{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>FECHA</th>\n",
       "      <th>St_100110</th>\n",
       "      <th>St_114035</th>\n",
       "      <th>St_114040</th>\n",
       "      <th>St_115044</th>\n",
       "      <th>St_115047</th>\n",
       "      <th>St_115049</th>\n",
       "      <th>St_115053</th>\n",
       "      <th>St_114041</th>\n",
       "      <th>St_116061</th>\n",
       "      <th>St_116060</th>\n",
       "      <th>St_114096</th>\n",
       "      <th>St_113119</th>\n",
       "      <th>St_116026</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1964-01-31</td>\n",
       "      <td>84.626944</td>\n",
       "      <td>96.514394</td>\n",
       "      <td>83.4</td>\n",
       "      <td>102.900000</td>\n",
       "      <td>52.1</td>\n",
       "      <td>208.7</td>\n",
       "      <td>92.3</td>\n",
       "      <td>84.52</td>\n",
       "      <td>96.514394</td>\n",
       "      <td>83.6</td>\n",
       "      <td>85.71</td>\n",
       "      <td>472.428075</td>\n",
       "      <td>48.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1964-02-29</td>\n",
       "      <td>95.000000</td>\n",
       "      <td>91.758561</td>\n",
       "      <td>57.1</td>\n",
       "      <td>102.800000</td>\n",
       "      <td>67.1</td>\n",
       "      <td>148.2</td>\n",
       "      <td>356.1</td>\n",
       "      <td>57.02</td>\n",
       "      <td>176.682811</td>\n",
       "      <td>115.6</td>\n",
       "      <td>137.01</td>\n",
       "      <td>712.369843</td>\n",
       "      <td>118.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1964-03-31</td>\n",
       "      <td>113.500000</td>\n",
       "      <td>134.639414</td>\n",
       "      <td>218.4</td>\n",
       "      <td>105.697742</td>\n",
       "      <td>101.1</td>\n",
       "      <td>272.7</td>\n",
       "      <td>235.3</td>\n",
       "      <td>104.55</td>\n",
       "      <td>178.468553</td>\n",
       "      <td>93.3</td>\n",
       "      <td>191.90</td>\n",
       "      <td>787.395604</td>\n",
       "      <td>107.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1964-04-30</td>\n",
       "      <td>53.500000</td>\n",
       "      <td>50.418601</td>\n",
       "      <td>17.3</td>\n",
       "      <td>64.365853</td>\n",
       "      <td>36.3</td>\n",
       "      <td>94.0</td>\n",
       "      <td>41.4</td>\n",
       "      <td>65.02</td>\n",
       "      <td>40.679108</td>\n",
       "      <td>52.2</td>\n",
       "      <td>60.80</td>\n",
       "      <td>431.680682</td>\n",
       "      <td>10.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1964-05-31</td>\n",
       "      <td>11.800000</td>\n",
       "      <td>3.526731</td>\n",
       "      <td>16.4</td>\n",
       "      <td>8.583089</td>\n",
       "      <td>12.3</td>\n",
       "      <td>67.8</td>\n",
       "      <td>31.0</td>\n",
       "      <td>13.51</td>\n",
       "      <td>35.234076</td>\n",
       "      <td>13.4</td>\n",
       "      <td>8.50</td>\n",
       "      <td>286.148643</td>\n",
       "      <td>22.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>655</th>\n",
       "      <td>2018-08-31</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>41.300000</td>\n",
       "      <td>18.6</td>\n",
       "      <td>4.259311</td>\n",
       "      <td>0.8</td>\n",
       "      <td>4.9</td>\n",
       "      <td>40.2</td>\n",
       "      <td>7.50</td>\n",
       "      <td>25.600000</td>\n",
       "      <td>7.0</td>\n",
       "      <td>36.90</td>\n",
       "      <td>334.200000</td>\n",
       "      <td>0.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>656</th>\n",
       "      <td>2018-09-30</td>\n",
       "      <td>3.600000</td>\n",
       "      <td>11.700000</td>\n",
       "      <td>14.4</td>\n",
       "      <td>0.537258</td>\n",
       "      <td>9.8</td>\n",
       "      <td>4.8</td>\n",
       "      <td>10.2</td>\n",
       "      <td>4.60</td>\n",
       "      <td>7.700000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.10</td>\n",
       "      <td>162.500000</td>\n",
       "      <td>0.6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>657</th>\n",
       "      <td>2018-10-31</td>\n",
       "      <td>45.500000</td>\n",
       "      <td>78.300000</td>\n",
       "      <td>92.9</td>\n",
       "      <td>69.809983</td>\n",
       "      <td>75.2</td>\n",
       "      <td>89.1</td>\n",
       "      <td>148.5</td>\n",
       "      <td>68.20</td>\n",
       "      <td>103.500000</td>\n",
       "      <td>87.5</td>\n",
       "      <td>55.10</td>\n",
       "      <td>692.500000</td>\n",
       "      <td>43.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>658</th>\n",
       "      <td>2018-11-30</td>\n",
       "      <td>22.700000</td>\n",
       "      <td>57.556963</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>23.6</td>\n",
       "      <td>8.5</td>\n",
       "      <td>48.8</td>\n",
       "      <td>73.50</td>\n",
       "      <td>12.200000</td>\n",
       "      <td>48.4</td>\n",
       "      <td>41.80</td>\n",
       "      <td>582.100000</td>\n",
       "      <td>14.4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>659</th>\n",
       "      <td>2018-12-31</td>\n",
       "      <td>89.800000</td>\n",
       "      <td>53.300000</td>\n",
       "      <td>58.2</td>\n",
       "      <td>46.400000</td>\n",
       "      <td>79.8</td>\n",
       "      <td>89.4</td>\n",
       "      <td>98.2</td>\n",
       "      <td>68.90</td>\n",
       "      <td>72.100000</td>\n",
       "      <td>98.3</td>\n",
       "      <td>50.00</td>\n",
       "      <td>1234.400000</td>\n",
       "      <td>93.6</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>660 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         FECHA   St_100110   St_114035  St_114040   St_115044  St_115047  \\\n",
       "0   1964-01-31   84.626944   96.514394       83.4  102.900000       52.1   \n",
       "1   1964-02-29   95.000000   91.758561       57.1  102.800000       67.1   \n",
       "2   1964-03-31  113.500000  134.639414      218.4  105.697742      101.1   \n",
       "3   1964-04-30   53.500000   50.418601       17.3   64.365853       36.3   \n",
       "4   1964-05-31   11.800000    3.526731       16.4    8.583089       12.3   \n",
       "..         ...         ...         ...        ...         ...        ...   \n",
       "655 2018-08-31    0.000000   41.300000       18.6    4.259311        0.8   \n",
       "656 2018-09-30    3.600000   11.700000       14.4    0.537258        9.8   \n",
       "657 2018-10-31   45.500000   78.300000       92.9   69.809983       75.2   \n",
       "658 2018-11-30   22.700000   57.556963       61.0    0.800000       23.6   \n",
       "659 2018-12-31   89.800000   53.300000       58.2   46.400000       79.8   \n",
       "\n",
       "     St_115049  St_115053  St_114041   St_116061  St_116060  St_114096  \\\n",
       "0        208.7       92.3      84.52   96.514394       83.6      85.71   \n",
       "1        148.2      356.1      57.02  176.682811      115.6     137.01   \n",
       "2        272.7      235.3     104.55  178.468553       93.3     191.90   \n",
       "3         94.0       41.4      65.02   40.679108       52.2      60.80   \n",
       "4         67.8       31.0      13.51   35.234076       13.4       8.50   \n",
       "..         ...        ...        ...         ...        ...        ...   \n",
       "655        4.9       40.2       7.50   25.600000        7.0      36.90   \n",
       "656        4.8       10.2       4.60    7.700000        0.0      18.10   \n",
       "657       89.1      148.5      68.20  103.500000       87.5      55.10   \n",
       "658        8.5       48.8      73.50   12.200000       48.4      41.80   \n",
       "659       89.4       98.2      68.90   72.100000       98.3      50.00   \n",
       "\n",
       "       St_113119  St_116026  \n",
       "0     472.428075       48.2  \n",
       "1     712.369843      118.4  \n",
       "2     787.395604      107.6  \n",
       "3     431.680682       10.6  \n",
       "4     286.148643       22.2  \n",
       "..           ...        ...  \n",
       "655   334.200000        0.2  \n",
       "656   162.500000        0.6  \n",
       "657   692.500000       43.2  \n",
       "658   582.100000       14.4  \n",
       "659  1234.400000       93.6  \n",
       "\n",
       "[660 rows x 14 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "file=\"datos_puno_eofs.xlsx\"\n",
    "data=pd.read_excel(file,\"DATOS\")\n",
    "location=pd.read_excel(file,\"UBICACIONES\")\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>St_100110</th>\n",
       "      <th>St_114035</th>\n",
       "      <th>St_114040</th>\n",
       "      <th>St_115044</th>\n",
       "      <th>St_115047</th>\n",
       "      <th>St_115049</th>\n",
       "      <th>St_115053</th>\n",
       "      <th>St_114041</th>\n",
       "      <th>St_116061</th>\n",
       "      <th>St_116060</th>\n",
       "      <th>St_114096</th>\n",
       "      <th>St_113119</th>\n",
       "      <th>St_116026</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FECHA</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>1981-01-31</th>\n",
       "      <td>-0.598431</td>\n",
       "      <td>0.450941</td>\n",
       "      <td>0.270782</td>\n",
       "      <td>1.258765</td>\n",
       "      <td>0.087764</td>\n",
       "      <td>-0.168002</td>\n",
       "      <td>0.911179</td>\n",
       "      <td>-0.316582</td>\n",
       "      <td>0.267563</td>\n",
       "      <td>0.325020</td>\n",
       "      <td>0.012904</td>\n",
       "      <td>-0.517624</td>\n",
       "      <td>-0.157935</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1982-01-31</th>\n",
       "      <td>0.862452</td>\n",
       "      <td>-0.115367</td>\n",
       "      <td>1.430030</td>\n",
       "      <td>1.451956</td>\n",
       "      <td>0.307308</td>\n",
       "      <td>1.111983</td>\n",
       "      <td>0.884278</td>\n",
