22.2  \n",
       "                2041-2060  24.1  23.6  22.6  21.5    22.9  \n",
       "                2061-2080  24.8  24.1  23.2  22.1    23.5  \n",
       "                2081-2100  25.5  24.8  23.9  22.7    24.1  \n",
       "       ssp585   2021-2040  23.6  22.9  22.0  20.9    22.3  \n",
       "                2041-2060  24.2  23.6  22.6  21.6    22.9  \n",
       "                2061-2080  25.0  24.4  23.4  22.3    23.7  \n",
       "                2081-2100  25.7  25.1  24.0  22.9    24.3  \n",
       "Min    ssp126   2021-2040  23.3  22.8  21.8  20.7    22.1  \n",
       "                2041-2060  23.4  22.9  22.0  20.8    22.3  \n",
       "                2061-2080  23.6  23.1  22.1  21.0    22.4  \n",
       "                2081-2100  23.5  23.0  21.9  20.8    22.3  \n",
       "       ssp245   2021-2040  23.5  22.9  21.8  20.9    22.2  \n",
       "                2041-2060  23.7  23.2  22.3  21.2    22.6  \n",
       "                2061-2080  24.2  23.6  22.6  21.4    22.9  \n",
       "                2081-2100  24.4  23.8  23.0  21.8    23.2  \n",
       "       ssp370   2021-2040  23.5  23.0  21.9  20.8    22.2  \n",
       "                2041-2060  24.1  23.6  22.6  21.5    22.9  \n",
       "                2061-2080  24.8  24.1  23.2  22.1    23.5  \n",
       "                2081-2100  25.5  24.8  23.9  22.7    24.1  \n",
       "       ssp585   2021-2040  23.6  22.9  22.0  20.9    22.3  \n",
       "                2041-2060  24.2  23.6  22.6  21.6    22.9  \n",
       "                2061-2080  25.0  24.4  23.4  22.3    23.7  \n",
       "                2081-2100  25.7  25.1  24.0  22.9    24.3  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"\"\"\n",
    "Created on February 2021\n",
    "@author: Loïc Duffar\n",
    "\"\"\"\n",
    "import plotly.graph_objects as go\n",
    "\n",
    "#============== Customization\n",
    "#------------ \n",
    "\n",
    "\n",
    "#============== Process\n",
    "df = df_total[0:0]\n",
    "#display(df)\n",
    "    \n",
    "for scenario in ssp_list:\n",
    "    test= (df_total.index.get_level_values('Scenario') == scenario) \n",
    "    group = df_total[test ].groupby(by= ['Period'])\n",
    "    df_median= group.median().round(1)\n",
    "#    display(scenario, df_median.reset_index(drop= True))\n",
    "    df_min= group.min().round(1)\n",
    "    df_max= group.max().round(1)\n",
    "    temp= [[scenario, scenario, scenario, scenario], [period_list[0], period_list[1], period_list[2], period_list[3]] ]\n",
    "    temp= [['Max', 'Max', 'Max', 'Max']] + temp\n",
    "#    print(temp)\n",
    "    df= df.append(pd.DataFrame(df_max.values, index= [['Max', 'Max', 'Max', 'Max'], [scenario, scenario, scenario, scenario], [period_list[0], period_list[1], period_list[2], period_list[3]] ] ))\n",
    "    df= df.append(pd.DataFrame(df_median.values, index= [['Median', 'Median', 'Median', 'Median'], [scenario, scenario, scenario, scenario], [period_list[0], period_list[1], period_list[2], period_list[3]] ]))\n",
    "    df= df.append(pd.DataFrame(df_min.values, index= [['Min', 'Min', 'Min', 'Min'], [scenario, scenario, scenario, scenario], [period_list[0], period_list[1], period_list[2], period_list[3]] ] ))\n",
    "df_stat= df.sort_index().copy()\n",
    "df_stat.drop(columns= annual_label, inplace= True)\n",
    "df_stat.rename(columns= {0:1, 1:2,2:3, 3:4, 4:5, 5:6, 6:7, 7:8, 8:9, 9:10, 10:11, 11:12, 12:annual_label}, inplace= True)\n",
    "#df_stat= df_future.append(df_historical)\n",
    "df_stat"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=section07></a>8) Plot montly projections (all scenarios and GCMs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
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         "legendgroup": "2021-2040",
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       "            Plotly.purge(gd);\n",
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       "if (notebookContainer) {{\n",
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   "source": [
    "\"\"\"\n",
    "Created on February 2021\n",
    "@author: Loïc Duffar\n",
    "\"\"\"\n",
    "# Initialisation\n",
    "showlegend= True\n",
    "alpha_list=[1, 0.75, 0.5, 0.3, 0.1]\n",
    "\n",
    "# Plot\n",
    "x= df_stat.columns.to_list()[:-1]\n",
    "y_historical= df_historical[:].values[0][:-1]\n",
    "\n",
    "fig = ps.make_subplots(rows= 4, cols= 1,\n",