       "      <td>-1.830612</td>\n",
       "      <td>0.925249</td>\n",
       "      <td>1.251191</td>\n",
       "      <td>0.455256</td>\n",
       "      <td>-0.285717</td>\n",
       "      <td>0.618310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1983-01-31</th>\n",
       "      <td>-2.299789</td>\n",
       "      <td>-2.225956</td>\n",
       "      <td>-1.424912</td>\n",
       "      <td>-1.826409</td>\n",
       "      <td>-0.405655</td>\n",
       "      <td>-1.479938</td>\n",
       "      <td>-1.178808</td>\n",
       "      <td>-1.093931</td>\n",
       "      <td>-1.327579</td>\n",
       "      <td>-1.680938</td>\n",
       "      <td>-1.205280</td>\n",
       "      <td>-0.725350</td>\n",
       "      <td>-1.583092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1984-01-31</th>\n",
       "      <td>2.182057</td>\n",
       "      <td>1.452872</td>\n",
       "      <td>-0.741924</td>\n",
       "      <td>0.423061</td>\n",
       "      <td>2.272501</td>\n",
       "      <td>1.525333</td>\n",
       "      <td>2.905979</td>\n",
       "      <td>0.996771</td>\n",
       "      <td>1.728549</td>\n",
       "      <td>2.652782</td>\n",
       "      <td>0.932482</td>\n",
       "      <td>-0.229755</td>\n",
       "      <td>1.670679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1985-01-31</th>\n",
       "      <td>-0.657047</td>\n",
       "      <td>-0.862459</td>\n",
       "      <td>0.156346</td>\n",
       "      <td>-1.396555</td>\n",
       "      <td>0.143710</td>\n",
       "      <td>2.415932</td>\n",
       "      <td>0.687695</td>\n",
       "      <td>0.239413</td>\n",
       "      <td>-1.046298</td>\n",
       "      <td>-0.619092</td>\n",
       "      <td>2.119802</td>\n",
       "      <td>-1.105106</td>\n",
       "      <td>-0.211114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1986-01-31</th>\n",
       "      <td>-0.430099</td>\n",
       "      <td>-1.180463</td>\n",
       "      <td>-0.072020</td>\n",
       "      <td>-0.141069</td>\n",
       "      <td>1.016232</td>\n",
       "      <td>2.557043</td>\n",
       "      <td>-0.212448</td>\n",
       "      <td>-0.848858</td>\n",
       "      <td>-1.011967</td>\n",
       "      <td>0.219620</td>\n",
       "      <td>0.521683</td>\n",
       "      <td>-0.360102</td>\n",
       "      <td>0.314292</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1987-01-31</th>\n",
       "      <td>0.760251</td>\n",
       "      <td>-0.923446</td>\n",
       "      <td>-0.451458</td>\n",
       "      <td>0.906289</td>\n",
       "      <td>2.852163</td>\n",
       "      <td>1.864133</td>\n",
       "      <td>0.609062</td>\n",
       "      <td>0.839992</td>\n",
       "      <td>1.091269</td>\n",
       "      <td>1.692973</td>\n",
       "      <td>1.353045</td>\n",
       "      <td>-0.992722</td>\n",
       "      <td>0.654168</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1988-01-31</th>\n",
       "      <td>0.593421</td>\n",
       "      <td>1.049922</td>\n",
       "      <td>0.307418</td>\n",
       "      <td>1.084038</td>\n",
       "      <td>-0.504622</td>\n",
       "      <td>-0.428259</td>\n",
       "      <td>0.660795</td>\n",
       "      <td>-0.098192</td>\n",
       "      <td>1.142318</td>\n",
       "      <td>0.434904</td>\n",
       "      <td>1.679469</td>\n",
       "      <td>-1.628105</td>\n",
       "      <td>-0.840976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1989-01-31</th>\n",
       "      <td>0.452142</td>\n",
       "      <td>0.069772</td>\n",
       "      <td>0.380688</td>\n",
       "      <td>0.461330</td>\n",
       "      <td>-0.359000</td>\n",
       "      <td>0.020368</td>\n",
       "      <td>-1.276065</td>\n",
       "      <td>-0.239794</td>\n",
       "      <td>-0.645687</td>\n",
       "      <td>-0.711037</td>\n",
       "      <td>-0.231473</td>\n",
       "      <td>-0.194750</td>\n",
       "      <td>0.014951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-01-31</th>\n",
       "      <td>-0.097943</td>\n",
       "      <td>-0.132792</td>\n",
       "      <td>-0.145291</td>\n",
       "      <td>0.501613</td>\n",
       "      <td>0.448689</td>\n",
       "      <td>0.318565</td>\n",
       "      <td>-0.498010</td>\n",
       "      <td>0.783456</td>\n",
       "      <td>-0.239845</td>\n",
       "      <td>-0.466599</td>\n",
       "      <td>-0.443989</td>\n",
       "      <td>-0.445350</td>\n",
       "      <td>-1.372618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-01-31</th>\n",
       "      <td>-0.745722</td>\n",
       "      <td>0.823398</td>\n",
       "      <td>0.451342</td>\n",
       "      <td>-0.229859</td>\n",
       "      <td>0.495143</td>\n",
       "      <td>-0.227242</td>\n",
       "      <td>-0.709078</td>\n",
       "      <td>-0.374489</td>\n",
       "      <td>-0.812874</td>\n",
       "      <td>-0.918472</td>\n",
       "      <td>1.908986</td>\n",
       "      <td>-0.823579</td>\n",
       "      <td>-0.867481</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1992-01-31</th>\n",
       "      <td>-1.618945</td>\n",
       "      <td>-0.953940</td>\n",
       "      <td>-0.063138</td>\n",
       "      <td>-1.250530</td>\n",
       "      <td>-0.130973</td>\n",
       "      <td>-0.394978</td>\n",
       "      <td>0.356608</td>\n",
       "      <td>-0.348086</td>\n",
       "      <td>-0.657174</td>\n",
       "      <td>-0.089851</td>\n",
       "      <td>-1.489566</td>\n",
       "      <td>-0.393276</td>\n",
       "      <td>-1.254129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1993-01-31</th>\n",
       "      <td>0.028306</td>\n",
       "      <td>0.649149</td>\n",
       "      <td>1.424796</td>\n",
       "      <td>0.793664</td>\n",
       "      <td>0.107355</td>\n",
       "      <td>-0.323757</td>\n",
       "      <td>0.379371</td>\n",
       "      <td>-0.155684</td>\n",
       "      <td>0.112396</td>\n",
       "      <td>0.262228</td>\n",
       "      <td>-0.222972</td>\n",
       "      <td>-0.227343</td>\n",
       "      <td>0.202039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1994-01-31</th>\n",
       "      <td>0.094436</td>\n",
       "      <td>1.215458</td>\n",
       "      <td>-0.443608</td>\n",
       "      <td>1.488546</td>\n",
       "      <td>-0.072400</td>\n",
       "      <td>-0.532096</td>\n",
       "      <td>-0.893245</td>\n",
       "      <td>-0.335507</td>\n",
       "      <td>-0.310038</td>\n",
       "      <td>-0.717764</td>\n",
       "      <td>0.338069</td>\n",
       "      <td>-0.214326</td>\n",
       "      <td>-0.457446</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-01-31</th>\n",
       "      <td>-0.766763</td>\n",
       "      <td>-0.738307</td>\n",
       "      <td>-1.767715</td>\n",
       "      <td>-1.059353</td>\n",
       "      <td>-0.171367</td>\n",
       "      <td>-1.167097</td>\n",
       "      <td>-0.028280</td>\n",
       "      <td>-1.504149</td>\n",
       "      <td>-1.045149</td>\n",
       "      <td>-0.739068</td>\n",
       "      <td>-1.275350</td>\n",
       "      <td>0.774100</td>\n",
       "      <td>-0.946993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1996-01-31</th>\n",
       "      <td>1.187093</td>\n",
       "      <td>0.187390</td>\n",
       "      <td>0.116390</td>\n",
       "      <td>0.823877</td>\n",
       "      <td>-1.413499</td>\n",
       "      <td>-0.240555</td>\n",
       "      <td>-0.564228</td>\n",
       "      <td>0.393120</td>\n",
       "      <td>-0.195176</td>\n",
       "      <td>0.345203</td>\n",
       "      <td>0.101752</td>\n",
       "      <td>0.434185</td>\n",
       "      <td>0.665082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1997-01-31</th>\n",
       "      <td>0.990204</td>\n",
       "      <td>1.121799</td>\n",
       "      <td>1.380311</td>\n",
       "      <td>0.352230</td>\n",
       "      <td>0.929384</td>\n",
       "      <td>-0.514790</td>\n",
       "      <td>0.128986</td>\n",
       "      <td>0.580008</td>\n",
       "      <td>0.680321</td>\n",
       "      <td>0.514515</td>\n",
       "      <td>1.026620</td>\n",
       "      <td>-0.750912</td>\n",
       "      <td>1.673797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1998-01-31</th>\n",
       "      <td>0.340923</td>\n",
       "      <td>-0.542277</td>\n",
       "      <td>-0.964353</td>\n",
       "      <td>0.169446</td>\n",
       "      <td>-0.415754</td>\n",
       "      <td>-0.576693</td>\n",
       "      <td>-1.487133</td>\n",
       "      <td>-0.730574</td>\n",
       "      <td>-1.000481</td>\n",
       "      <td>-1.044055</td>\n",
       "      <td>-1.033932</td>\n",
       "      <td>1.095591</td>\n",
       "      <td>-0.117570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1999-01-31</th>\n",
       "      <td>0.291325</td>\n",
       "      <td>-0.860281</td>\n",
       "      <td>-0.770709</td>\n",
       "      <td>-1.109539</td>\n",
       "      <td>-0.900488</td>\n",
       "      <td>-0.394978</td>\n",
       "      <td>-0.595267</td>\n",
       "      <td>-0.617022</td>\n",
       "      <td>-0.664576</td>\n",
       "      <td>0.271199</td>\n",
       "      <td>-0.590199</td>\n",
       "      <td>2.183504</td>\n",
       "      <td>0.081991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2000-01-31</th>\n",
       "      <td>-0.099446</td>\n",
       "      <td>0.649149</td>\n",
       "      <td>-0.265664</td>\n",
       "      <td>0.404262</td>\n",
       "      <td>-0.185505</td>\n",
       "      <td>-0.599989</td>\n",
       "      <td>-0.202101</td>\n",
       "      <td>0.154187</td>\n",
       "      <td>0.823259</td>\n",
       "      <td>0.160193</td>\n",
       "      <td>0.134054</td>\n",
       "      <td>0.230143</td>\n",
       "      <td>0.704058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2001-01-31</th>\n",
       "      <td>1.158537</td>\n",
       "      <td>1.851466</td>\n",
       "      <td>0.385922</td>\n",
       "      <td>1.288810</td>\n",
       "      <td>-0.654082</td>\n",
       "      <td>0.613435</td>\n",
       "      <td>0.209688</td>\n",
       "      <td>1.644560</td>\n",
       "      <td>1.444786</td>\n",
       "      <td>1.706428</td>\n",
       "      <td>1.237436</td>\n",
       "      <td>1.163758</td>\n",
       "      <td>2.076036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-31</th>\n",
       "      <td>-0.663059</td>\n",
       "      <td>0.069772</td>\n",
       "      <td>-0.524729</td>\n",
       "      <td>-1.022091</td>\n",
       "      <td>-1.021672</td>\n",
       "      <td>-0.341729</td>\n",
       "      <td>-1.474717</td>\n",
       "      <td>0.745605</td>\n",
       "      <td>-0.829465</td>\n",
       "      <td>-0.900532</td>\n",
       "      <td>-1.169942</td>\n",
       "      <td>-0.048974</td>\n",
       "      <td>-0.996883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2003-01-31</th>\n",
       "      <td>0.011773</td>\n",
       "      <td>-0.341891</td>\n",
       "      <td>1.165732</td>\n",
       "      <td>-0.876233</td>\n",
       "      <td>1.066725</td>\n",
       "      <td>-0.216592</td>\n",
       "      <td>0.393856</td>\n",
       "      <td>0.568180</td>\n",
       "      <td>0.241296</td>\n",
       "      <td>-0.178432</td>\n",
       "      <td>-0.445689</td>\n",
       "      <td>0.134341</td>\n",
       "      <td>-0.483950</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2004-01-31</th>\n",
       "      <td>0.528794</td>\n",
       "      <td>1.350501</td>\n",
       "      <td>2.704418</td>\n",
       "      <td>-0.178163</td>\n",
       "      <td>0.262874</td>\n",
       "      <td>0.485636</td>\n",
       "      <td>1.778213</td>\n",
       "      <td>2.401575</td>\n",
       "      <td>1.419261</td>\n",
       "      <td>0.407994</td>\n",
       "      <td>-0.362383</td>\n",
       "      <td>-0.957947</td>\n",
       "      <td>0.131881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2005-01-31</th>\n",
       "      <td>-1.058339</td>\n",
       "      <td>-1.426590</td>\n",
       "      <td>-2.212573</td>\n",
       "      <td>-1.638086</td>\n",
       "      <td>-1.328670</td>\n",
       "      <td>-0.428259</td>\n",
       "      <td>-0.131745</td>\n",
       "      <td>-1.972552</td>\n",
       "      <td>-0.914973</td>\n",
       "      <td>-1.005931</td>\n",
       "      <td>-1.214146</td>\n",
       "      <td>-0.576119</td>\n",
       "      <td>-0.391965</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2006-01-31</th>\n",
       "      <td>1.764232</td>\n",
       "      <td>0.766767</td>\n",
       "      <td>0.244614</td>\n",
       "      <td>-0.007631</td>\n",
       "      <td>0.876871</td>\n",
       "      <td>0.354509</td>\n",
       "      <td>1.591977</td>\n",
       "      <td>1.486297</td>\n",
       "      <td>1.740872</td>\n",
       "      <td>1.141306</td>\n",
       "      <td>0.392473</td>\n",
       "      <td>-0.278347</td>\n",
       "      <td>2.138399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2007-01-31</th>\n",
       "      <td>-1.336388</td>\n",
       "      <td>-1.263231</td>\n",
       "      <td>-0.179309</td>\n",
       "      <td>-1.008496</td>\n",
       "      <td>-1.110540</td>\n",
       "      <td>-0.817647</td>\n",
       "      <td>-0.214517</td>\n",
       "      <td>-0.683024</td>\n",
       "      <td>-1.706111</td>\n",
       "      <td>-1.721303</td>\n",
       "      <td>-0.860519</td>\n",
       "      <td>0.088742</td>\n",
       "      <td>-0.731842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-31</th>\n",
       "      <td>0.540817</td>\n",
       "      <td>0.019676</td>\n",
       "      <td>-0.176693</td>\n",
       "      <td>0.790811</td>\n",
       "      <td>0.198243</td>\n",
       "      <td>-0.924146</td>\n",
       "      <td>-0.504218</td>\n",
       "      <td>-0.650141</td>\n",
       "      <td>1.092545</td>\n",
       "      <td>0.217377</td>\n",
       "      <td>-0.336881</td>\n",
       "      <td>3.281319</td>\n",
       "      <td>0.936359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2009-01-31</th>\n",
       "      <td>-0.296335</td>\n",
       "      <td>-0.860281</td>\n",
       "      <td>-0.652953</td>\n",
       "      <td>-1.126324</td>\n",
       "      <td>-1.558919</td>\n",
       "      <td>-1.088554</td>\n",
       "      <td>-1.139491</td>\n",
       "      <td>0.097411</td>\n",
       "      <td>-0.626544</td>\n",
       "      <td>-0.657215</td>\n",
       "      <td>-0.506893</td>\n",
       "      <td>0.939912</td>\n",
       "      <td>-0.987529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-31</th>\n",
       "      <td>-1.118458</td>\n",
       "      <td>0.699246</td>\n",
       "      <td>0.438258</td>\n",
       "      <td>0.671641</td>\n",
       "      <td>-0.831817</td>\n",
       "      <td>-0.401635</td>\n",
       "      <td>-0.388338</td>\n",
       "      <td>0.868620</td>\n",
       "      <td>0.324251</td>\n",
       "      <td>-0.152643</td>\n",
       "      <td>-0.824817</td>\n",
       "      <td>0.429809</td>\n",
       "      <td>-0.480520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            St_100110  St_114035  St_114040  St_115044  St_115047  St_115049  \\\n",
       "FECHA                                                                          \n",
       "1981-01-31  -0.598431   0.450941   0.270782   1.258765   0.087764  -0.168002   \n",
       "1982-01-31   0.862452  -0.115367   1.430030   1.451956   0.307308   1.111983   \n",
       "1983-01-31  -2.299789  -2.225956  -1.424912  -1.826409  -0.405655  -1.479938   \n",
       "1984-01-31   2.182057   1.452872  -0.741924   0.423061   2.272501   1.525333   \n",
       "1985-01-31  -0.657047  -0.862459   0.156346  -1.396555   0.143710   2.415932   \n",
       "1986-01-31  -0.430099  -1.180463  -0.072020  -0.141069   1.016232   2.557043   \n",
       "1987-01-31   0.760251  -0.923446  -0.451458   0.906289   2.852163   1.864133   \n",
       "1988-01-31   0.593421   1.049922   0.307418   1.084038  -0.504622  -0.428259   \n",
       "1989-01-31   0.452142   0.069772   0.380688   0.461330  -0.359000   0.020368   \n",
       "1990-01-31  -0.097943  -0.132792  -0.145291   0.501613   0.448689   0.318565   \n",
       "1991-01-31  -0.745722   0.823398   0.451342  -0.229859   0.495143  -0.227242   \n",
       "1992-01-31  -1.618945  -0.953940  -0.063138  -1.250530  -0.130973  -0.394978   \n",
       "1993-01-31   0.028306   0.649149   1.424796   0.793664   0.107355  -0.323757   \n",
       "1994-01-31   0.094436   1.215458  -0.443608   1.488546  -0.072400  -0.532096   \n",
       "1995-01-31  -0.766763  -0.738307  -1.767715  -1.059353  -0.171367  -1.167097   \n",
       "1996-01-31   1.187093   0.187390   0.116390   0.823877  -1.413499  -0.240555   \n",
       "1997-01-31   0.990204   1.121799   1.380311   0.352230   0.929384  -0.514790   \n",
       "1998-01-31   0.340923  -0.542277  -0.964353   0.169446  -0.415754  -0.576693   \n",
       "1999-01-31   0.291325  -0.860281  -0.770709  -1.109539  -0.900488  -0.394978   \n",
       "2000-01-31  -0.099446   0.649149  -0.265664   0.404262  -0.185505  -0.599989   \n",
       "2001-01-31   1.158537   1.851466   0.385922   1.288810  -0.654082   0.613435   \n",
       "2002-01-31  -0.663059   0.069772  -0.524729  -1.022091  -1.021672  -0.341729   \n",
       "2003-01-31   0.011773  -0.341891   1.165732  -0.876233   1.066725  -0.216592   \n",
       "2004-01-31   0.528794   1.350501   2.704418  -0.178163   0.262874   0.485636   \n",
       "2005-01-31  -1.058339  -1.426590  -2.212573  -1.638086  -1.328670  -0.428259   \n",
       "2006-01-31   1.764232   0.766767   0.244614  -0.007631   0.876871   0.354509   \n",
       "2007-01-31  -1.336388  -1.263231  -0.179309  -1.008496  -1.110540  -0.817647   \n",
       "2008-01-31   0.540817   0.019676  -0.176693   0.790811   0.198243  -0.924146   \n",
       "2009-01-31  -0.296335  -0.860281  -0.652953  -1.126324  -1.558919  -1.088554   \n",
       "2010-01-31  -1.118458   0.699246   0.438258   0.671641  -0.831817  -0.401635   \n",
       "\n",
       "            St_115053  St_114041  St_116061  St_116060  St_114096  St_113119  \\\n",
       "FECHA                                                                          \n",
       "1981-01-31   0.911179  -0.316582   0.267563   0.325020   0.012904  -0.517624   \n",
       "1982-01-31   0.884278  -1.830612   0.925249   1.251191   0.455256  -0.285717   \n",
       "1983-01-31  -1.178808  -1.093931  -1.327579  -1.680938  -1.205280  -0.725350   \n",
       "1984-01-31   2.905979   0.996771   1.728549   2.652782   0.932482  -0.229755   \n",
       "1985-01-31   0.687695   0.239413  -1.046298  -0.619092   2.119802  -1.105106   \n",
       "1986-01-31  -0.212448  -0.848858  -1.011967   0.219620   0.521683  -0.360102   \n",
       "1987-01-31   0.609062   0.839992   1.091269   1.692973   1.353045  -0.992722   \n",
       "1988-01-31   0.660795  -0.098192   1.142318   0.434904   1.679469  -1.628105   \n",
       "1989-01-31  -1.276065  -0.239794  -0.645687  -0.711037  -0.231473  -0.194750   \n",
       "1990-01-31  -0.498010   0.783456  -0.239845  -0.466599  -0.443989  -0.445350   \n",
       "1991-01-31  -0.709078  -0.374489  -0.812874  -0.918472   1.908986  -0.823579   \n",
       "1992-01-31   0.356608  -0.348086  -0.657174  -0.089851  -1.489566  -0.393276   \n",
       "1993-01-31   0.379371  -0.155684   0.112396   0.262228  -0.222972  -0.227343   \n",
       "1994-01-31  -0.893245  -0.335507  -0.310038  -0.717764   0.338069  -0.214326   \n",
       "1995-01-31  -0.028280  -1.504149  -1.045149  -0.739068  -1.275350   0.774100   \n",
       "1996-01-31  -0.564228   0.393120  -0.195176   0.345203   0.101752   0.434185   \n",
       "1997-01-31   0.128986   0.580008   0.680321   0.514515   1.026620  -0.750912   \n",
       "1998-01-31  -1.487133  -0.730574  -1.000481  -1.044055  -1.033932   1.095591   \n",
       "1999-01-31  -0.595267  -0.617022  -0.664576   0.271199  -0.590199   2.183504   \n",