    "                       shared_xaxes= False,\n",
    "                       vertical_spacing= 0.05,\n",
    "                       subplot_titles= ssp_list_long\n",
    "                      )\n",
    "\n",
    "rw= 0\n",
    "for scenario, rgb, rgba in zip(ssp_list, rgb_list, rgba_list):\n",
    "    showlegend_historical= True if rw==0 else False\n",
    "    rw= rw + 1\n",
    "    fig.add_trace(\n",
    "        go.Scatter(\n",
    "                    name= baseline_label,\n",
    "                    x= x,\n",
    "                    y= y_historical,\n",
    "                    mode= 'lines+markers',\n",
    "                    line= dict(color= 'rgba(0,0,0,0.5)'),\n",
    "                    marker= dict(color= 'rgba(0,0,0,0)', line= dict(color='rgba(0,0,0,0.5)', width= 1)),\n",
    "                    legendgroup= baseline_label,\n",
    "                    showlegend= showlegend_historical,\n",
    "        #            yaxis= dict(range= [df_total[test ][month].min(), df_total[test ][month].max()]),\n",
    "                        ),\n",
    "                    row= rw, col= 1\n",
    "                    )\n",
    "\n",
    "    for period, alpha in zip(period_list, alpha_list):\n",
    "        rgba= 'rgba' + rgb[3:-1] + ',' + str(alpha) + ')'\n",
    "        y= df_stat.loc[('Median', scenario, period)].values[:-1]\n",
    "        fig.add_trace(\n",
    "            go.Scatter(\n",
    "                        name= period + ' ' + scenario,\n",
    "                        x= x,\n",
    "                        y= y,\n",
    "                        mode= 'lines',\n",
    "                        line= dict(color= rgba),\n",
    "                        legendgroup= period,\n",
    "                        showlegend= showlegend,\n",
    "        #                yaxis= dict(range= [df_total[test ][month].min(), df_total[test ][month].max()]),\n",
    "                            ),        \n",
    "                        row= rw, col= 1\n",
    "                        )\n",
    "\n",
    "fig.update_layout(\n",
    "    height= 900, width= 800,\n",
    "    yaxis_title= unit,\n",
    "    title= 'Monthly projections for each future period and each scenario (median of ' + str(len(gcm_list)) +' GCMs)',\n",
    "    template= \"plotly\", # \"plotly\", \"plotly_white\", \"plotly_dark\", \"ggplot2\", \"seaborn\", \"simple_white\", \"none\"\n",
    "    hovermode= \"x\",\n",
    "#    xaxis1 = dict(tickvals = x), xaxis2 = dict(tickvals = x), xaxis3 = dict(tickvals = x), xaxis4 = dict(tickvals = x), \n",
    "#    yaxis_range= [df_total.min().max(), df_total.max().max()],\n",
    "#    legend= dict(orientation= 'h', yanchor= \"top\", y= -0.1, xanchor= \"left\", x= 0.05),\n",
    "    showlegend= True,\n",
    "    )\n",
    "\n",
    "for ax in fig['layout']:\n",
    "    if ax[:5]== 'xaxis':\n",
    "        fig['layout'][ax]['tickvals']= x\n",
    "    if ax[:5]== 'yaxis':\n",
    "        fig['layout'][ax]['title']= unit\n",
    "\n",
    "file_future_by_scenario= 'WorldClim - future by scenario.png'\n",
    "fig.write_image(os.path.join(fld_out, file_future_by_scenario))# needs installation of \"plotly-orca\" or \"kaleido\"\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <a name=section08></a>9) Store outputs in excel file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "writer = pd.ExcelWriter(os.path.join(fld_out, 'worldclim - output.xlsx'), engine= 'xlsxwriter')\n",
    "workbook  = writer.book\n",
    "df_total.to_excel(writer, sheet_name='Data')\n",
    "df_stat.to_excel(writer, sheet_name='Stat')\n",
    "worksheet = writer.sheets['Data']\n",
    "if os.path.exists(os.path.join(fld_out, file_historical)):\n",
    "    worksheet.insert_image('R1', os.path.join(fld_out, file_historical))\n",
    "\n",
    "worksheet = workbook.add_worksheet('Graph')\n",
    "if os.path.exists(os.path.join(fld_out, file_future_by_year)):\n",
    "    worksheet.insert_image('A1', os.path.join(fld_out, file_future_by_year))\n",
    "if os.path.exists(os.path.join(fld_out, file_future_by_month)):\n",
    "    worksheet.insert_image('P1', os.path.join(fld_out, file_future_by_month))\n",
    "if os.path.exists(os.path.join(fld_out, file_future_by_scenario)):\n",
    "    worksheet.insert_image('A36', os.path.join(fld_out, file_future_by_scenario))\n",
    "writer.save()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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