       "2000-01-31  -0.202101   0.154187   0.823259   0.160193   0.134054   0.230143   \n",
       "2001-01-31   0.209688   1.644560   1.444786   1.706428   1.237436   1.163758   \n",
       "2002-01-31  -1.474717   0.745605  -0.829465  -0.900532  -1.169942  -0.048974   \n",
       "2003-01-31   0.393856   0.568180   0.241296  -0.178432  -0.445689   0.134341   \n",
       "2004-01-31   1.778213   2.401575   1.419261   0.407994  -0.362383  -0.957947   \n",
       "2005-01-31  -0.131745  -1.972552  -0.914973  -1.005931  -1.214146  -0.576119   \n",
       "2006-01-31   1.591977   1.486297   1.740872   1.141306   0.392473  -0.278347   \n",
       "2007-01-31  -0.214517  -0.683024  -1.706111  -1.721303  -0.860519   0.088742   \n",
       "2008-01-31  -0.504218  -0.650141   1.092545   0.217377  -0.336881   3.281319   \n",
       "2009-01-31  -1.139491   0.097411  -0.626544  -0.657215  -0.506893   0.939912   \n",
       "2010-01-31  -0.388338   0.868620   0.324251  -0.152643  -0.824817   0.429809   \n",
       "\n",
       "            St_116026  \n",
       "FECHA                  \n",
       "1981-01-31  -0.157935  \n",
       "1982-01-31   0.618310  \n",
       "1983-01-31  -1.583092  \n",
       "1984-01-31   1.670679  \n",
       "1985-01-31  -0.211114  \n",
       "1986-01-31   0.314292  \n",
       "1987-01-31   0.654168  \n",
       "1988-01-31  -0.840976  \n",
       "1989-01-31   0.014951  \n",
       "1990-01-31  -1.372618  \n",
       "1991-01-31  -0.867481  \n",
       "1992-01-31  -1.254129  \n",
       "1993-01-31   0.202039  \n",
       "1994-01-31  -0.457446  \n",
       "1995-01-31  -0.946993  \n",
       "1996-01-31   0.665082  \n",
       "1997-01-31   1.673797  \n",
       "1998-01-31  -0.117570  \n",
       "1999-01-31   0.081991  \n",
       "2000-01-31   0.704058  \n",
       "2001-01-31   2.076036  \n",
       "2002-01-31  -0.996883  \n",
       "2003-01-31  -0.483950  \n",
       "2004-01-31   0.131881  \n",
       "2005-01-31  -0.391965  \n",
       "2006-01-31   2.138399  \n",
       "2007-01-31  -0.731842  \n",
       "2008-01-31   0.936359  \n",
       "2009-01-31  -0.987529  \n",
       "2010-01-31  -0.480520  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_idx=data.set_index(\"FECHA\")\n",
    "\n",
    "data_ene=data_idx.loc[data_idx.index.month==1]\n",
    "data_ene_c=data_ene.loc['1981-01-31':'2010-01-31']\n",
    "data_ene_c_anomstd=(data_ene_c-data_ene_c.mean())/data_ene_c.std()\n",
    "data_ene_c_anomstd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='FECHA'>"
      ]
     },
     "execution_count": 3,
     "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": [
    "data_ene_c_anomstd.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='FECHA'>"
      ]
     },
     "execution_count": 4,
     "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": [
    "data_ene_c_anomstd[\"St_114035\"].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "serite_totest=data_ene_c_anomstd[\"St_114035\"].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "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>St_100110</th>\n",
       "      <th>St_114035</th>\n",
       "      <th>St_114040</th>\n",
       "      <th>St_115044</th>\n",
       "      <th>St_115047</th>\n",
       "      <th>St_115049</th>\n",
       "      <th>St_115053</th>\n",
       "      <th>St_114041</th>\n",
       "      <th>St_116061</th>\n",
       "      <th>St_116060</th>\n",
       "      <th>St_114096</th>\n",
       "      <th>St_113119</th>\n",
       "      <th>St_116026</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>St_100110</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.629861</td>\n",
       "      <td>0.332420</td>\n",
       "      <td>0.601013</td>\n",
       "      <td>0.416222</td>\n",
       "      <td>0.361288</td>\n",
       "      <td>0.476992</td>\n",
       "      <td>0.462739</td>\n",
       "      <td>0.751934</td>\n",
       "      <td>0.783895</td>\n",
       "      <td>0.488273</td>\n",
       "      <td>0.125042</td>\n",
       "      <td>0.807443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_114035</th>\n",
       "      <td>0.629861</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.546897</td>\n",
       "      <td>0.687446</td>\n",
       "      <td>0.185422</td>\n",
       "      <td>0.076623</td>\n",
       "      <td>0.390872</td>\n",
       "      <td>0.606815</td>\n",
       "      <td>0.710011</td>\n",
       "      <td>0.540898</td>\n",
       "      <td>0.464672</td>\n",
       "      <td>-0.061753</td>\n",
       "      <td>0.527514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_114040</th>\n",
       "      <td>0.332420</td>\n",
       "      <td>0.546897</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.421828</td>\n",
       "      <td>0.236277</td>\n",
       "      <td>0.244863</td>\n",
       "      <td>0.375204</td>\n",
       "      <td>0.507141</td>\n",
       "      <td>0.475271</td>\n",
       "      <td>0.331629</td>\n",
       "      <td>0.344864</td>\n",
       "      <td>-0.243367</td>\n",
       "      <td>0.291855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_115044</th>\n",
       "      <td>0.601013</td>\n",
       "      <td>0.687446</td>\n",
       "      <td>0.421828</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.279347</td>\n",
       "      <td>0.201899</td>\n",
       "      <td>0.210275</td>\n",
       "      <td>0.242376</td>\n",
       "      <td>0.627982</td>\n",
       "      <td>0.564902</td>\n",
       "      <td>0.444377</td>\n",
       "      <td>0.012843</td>\n",
       "      <td>0.486128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_115047</th>\n",
       "      <td>0.416222</td>\n",
       "      <td>0.185422</td>\n",
       "      <td>0.236277</td>\n",
       "      <td>0.279347</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.593086</td>\n",
       "      <td>0.580775</td>\n",
       "      <td>0.282494</td>\n",
       "      <td>0.483325</td>\n",
       "      <td>0.585901</td>\n",
       "      <td>0.471526</td>\n",
       "      <td>-0.305812</td>\n",
       "      <td>0.396454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_115049</th>\n",
       "      <td>0.361288</td>\n",
       "      <td>0.076623</td>\n",
       "      <td>0.244863</td>\n",
       "      <td>0.201899</td>\n",
       "      <td>0.593086</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.501784</td>\n",
       "      <td>0.264727</td>\n",
       "      <td>0.259072</td>\n",
       "      <td>0.538204</td>\n",
       "      <td>0.592761</td>\n",
       "      <td>-0.346119</td>\n",
       "      <td>0.390298</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_115053</th>\n",
       "      <td>0.476992</td>\n",
       "      <td>0.390872</td>\n",
       "      <td>0.375204</td>\n",
       "      <td>0.210275</td>\n",
       "      <td>0.580775</td>\n",
       "      <td>0.501784</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.382008</td>\n",
       "      <td>0.674296</td>\n",
       "      <td>0.725804</td>\n",
       "      <td>0.387784</td>\n",
       "      <td>-0.339100</td>\n",
       "      <td>0.493985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_114041</th>\n",
       "      <td>0.462739</td>\n",
       "      <td>0.606815</td>\n",
       "      <td>0.507141</td>\n",
       "      <td>0.242376</td>\n",
       "      <td>0.282494</td>\n",
       "      <td>0.264727</td>\n",
       "      <td>0.382008</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.583631</td>\n",
       "      <td>0.455593</td>\n",
       "      <td>0.297647</td>\n",
       "      <td>-0.138819</td>\n",
       "      <td>0.388847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_116061</th>\n",
       "      <td>0.751934</td>\n",
       "      <td>0.710011</td>\n",
       "      <td>0.475271</td>\n",
       "      <td>0.627982</td>\n",
       "      <td>0.483325</td>\n",
       "      <td>0.259072</td>\n",
       "      <td>0.674296</td>\n",
       "      <td>0.583631</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.851848</td>\n",
       "      <td>0.429941</td>\n",
       "      <td>-0.013761</td>\n",
       "      <td>0.708373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_116060</th>\n",
       "      <td>0.783895</td>\n",
       "      <td>0.540898</td>\n",
       "      <td>0.331629</td>\n",
       "      <td>0.564902</td>\n",
       "      <td>0.585901</td>\n",
       "      <td>0.538204</td>\n",
       "      <td>0.725804</td>\n",
       "      <td>0.455593</td>\n",
       "      <td>0.851848</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.497512</td>\n",
       "      <td>-0.001259</td>\n",
       "      <td>0.769890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_114096</th>\n",
       "      <td>0.488273</td>\n",
       "      <td>0.464672</td>\n",
       "      <td>0.344864</td>\n",
       "      <td>0.444377</td>\n",
       "      <td>0.471526</td>\n",
       "      <td>0.592761</td>\n",
       "      <td>0.387784</td>\n",
       "      <td>0.297647</td>\n",
       "      <td>0.429941</td>\n",
       "      <td>0.497512</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.365260</td>\n",
       "      <td>0.453235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_113119</th>\n",
       "      <td>0.125042</td>\n",
       "      <td>-0.061753</td>\n",
       "      <td>-0.243367</td>\n",
       "      <td>0.012843</td>\n",
       "      <td>-0.305812</td>\n",
       "      <td>-0.346119</td>\n",
       "      <td>-0.339100</td>\n",
       "      <td>-0.138819</td>\n",
       "      <td>-0.013761</td>\n",
       "      <td>-0.001259</td>\n",
       "      <td>-0.365260</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.195365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_116026</th>\n",
       "      <td>0.807443</td>\n",
       "      <td>0.527514</td>\n",
       "      <td>0.291855</td>\n",
       "      <td>0.486128</td>\n",
       "      <td>0.396454</td>\n",
       "      <td>0.390298</td>\n",
       "      <td>0.493985</td>\n",
       "      <td>0.388847</td>\n",
       "      <td>0.708373</td>\n",
       "      <td>0.769890</td>\n",
       "      <td>0.453235</td>\n",
       "      <td>0.195365</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           St_100110  St_114035  St_114040  St_115044  St_115047  St_115049  \\\n",
       "St_100110   1.000000   0.629861   0.332420   0.601013   0.416222   0.361288   \n",
       "St_114035   0.629861   1.000000   0.546897   0.687446   0.185422   0.076623   \n",
       "St_114040   0.332420   0.546897   1.000000   0.421828   0.236277   0.244863   \n",
       "St_115044   0.601013   0.687446   0.421828   1.000000   0.279347   0.201899   \n",
       "St_115047   0.416222   0.185422   0.236277   0.279347   1.000000   0.593086   \n",
       "St_115049   0.361288   0.076623   0.244863   0.201899   0.593086   1.000000   \n",
       "St_115053   0.476992   0.390872   0.375204   0.210275   0.580775   0.501784   \n",
       "St_114041   0.462739   0.606815   0.507141   0.242376   0.282494   0.264727   \n",
       "St_116061   0.751934   0.710011   0.475271   0.627982   0.483325   0.259072   \n",
       "St_116060   0.783895   0.540898   0.331629   0.564902   0.585901   0.538204   \n",
       "St_114096   0.488273   0.464672   0.344864   0.444377   0.471526   0.592761   \n",
       "St_113119   0.125042  -0.061753  -0.243367   0.012843  -0.305812  -0.346119   \n",
       "St_116026   0.807443   0.527514   0.291855   0.486128   0.396454   0.390298   \n",
       "\n",
       "           St_115053  St_114041  St_116061  St_116060  St_114096  St_113119  \\\n",
       "St_100110   0.476992   0.462739   0.751934   0.783895   0.488273   0.125042   \n",
       "St_114035   0.390872   0.606815   0.710011   0.540898   0.464672  -0.061753   \n",
       "St_114040   0.375204   0.507141   0.475271   0.331629   0.344864  -0.243367   \n",
       "St_115044   0.210275   0.242376   0.627982   0.564902   0.444377   0.012843   \n",
       "St_115047   0.580775   0.282494   0.483325   0.585901   0.471526  -0.305812   \n",
       "St_115049   0.501784   0.264727   0.259072   0.538204   0.592761  -0.346119   \n",
       "St_115053   1.000000   0.382008   0.674296   0.725804   0.387784  -0.339100   \n",
       "St_114041   0.382008   1.000000   0.583631   0.455593   0.297647  -0.138819   \n",
       "St_116061   0.674296   0.583631   1.000000   0.851848   0.429941  -0.013761   \n",
       "St_116060   0.725804   0.455593   0.851848   1.000000   0.497512  -0.001259   \n",
       "St_114096   0.387784   0.297647   0.429941   0.497512   1.000000  -0.365260   \n",
       "St_113119  -0.339100  -0.138819  -0.013761  -0.001259  -0.365260   1.000000   \n",
       "St_116026   0.493985   0.388847   0.708373   0.769890   0.453235   0.195365   \n",
       "\n",
       "           St_116026  \n",
       "St_100110   0.807443  \n",
       "St_114035   0.527514  \n",
       "St_114040   0.291855  \n",
       "St_115044   0.486128  \n",
       "St_115047   0.396454  \n",
       "St_115049   0.390298  \n",
       "St_115053   0.493985  \n",
       "St_114041   0.388847  \n",
       "St_116061   0.708373  \n",
       "St_116060   0.769890  \n",
       "St_114096   0.453235  \n",
       "St_113119   0.195365  \n",
       "St_116026   1.000000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covr=data_ene_c_anomstd.cov()\n",
    "covr"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# apartir de aqui seguimos a venegas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_ene_c_anomstd=data_ene_c_anomstd.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>FECHA</th>\n",
       "      <th>1981-01-31</th>\n",
       "      <th>1982-01-31</th>\n",
       "      <th>1983-01-31</th>\n",
       "      <th>1984-01-31</th>\n",
       "      <th>1985-01-31</th>\n",
       "      <th>1986-01-31</th>\n",
       "      <th>1987-01-31</th>\n",
       "      <th>1988-01-31</th>\n",
       "      <th>1989-01-31</th>\n",
       "      <th>1990-01-31</th>\n",
       "      <th>...</th>\n",
       "      <th>2001-01-31</th>\n",
       "      <th>2002-01-31</th>\n",
       "      <th>2003-01-31</th>\n",
       "      <th>2004-01-31</th>\n",
       "      <th>2005-01-31</th>\n",
       "      <th>2006-01-31</th>\n",
       "      <th>2007-01-31</th>\n",
       "      <th>2008-01-31</th>\n",
       "      <th>2009-01-31</th>\n",
       "      <th>2010-01-31</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>St_100110</th>\n",
       "      <td>-0.598431</td>\n",
       "      <td>0.862452</td>\n",
       "      <td>-2.299789</td>\n",
       "      <td>2.182057</td>\n",
       "      <td>-0.657047</td>\n",
       "      <td>-0.430099</td>\n",
       "      <td>0.760251</td>\n",
       "      <td>0.593421</td>\n",
       "      <td>0.452142</td>\n",
       "      <td>-0.097943</td>\n",
       "      <td>...</td>\n",
       "      <td>1.158537</td>\n",
       "      <td>-0.663059</td>\n",
       "      <td>0.011773</td>\n",
       "      <td>0.528794</td>\n",
       "      <td>-1.058339</td>\n",
       "      <td>1.764232</td>\n",
       "      <td>-1.336388</td>\n",
       "      <td>0.540817</td>\n",
       "      <td>-0.296335</td>\n",
       "      <td>-1.118458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_114035</th>\n",
       "      <td>0.450941</td>\n",
       "      <td>-0.115367</td>\n",
       "      <td>-2.225956</td>\n",
       "      <td>1.452872</td>\n",
       "      <td>-0.862459</td>\n",
       "      <td>-1.180463</td>\n",
       "      <td>-0.923446</td>\n",
       "      <td>1.049922</td>\n",
       "      <td>0.069772</td>\n",
       "      <td>-0.132792</td>\n",
       "      <td>...</td>\n",
       "      <td>1.851466</td>\n",
       "      <td>0.069772</td>\n",
       "      <td>-0.341891</td>\n",
       "      <td>1.350501</td>\n",
       "      <td>-1.426590</td>\n",
       "      <td>0.766767</td>\n",
       "      <td>-1.263231</td>\n",
       "      <td>0.019676</td>\n",
       "      <td>-0.860281</td>\n",
       "      <td>0.699246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_114040</th>\n",
       "      <td>0.270782</td>\n",
       "      <td>1.430030</td>\n",
       "      <td>-1.424912</td>\n",
       "      <td>-0.741924</td>\n",
       "      <td>0.156346</td>\n",
       "      <td>-0.072020</td>\n",
       "      <td>-0.451458</td>\n",
       "      <td>0.307418</td>\n",
       "      <td>0.380688</td>\n",
       "      <td>-0.145291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.385922</td>\n",
       "      <td>-0.524729</td>\n",
       "      <td>1.165732</td>\n",
       "      <td>2.704418</td>\n",
       "      <td>-2.212573</td>\n",
       "      <td>0.244614</td>\n",
       "      <td>-0.179309</td>\n",
       "      <td>-0.176693</td>\n",
       "      <td>-0.652953</td>\n",
       "      <td>0.438258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_115044</th>\n",
       "      <td>1.258765</td>\n",
       "      <td>1.451956</td>\n",
       "      <td>-1.826409</td>\n",
       "      <td>0.423061</td>\n",
       "      <td>-1.396555</td>\n",
       "      <td>-0.141069</td>\n",
       "      <td>0.906289</td>\n",
       "      <td>1.084038</td>\n",
       "      <td>0.461330</td>\n",
       "      <td>0.501613</td>\n",
       "      <td>...</td>\n",
       "      <td>1.288810</td>\n",
       "      <td>-1.022091</td>\n",
       "      <td>-0.876233</td>\n",
       "      <td>-0.178163</td>\n",
       "      <td>-1.638086</td>\n",
       "      <td>-0.007631</td>\n",
       "      <td>-1.008496</td>\n",
       "      <td>0.790811</td>\n",
       "      <td>-1.126324</td>\n",
       "      <td>0.671641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_115047</th>\n",
       "      <td>0.087764</td>\n",
       "      <td>0.307308</td>\n",
       "      <td>-0.405655</td>\n",
       "      <td>2.272501</td>\n",
       "      <td>0.143710</td>\n",
       "      <td>1.016232</td>\n",
       "      <td>2.852163</td>\n",
       "      <td>-0.504622</td>\n",
       "      <td>-0.359000</td>\n",
       "      <td>0.448689</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.654082</td>\n",
       "      <td>-1.021672</td>\n",
       "      <td>1.066725</td>\n",
       "      <td>0.262874</td>\n",
       "      <td>-1.328670</td>\n",
       "      <td>0.876871</td>\n",
       "      <td>-1.110540</td>\n",
       "      <td>0.198243</td>\n",
       "      <td>-1.558919</td>\n",
       "      <td>-0.831817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_115049</th>\n",
       "      <td>-0.168002</td>\n",
       "      <td>1.111983</td>\n",
       "      <td>-1.479938</td>\n",
       "      <td>1.525333</td>\n",
       "      <td>2.415932</td>\n",
       "      <td>2.557043</td>\n",
       "      <td>1.864133</td>\n",
       "      <td>-0.428259</td>\n",
       "      <td>0.020368</td>\n",
       "      <td>0.318565</td>\n",
       "      <td>...</td>\n",
       "      <td>0.613435</td>\n",
       "      <td>-0.341729</td>\n",
       "      <td>-0.216592</td>\n",
       "      <td>0.485636</td>\n",
       "      <td>-0.428259</td>\n",
       "      <td>0.354509</td>\n",
       "      <td>-0.817647</td>\n",
       "      <td>-0.924146</td>\n",
       "      <td>-1.088554</td>\n",
       "      <td>-0.401635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_115053</th>\n",
       "      <td>0.911179</td>\n",
       "      <td>0.884278</td>\n",
       "      <td>-1.178808</td>\n",
       "      <td>2.905979</td>\n",
       "      <td>0.687695</td>\n",
       "      <td>-0.212448</td>\n",
       "      <td>0.609062</td>\n",
       "      <td>0.660795</td>\n",
       "      <td>-1.276065</td>\n",
       "      <td>-0.498010</td>\n",
       "      <td>...</td>\n",
       "      <td>0.209688</td>\n",
       "      <td>-1.474717</td>\n",
       "      <td>0.393856</td>\n",
       "      <td>1.778213</td>\n",
       "      <td>-0.131745</td>\n",
       "      <td>1.591977</td>\n",
       "      <td>-0.214517</td>\n",
       "      <td>-0.504218</td>\n",
       "      <td>-1.139491</td>\n",
       "      <td>-0.388338</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_114041</th>\n",
       "      <td>-0.316582</td>\n",
       "      <td>-1.830612</td>\n",
       "      <td>-1.093931</td>\n",
       "      <td>0.996771</td>\n",
       "      <td>0.239413</td>\n",
       "      <td>-0.848858</td>\n",
       "      <td>0.839992</td>\n",
       "      <td>-0.098192</td>\n",
       "      <td>-0.239794</td>\n",
       "      <td>0.783456</td>\n",
       "      <td>...</td>\n",
       "      <td>1.644560</td>\n",
       "      <td>0.745605</td>\n",
       "      <td>0.568180</td>\n",
       "      <td>2.401575</td>\n",
       "      <td>-1.972552</td>\n",
       "      <td>1.486297</td>\n",
       "      <td>-0.683024</td>\n",
       "      <td>-0.650141</td>\n",
       "      <td>0.097411</td>\n",
       "      <td>0.868620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_116061</th>\n",
       "      <td>0.267563</td>\n",
       "      <td>0.925249</td>\n",
       "      <td>-1.327579</td>\n",
       "      <td>1.728549</td>\n",
       "      <td>-1.046298</td>\n",
       "      <td>-1.011967</td>\n",
       "      <td>1.091269</td>\n",
       "      <td>1.142318</td>\n",
       "      <td>-0.645687</td>\n",
       "      <td>-0.239845</td>\n",
       "      <td>...</td>\n",
       "      <td>1.444786</td>\n",
       "      <td>-0.829465</td>\n",
       "      <td>0.241296</td>\n",
       "      <td>1.419261</td>\n",
       "      <td>-0.914973</td>\n",
       "      <td>1.740872</td>\n",
       "      <td>-1.706111</td>\n",
       "      <td>1.092545</td>\n",
       "      <td>-0.626544</td>\n",
       "      <td>0.324251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_116060</th>\n",
       "      <td>0.325020</td>\n",
       "      <td>1.251191</td>\n",
       "      <td>-1.680938</td>\n",
       "      <td>2.652782</td>\n",
       "      <td>-0.619092</td>\n",
       "      <td>0.219620</td>\n",
       "      <td>1.692973</td>\n",
       "      <td>0.434904</td>\n",
       "      <td>-0.711037</td>\n",
       "      <td>-0.466599</td>\n",
       "      <td>...</td>\n",
       "      <td>1.706428</td>\n",
       "      <td>-0.900532</td>\n",
       "      <td>-0.178432</td>\n",
       "      <td>0.407994</td>\n",
       "      <td>-1.005931</td>\n",
       "      <td>1.141306</td>\n",
       "      <td>-1.721303</td>\n",
       "      <td>0.217377</td>\n",
       "      <td>-0.657215</td>\n",
       "      <td>-0.152643</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_114096</th>\n",
       "      <td>0.012904</td>\n",
       "      <td>0.455256</td>\n",
       "      <td>-1.205280</td>\n",
       "      <td>0.932482</td>\n",
       "      <td>2.119802</td>\n",
       "      <td>0.521683</td>\n",
       "      <td>1.353045</td>\n",
       "      <td>1.679469</td>\n",
       "      <td>-0.231473</td>\n",
       "      <td>-0.443989</td>\n",
       "      <td>...</td>\n",
       "      <td>1.237436</td>\n",
       "      <td>-1.169942</td>\n",
       "      <td>-0.445689</td>\n",
       "      <td>-0.362383</td>\n",
       "      <td>-1.214146</td>\n",
       "      <td>0.392473</td>\n",
       "      <td>-0.860519</td>\n",
       "      <td>-0.336881</td>\n",
       "      <td>-0.506893</td>\n",
       "      <td>-0.824817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_113119</th>\n",
       "      <td>-0.517624</td>\n",
       "      <td>-0.285717</td>\n",
       "      <td>-0.725350</td>\n",
       "      <td>-0.229755</td>\n",
       "      <td>-1.105106</td>\n",
       "      <td>-0.360102</td>\n",
       "      <td>-0.992722</td>\n",
       "      <td>-1.628105</td>\n",
       "      <td>-0.194750</td>\n",
       "      <td>-0.445350</td>\n",
       "      <td>...</td>\n",
       "      <td>1.163758</td>\n",
       "      <td>-0.048974</td>\n",
       "      <td>0.134341</td>\n",
       "      <td>-0.957947</td>\n",
       "      <td>-0.576119</td>\n",
       "      <td>-0.278347</td>\n",
       "      <td>0.088742</td>\n",
       "      <td>3.281319</td>\n",
       "      <td>0.939912</td>\n",
       "      <td>0.429809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>St_116026</th>\n",
       "      <td>-0.157935</td>\n",
       "      <td>0.618310</td>\n",
       "      <td>-1.583092</td>\n",
       "      <td>1.670679</td>\n",
       "      <td>-0.211114</td>\n",
       "      <td>0.314292</td>\n",
       "      <td>0.654168</td>\n",
       "      <td>-0.840976</td>\n",
       "      <td>0.014951</td>\n",
       "      <td>-1.372618</td>\n",
       "      <td>...</td>\n",
       "      <td>2.076036</td>\n",
       "      <td>-0.996883</td>\n",
       "      <td>-0.483950</td>\n",
       "      <td>0.131881</td>\n",
       "      <td>-0.391965</td>\n",
       "      <td>2.138399</td>\n",
       "      <td>-0.731842</td>\n",
       "      <td>0.936359</td>\n",
       "      <td>-0.987529</td>\n",
       "      <td>-0.480520</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>13 rows × 30 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "FECHA      1981-01-31  1982-01-31  1983-01-31  1984-01-31  1985-01-31  \\\n",
       "St_100110   -0.598431    0.862452   -2.299789    2.182057   -0.657047   \n",
       "St_114035    0.450941   -0.115367   -2.225956    1.452872   -0.862459   \n",
       "St_114040    0.270782    1.430030   -1.424912   -0.741924    0.156346   \n",
       "St_115044    1.258765    1.451956   -1.826409    0.423061   -1.396555   \n",
       "St_115047    0.087764    0.307308   -0.405655    2.272501    0.143710   \n",
       "St_115049   -0.168002    1.111983   -1.479938    1.525333    2.415932   \n",
       "St_115053    0.911179    0.884278   -1.178808    2.905979    0.687695   \n",
       "St_114041   -0.316582   -1.830612   -1.093931    0.996771    0.239413   \n",
       "St_116061    0.267563    0.925249   -1.327579    1.728549   -1.046298   \n",
       "St_116060    0.325020    1.251191   -1.680938    2.652782   -0.619092   \n",
       "St_114096    0.012904    0.455256   -1.205280    0.932482    2.119802   \n",
       "St_113119   -0.517624   -0.285717   -0.725350   -0.229755   -1.105106   \n",
       "St_116026   -0.157935    0.618310   -1.583092    1.670679   -0.211114   \n",
       "\n",
       "FECHA      1986-01-31  1987-01-31  1988-01-31  1989-01-31  1990-01-31  ...  \\\n",
       "St_100110   -0.430099    0.760251    0.593421    0.452142   -0.097943  ...   \n",
       "St_114035   -1.180463   -0.923446    1.049922    0.069772   -0.132792  ...   \n",
       "St_114040   -0.072020   -0.451458    0.307418    0.380688   -0.145291  ...   \n",
       "St_115044   -0.141069    0.906289    1.084038    0.461330    0.501613  ...   \n",
       "St_115047    1.016232    2.852163   -0.504622   -0.359000    0.448689  ...   \n",
       "St_115049    2.557043    1.864133   -0.428259    0.020368    0.318565  ...   \n",
       "St_115053   -0.212448    0.609062    0.660795   -1.276065   -0.498010  ...   \n",
       "St_114041   -0.848858    0.839992   -0.098192   -0.239794    0.783456  ...   \n",
       "St_116061   -1.011967    1.091269    1.142318   -0.645687   -0.239845  ...   \n",
       "St_116060    0.219620    1.692973    0.434904   -0.711037   -0.466599  ...   \n",
       "St_114096    0.521683    1.353045    1.679469   -0.231473   -0.443989  ...   \n",
       "St_113119   -0.360102   -0.992722   -1.628105   -0.194750   -0.445350  ...   \n",
       "St_116026    0.314292    0.654168   -0.840976    0.014951   -1.372618  ...   \n",
       "\n",
       "FECHA      2001-01-31  2002-01-31  2003-01-31  2004-01-31  2005-01-31  \\\n",
       "St_100110    1.158537   -0.663059    0.011773    0.528794   -1.058339   \n",
       "St_114035    1.851466    0.069772   -0.341891    1.350501   -1.426590   \n",
       "St_114040    0.385922   -0.524729    1.165732    2.704418   -2.212573   \n",
       "St_115044    1.288810   -1.022091   -0.876233   -0.178163   -1.638086   \n",
       "St_115047   -0.654082   -1.021672    1.066725    0.262874   -1.328670   \n",
       "St_115049    0.613435   -0.341729   -0.216592    0.485636   -0.428259   \n",
       "St_115053    0.209688   -1.474717    0.393856    1.778213   -0.131745   \n",
       "St_114041    1.644560    0.745605    0.568180    2.401575   -1.972552   \n",
       "St_116061    1.444786   -0.829465    0.241296    1.419261   -0.914973   \n",
       "St_116060    1.706428   -0.900532   -0.178432    0.407994   -1.005931   \n",
       "St_114096    1.237436   -1.169942   -0.445689   -0.362383   -1.214146   \n",
       "St_113119    1.163758   -0.048974    0.134341   -0.957947   -0.576119   \n",
       "St_116026    2.076036   -0.996883   -0.483950    0.131881   -0.391965   \n",
       "\n",
       "FECHA      2006-01-31  2007-01-31  2008-01-31  2009-01-31  2010-01-31  \n",
       "St_100110    1.764232   -1.336388    0.540817   -0.296335   -1.118458  \n",
       "St_114035    0.766767   -1.263231    0.019676   -0.860281    0.699246  \n",
       "St_114040    0.244614   -0.179309   -0.176693   -0.652953    0.438258  \n",
       "St_115044   -0.007631   -1.008496    0.790811   -1.126324    0.671641  \n",
       "St_115047    0.876871   -1.110540    0.198243   -1.558919   -0.831817  \n",
       "St_115049    0.354509   -0.817647   -0.924146   -1.088554   -0.401635  \n",
       "St_115053    1.591977   -0.214517   -0.504218   -1.139491   -0.388338  \n",
       "St_114041    1.486297   -0.683024   -0.650141    0.097411    0.868620  \n",
       "St_116061    1.740872   -1.706111    1.092545   -0.626544    0.324251  \n",
       "St_116060    1.141306   -1.721303    0.217377   -0.657215   -0.152643  \n",
       "St_114096    0.392473   -0.860519   -0.336881   -0.506893   -0.824817  \n",
       "St_113119   -0.278347    0.088742    3.281319    0.939912    0.429809  \n",
       "St_116026    2.138399   -0.731842    0.936359   -0.987529   -0.480520  \n",
       "\n",
       "[13 rows x 30 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_ene_c_anomstd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "matriz_F=data_ene_c_anomstd.to_numpy()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13, 30)"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matriz_F.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(13, 13)\n",
      "------------------\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 1.        ,  0.62986071,  0.3324201 ,  0.60101268,  0.4162221 ,\n",
       "         0.36128796,  0.47699225,  0.46273895,  0.75193399,  0.78389463,\n",
       "         0.48827302,  0.12504212,  0.80744327],\n",
       "       [ 0.62986071,  1.        ,  0.54689747,  0.68744569,  0.18542238,\n",
       "         0.07662328,  0.39087188,  0.60681542,  0.71001141,  0.54089834,\n",
       "         0.46467164, -0.06175287,  0.52751449],\n",
       "       [ 0.3324201 ,  0.54689747,  1.        ,  0.42182763,  0.23627677,\n",
       "         0.24486311,  0.3752043 ,  0.5071414 ,  0.47527118,  0.33162857,\n",
       "         0.34486434, -0.2433667 ,  0.29185483],\n",
       "       [ 0.60101268,  0.68744569,  0.42182763,  1.        ,  0.27934731,\n",
       "         0.20189903,  0.21027505,  0.24237551,  0.62798221,  0.56490183,\n",
       "         0.44437669,  0.01284275,  0.48612791],\n",
       "       [ 0.4162221 ,  0.18542238,  0.23627677,  0.27934731,  1.        ,\n",
       "         0.5930863 ,  0.58077472,  0.28249363,  0.4833253 ,  0.58590087,\n",
       "         0.47152605, -0.30581185,  0.39645404],\n",
       "       [ 0.36128796,  0.07662328,  0.24486311,  0.20189903,  0.5930863 ,\n",
       "         1.        ,  0.50178432,  0.26472668,  0.2590716 ,  0.53820378,\n",
       "         0.59276115, -0.34611938,  0.390298  ],\n",
       "       [ 0.47699225,  0.39087188,  0.3752043 ,  0.21027505,  0.58077472,\n",
       "         0.50178432,  1.        ,  0.38200771,  0.67429572,  0.72580371,\n",
       "         0.38778409, -0.33909963,  0.49398458],\n",
       "       [ 0.46273895,  0.60681542,  0.5071414 ,  0.24237551,  0.28249363,\n",
       "         0.26472668,  0.38200771,  1.        ,  0.58363073,  0.45559271,\n",
       "         0.29764682, -0.13881909,  0.38884704],\n",
       "       [ 0.75193399,  0.71001141,  0.47527118,  0.62798221,  0.4833253 ,\n",
       "         0.2590716 ,  0.67429572,  0.58363073,  1.        ,  0.85184807,\n",
       "         0.42994124, -0.01376102,  0.70837304],\n",
       "       [ 0.78389463,  0.54089834,  0.33162857,  0.56490183,  0.58590087,\n",
       "         0.53820378,  0.72580371,  0.45559271,  0.85184807,  1.        ,\n",
       "         0.49751169, -0.00125928,  0.76988974],\n",
       "       [ 0.48827302,  0.46467164,  0.34486434,  0.44437669,  0.47152605,\n",
       "         0.59276115,  0.38778409,  0.29764682,  0.42994124,  0.49751169,\n",
       "         1.        , -0.36525965,  0.45323522],\n",
       "       [ 0.12504212, -0.06175287, -0.2433667 ,  0.01284275, -0.30581185,\n",
       "        -0.34611938, -0.33909963, -0.13881909, -0.01376102, -0.00125928,\n",
       "        -0.36525965,  1.        ,  0.1953651 ],\n",
       "       [ 0.80744327,  0.52751449,  0.29185483,  0.48612791,  0.39645404,\n",
       "         0.390298  ,  0.49398458,  0.38884704,  0.70837304,  0.76988974,\n",
       "         0.45323522,  0.1953651 ,  1.        ]])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# matriz de covarianza, es corrc on anom std, RFF\n",
    "RFF = (matriz_F @ matriz_F.T) /29 # RFF\n",
    "print(RFF.shape)\n",
    "print(\"------------------\")\n",
    "RFF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Eigenvalues :\n",
      " [6.35783833 1.83832905 1.30319737 0.89265812 0.62679012 0.5057207\n",
      " 0.43874511 0.05966601 0.07682027 0.31268619 0.24864346 0.16824152\n",
      " 0.17066375]\n",
      "---------------\n",
      "Eigenvectors:\n",
      " [[ 0.33152063  0.21252529 -0.18974734  0.06780558  0.11427178  0.115011\n",
      "  -0.03655852  0.03711875 -0.0817827  -0.0547164   0.5155935   0.70691776\n",
      "  -0.008594  ]\n",
      " [ 0.29456253  0.27127246  0.36351917  0.09309074 -0.07136717  0.28310722\n",
      "   0.00081359  0.21785003  0.35852894 -0.03000496 -0.15536672 -0.03229516\n",
      "  -0.64148635]\n",
      " [ 0.22697287 -0.00787514  0.52132127 -0.06209261  0.09625151 -0.71908179\n",
      "  -0.24073275 -0.04179753  0.10585781 -0.23566964  0.05925384  0.08494658\n",
      "   0.09630514]\n",
      " [ 0.26600151  0.24246286  0.11813212  0.524447   -0.32302207 -0.19050226\n",
      "   0.24332323 -0.23732854 -0.37927601  0.40484817  0.01471094 -0.13111239\n",
      "   0.01142409]\n",
      " [ 0.24994071 -0.34970042 -0.22758659 -0.05791601 -0.17966206 -0.20935207\n",
      "   0.67857998 -0.00578122  0.05493879 -0.4203218   0.04326097 -0.02930838\n",
      "  -0.20263071]\n",
      " [ 0.22319149 -0.44308012 -0.22483573  0.14707371  0.41627479 -0.23758593\n",
      "  -0.07982113  0.37386089  0.01856216  0.5056516  -0.07466385 -0.00512759\n",
      "  -0.21018931]\n",
      " [ 0.2879573  -0.24182919 -0.08559516 -0.41924516 -0.36098308  0.0485329\n",
      "  -0.392824   -0.20626951 -0.43795476  0.01974675 -0.24499936  0.12200891\n",
      "  -0.28085407]\n",
      " [ 0.24815882  0.05516833  0.34256623 -0.4336118   0.52058272  0.22917988\n",
      "   0.38407208 -0.24041735 -0.22092004  0.18324062 -0.02964218 -0.07679745\n",
      "   0.10955314]\n",
      " [ 0.35294311  0.16624266  0.00303111 -0.1933138  -0.26461585  0.0699822\n",
      "   0.05401977  0.67177763 -0.07279059 -0.00465271 -0.1506797  -0.09009541\n",
      "   0.49512733]\n",
      " [ 0.35596744  0.03046778 -0.26061667 -0.10602812 -0.12362218 -0.00493772\n",
      "  -0.05145152 -0.42800163  0.65300683  0.25712889 -0.1612143   0.02103618\n",
      "   0.27035283]\n",
      " [ 0.26609997 -0.23988631  0.04974453  0.51513278  0.25748443  0.2983735\n",
      "  -0.15112295 -0.12141078 -0.10763601 -0.41692093 -0.40397808  0.07248724\n",
      "   0.23883908]\n",
      " [-0.06639864  0.56406212 -0.39541555 -0.07125877  0.26850237 -0.3225696\n",
      "   0.07685871  0.00242111 -0.12648809 -0.1238844  -0.51587153  0.12546622\n",
      "  -0.14395933]\n",
      " [ 0.31267693  0.19489046 -0.30386768 -0.00373563  0.19407993  0.00995138\n",
      "  -0.2802308  -0.06100555 -0.08023989 -0.23459595  0.39991425 -0.65084003\n",
      "  -0.08298462]]\n"
     ]
    }
   ],
   "source": [
    "# 2) eigenproblem\n",
    "e_values, e_vectors = np.linalg.eig(RFF)\n",
    "\n",
    "print(\"Eigenvalues :\\n\", e_values)\n",
    "print(\"---------------\")\n",
    "print(\"Eigenvectors:\\n\", e_vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Eigenvalues :\n",
      " [6.35783833 1.83832905 1.30319737 0.89265812 0.62679012 0.5057207\n",
      " 0.43874511 0.31268619 0.24864346 0.17066375 0.16824152 0.07682027\n",
      " 0.05966601]\n",
      "---------------\n",
      "Eigenvectors:\n",
      " [[ 0.33152063  0.21252529 -0.18974734  0.06780558  0.11427178  0.115011\n",
      "  -0.03655852 -0.0547164   0.5155935  -0.008594    0.70691776 -0.0817827\n",
      "   0.03711875]\n",
      " [ 0.29456253  0.27127246  0.36351917  0.09309074 -0.07136717  0.28310722\n",
      "   0.00081359 -0.03000496 -0.15536672 -0.64148635 -0.03229516  0.35852894\n",
      "   0.21785003]\n",
      " [ 0.22697287 -0.00787514  0.52132127 -0.06209261  0.09625151 -0.71908179\n",
      "  -0.24073275 -0.23566964  0.05925384  0.09630514  0.08494658  0.10585781\n",
      "  -0.04179753]\n",
      " [ 0.26600151  0.24246286  0.11813212  0.524447   -0.32302207 -0.19050226\n",
      "   0.24332323  0.40484817  0.01471094  0.01142409 -0.13111239 -0.37927601\n",
      "  -0.23732854]\n",
      " [ 0.24994071 -0.34970042 -0.22758659 -0.05791601 -0.17966206 -0.20935207\n",
      "   0.67857998 -0.4203218   0.04326097 -0.20263071 -0.02930838  0.05493879\n",
      "  -0.00578122]\n",
      " [ 0.22319149 -0.44308012 -0.22483573  0.14707371  0.41627479 -0.23758593\n",
      "  -0.07982113  0.5056516  -0.07466385 -0.21018931 -0.00512759  0.01856216\n",
      "   0.37386089]\n",
      " [ 0.2879573  -0.24182919 -0.08559516 -0.41924516 -0.36098308  0.0485329\n",
      "  -0.392824    0.01974675 -0.24499936 -0.28085407  0.12200891 -0.43795476\n",
      "  -0.20626951]\n",
      " [ 0.24815882  0.05516833  0.34256623 -0.4336118   0.52058272  0.22917988\n",
      "   0.38407208  0.18324062 -0.02964218  0.10955314 -0.07679745 -0.22092004\n",
      "  -0.24041735]\n",
      " [ 0.35294311  0.16624266  0.00303111 -0.1933138  -0.26461585  0.0699822\n",
      "   0.05401977 -0.00465271 -0.1506797   0.49512733 -0.09009541 -0.07279059\n",
      "   0.67177763]\n",
      " [ 0.35596744  0.03046778 -0.26061667 -0.10602812 -0.12362218 -0.00493772\n",
      "  -0.05145152  0.25712889 -0.1612143   0.27035283  0.02103618  0.65300683\n",
      "  -0.42800163]\n",
      " [ 0.26609997 -0.23988631  0.04974453  0.51513278  0.25748443  0.2983735\n",
      "  -0.15112295 -0.41692093 -0.40397808  0.23883908  0.07248724 -0.10763601\n",
      "  -0.12141078]\n",
      " [-0.06639864  0.56406212 -0.39541555 -0.07125877  0.26850237 -0.3225696\n",
      "   0.07685871 -0.1238844  -0.51587153 -0.14395933  0.12546622 -0.12648809\n",
      "   0.00242111]\n",
      " [ 0.31267693  0.19489046 -0.30386768 -0.00373563  0.19407993  0.00995138\n",
      "  -0.2802308  -0.23459595  0.39991425 -0.08298462 -0.65084003 -0.08023989\n",
      "  -0.06100555]]\n"
     ]
    }
   ],
   "source": [
    "isort = np.argsort(e_values)[::-1]\n",
    "e_values = e_values[isort]\n",
    "e_vectors = e_vectors[:, isort] # re-arrange the columns\n",
    "print(\"Eigenvalues :\\n\", e_values)\n",
    "print(\"---------------\")\n",
    "print(\"Eigenvectors:\\n\", e_vectors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(13, 30)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([[ 6.97540904e-01,  2.19347385e+00, -5.10444710e+00,\n",
       "         5.42823941e+00,  6.48763300e-03, -9.28476464e-03,\n",
       "         3.24969997e+00,  1.65837597e+00, -6.57560269e-01,\n",
       "        -5.05376867e-01, -5.09879765e-01, -2.29559275e+00,\n",
       "         9.12235612e-01, -1.96493916e-01, -3.15825227e+00,\n",
       "         4.82613249e-01,  2.63383686e+00, -2.17207511e+00,\n",
       "        -1.67906742e+00,  5.93391458e-01,  3.82029424e+00,\n",
       "        -2.39458395e+00,  1.50203800e-01,  3.07622877e+00,\n",
       "        -3.75252529e+00,  3.80202320e+00, -3.49402634e+00,\n",
       "         3.40340606e-01, -2.69715081e+00, -4.18668923e-01],\n",
       "       [-1.67314362e-01, -3.80151186e-01, -1.20236635e+00,\n",
       "        -8.11517548e-01, -3.35305346e+00, -2.35762930e+00,\n",
       "        -2.31399338e+00, -4.09626751e-01,  4.55339786e-01,\n",
       "        -5.34770175e-01, -1.17072634e+00, -1.01109879e+00,\n",
       "         3.60204497e-01,  8.08230971e-01,  2.56483799e-01,\n",
       "         1.58917169e+00,  2.78330339e-01,  1.33922846e+00,\n",
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       "         4.34195498e-01, -5.29793252e-01, -3.69731967e-01,\n",
       "        -7.07097825e-01,  3.02241906e-01, -3.27191129e-01,\n",
       "         3.04203990e+00,  1.07923194e+00,  1.11796328e+00],\n",
       "       [ 5.68113145e-01, -6.86844599e-01, -3.82073125e-02,\n",
       "        -2.04666467e+00, -6.03124029e-02, -1.46798838e+00,\n",
       "        -1.61770172e+00,  1.55131197e+00,  5.41033873e-01,\n",
       "         7.83080808e-01,  1.44089297e+00,  2.32542151e-01,\n",
       "         9.79106691e-01,  8.92831431e-01, -1.27335893e+00,\n",
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       "        -1.38462101e+00, -6.48154036e-01,  3.90630017e-01,\n",
       "        -1.76316628e+00,  7.30757616e-02,  1.36043670e+00],\n",
       "       [ 3.28155717e-01,  1.23025217e+00, -5.86559426e-01,\n",
       "        -1.13160018e+00,  5.27327221e-01,  1.03135918e+00,\n",
       "         3.33153945e-01,  1.13655926e+00,  1.01299945e+00,\n",
       "         4.70144630e-02,  1.57490784e+00, -1.49761757e+00,\n",
       "         9.57917408e-02,  1.70083363e+00, -4.92378920e-01,\n",
       "         6.55482495e-01,  2.25509813e-01,  6.94763587e-01,\n",
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       "        -5.77671495e-01, -1.33315796e+00, -2.26697338e+00,\n",
       "        -3.01141938e-01, -1.38226061e+00, -3.30362531e-01,\n",
       "         1.65001775e-01, -4.18256873e-01, -4.10667306e-01],\n",
       "       [-1.33783562e+00, -1.32810248e+00, -5.91498346e-01,\n",
       "        -6.48530061e-01,  1.87041612e+00,  9.29645165e-01,\n",
       "         8.30921667e-03, -1.22893112e+00,  4.92861510e-01,\n",
       "         8.27468784e-02,  2.81855931e-01, -7.17405155e-01,\n",
       "        -6.75779370e-01, -5.48694744e-01, -1.02714857e+00,\n",
       "         7.10323507e-01,  7.02214172e-02,  3.20182348e-01,\n",
       "         8.62496730e-01, -2.81754293e-01,  1.21513641e+00,\n",
       "         9.83652140e-01,  7.83839064e-02,  2.94223054e-01,\n",
       "        -7.98746619e-01,  2.01571936e-01,  1.51448747e-01,\n",
       "        -1.28762317e-01,  7.94733345e-01, -3.50196710e-02],\n",
       "       [-1.96096012e-01, -1.65080343e+00,  3.80488283e-01,\n",
       "         1.12334872e+00,  2.34752389e-01, -1.12708299e+00,\n",
       "        -4.14867798e-02,  1.25059094e+00, -3.84216650e-01,\n",
       "        -7.11377576e-02,  4.70939931e-01, -4.89455129e-01,\n",
       "        -9.36141559e-01,  5.59018010e-01,  4.33654807e-01,\n",
       "         2.46278990e-01,  4.90059665e-02, -1.96631440e-01,\n",
       "        -2.59875726e-01,  5.22865707e-01,  6.19812063e-01,\n",
       "         5.13108070e-01, -9.52665835e-01, -7.01822087e-01,\n",
       "         1.05953035e+00,  7.39996099e-01, -3.34024434e-01,\n",
       "        -1.02550015e+00,  4.53610116e-01, -2.90060464e-01],\n",
       "       [-1.42957946e-01, -1.23168636e+00,  4.51456041e-01,\n",
       "         1.94701508e-01, -9.98442522e-01, -1.98593146e-02,\n",
       "         1.67839421e+00, -5.40546739e-01,  1.85597200e-01,\n",
       "         1.36464836e+00,  2.46843458e-01, -4.63464468e-02,\n",
       "        -3.08327727e-01,  7.62707046e-01,  1.04668009e-01,\n",
       "        -6.34825524e-01, -1.09651008e-01,  6.01050699e-01,\n",
       "        -4.94279571e-01,  6.34663046e-02, -4.52788069e-01,\n",
       "         5.55504168e-01,  5.45618687e-01, -3.49299051e-01,\n",
       "        -1.15031279e+00, -2.57040180e-01, -6.82434436e-01,\n",
       "         4.60407047e-01, -1.67120611e-01,  3.70855569e-01],\n",
       "       [ 4.81273011e-01,  3.40155196e-01, -4.74828887e-01,\n",
       "         1.61096256e-01, -1.73420793e-01,  5.39460704e-01,\n",
       "         2.04777334e-01,  9.83506433e-02,  9.95762191e-02,\n",
       "         7.96307970e-01, -1.31172078e+00,  3.68318270e-01,\n",
       "        -1.24730299e-01,  1.57605083e-01, -2.69658853e-01,\n",
       "         6.06353474e-01, -1.41118211e+00,  7.25146711e-02,\n",
       "        -1.74579687e-01, -2.01124355e-01,  4.87413359e-01,\n",
       "         6.08208675e-01, -8.30147767e-01,  1.68441981e-01,\n",
       "         3.51970707e-01, -4.11244738e-01, -2.46255433e-01,\n",
       "        -7.82999904e-01,  5.75350622e-04,  8.69494708e-01],\n",
       "       [-4.35619791e-01,  2.06203066e-01,  1.61989423e-01,\n",
       "        -1.73671330e-01, -6.79025360e-01,  1.03346385e-01,\n",
       "         1.21883955e-01, -3.88965319e-01,  9.66193390e-01,\n",
       "         3.48547756e-02, -6.88535174e-01, -3.45275071e-01,\n",
       "         1.79268122e-01,  7.43302249e-02, -2.55923799e-01,\n",
       "         6.59997826e-01,  9.09630906e-01,  7.41007597e-01,\n",
       "        -4.22234544e-01, -1.21398388e-01, -5.85525666e-01,\n",
       "         2.91072244e-01, -2.60301159e-02,  1.02394676e-01,\n",
       "         5.16992118e-01,  7.76161502e-01,  1.11331464e-01,\n",
       "        -8.84521993e-01, -2.58932938e-01, -6.90998184e-01],\n",
       "       [-2.05681419e-01,  3.70935108e-01,  7.30246307e-01,\n",
       "        -8.15225231e-01, -1.48354731e-01, -3.15631968e-01,\n",
       "         9.13732326e-01,  7.47765425e-01, -1.46547553e-01,\n",
       "        -2.73380111e-02, -3.79693498e-01,  3.20026891e-02,\n",
       "        -2.58435926e-01, -6.63598914e-01, -6.33692523e-01,\n",
       "         3.32019542e-01,  4.63677447e-02, -3.75449450e-01,\n",
       "         1.09696683e-01,  1.92207326e-01,  1.11543058e-01,\n",
       "        -1.70360590e-01,  8.80825838e-02, -1.50691052e-01,\n",
       "        -2.69210604e-02,  1.06821515e-01, -2.92319396e-01,\n",
       "         1.68387899e-01,  6.91720537e-01, -3.15874189e-02],\n",
       "       [-4.24356490e-01,  3.15974442e-01, -5.39573652e-01,\n",
       "         4.32194447e-01,  4.23304134e-02, -3.73294591e-01,\n",
       "        -1.88205065e-01,  7.45765294e-01,  1.54639724e-01,\n",
       "         5.38316380e-01,  9.71728731e-02, -1.62713553e-01,\n",
       "        -1.08017413e-01,  2.44613455e-02,  2.93242904e-01,\n",
       "         3.32457028e-01, -4.78211398e-01,  2.51394949e-01,\n",
       "         5.60297281e-01, -6.85260602e-01, -6.71417744e-01,\n",
       "         2.66084347e-02,  4.81569391e-01,  2.54040059e-01,\n",
       "        -3.42626653e-01, -2.34307512e-01, -1.81330584e-01,\n",
       "        -6.56832762e-02,  5.81799932e-01, -6.77266368e-01],\n",
       "       [-2.96030154e-01,  2.30672192e-01, -1.24546999e-02,\n",
       "         1.64815228e-01, -4.10136830e-01,  2.22944477e-01,\n",
       "        -9.22682636e-02, -6.05995689e-02,  7.68913339e-02,\n",
       "        -2.42615684e-01,  3.35123150e-01,  4.64062085e-01,\n",
       "         1.47966679e-01, -1.50719185e-01,  3.50742534e-02,\n",
       "        -1.31528606e-01,  3.27253915e-01, -2.36311291e-01,\n",
       "         3.53414046e-01,  3.71900888e-02,  2.03563146e-01,\n",
       "         5.14454016e-01,  2.44969470e-02, -1.78366498e-01,\n",
       "         1.94088727e-02, -3.71458473e-01, -6.71154341e-01,\n",
       "        -3.89122891e-01,  7.68932627e-02,  8.54279193e-03],\n",
       "       [-3.61739088e-01,  2.66544656e-01, -5.33051945e-02,\n",
       "        -1.43706802e-01,  1.30543816e-01,  1.04168334e-01,\n",
       "        -2.14404499e-01,  1.35444006e-01,  1.34424419e-01,\n",
       "         6.04815231e-02,  2.05212443e-03, -2.51876790e-01,\n",
       "        -2.90462203e-01,  8.52303353e-02, -1.03182855e-01,\n",
       "        -5.06138778e-01, -2.15791834e-01,  7.39183930e-02,\n",
       "        -2.42971779e-01,  2.60079665e-01, -1.15018387e-01,\n",
       "         2.89125195e-01,  1.02630212e-01,  2.91387049e-01,\n",
       "         4.65969722e-01,  1.68092505e-01, -4.28836238e-01,\n",
       "         3.90357691e-01, -1.05689670e-01,  7.26744743e-02]])"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "A = e_vectors.T @ matriz_F\n",
    "print(A.shape)\n",
    "A"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'PCs / EOF temporal evolu')"
      ]
     },
     "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": [
    "# plotear componentes principales, evolucion temporal de cada modo\n",
    "plt.figure()\n",
    "plt.plot(A.T)\n",
    "plt.legend([\"0\", \"1\", \"2\", \"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\",\"11\",\"12\",\"13\"])\n",
    "plt.title(\"PCs / EOF temporal evolu\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "varianzas:\n",
      " [6.35783833 1.83832905 1.30319737 0.89265812 0.62679012 0.5057207\n",
      " 0.43874511 0.31268619 0.24864346 0.17066375 0.16824152 0.07682027\n",
      " 0.05966601]\n",
      "eigenvalues:\n",
      " [6.35783833 1.83832905 1.30319737 0.89265812 0.62679012 0.5057207\n",
      " 0.43874511 0.31268619 0.24864346 0.17066375 0.16824152 0.07682027\n",
      " 0.05966601]\n",
      "% de explicacion :\n",
      " [48.90644871 14.14099267 10.02459512  6.86660096  4.82146245  3.89015923\n",
      "  3.37496235  2.4052784   1.91264203  1.31279808  1.29416555  0.59092516\n",
      "  0.45896931]\n"
     ]
    }
   ],
   "source": [
    "print(\"varianzas:\\n\", np.var(A,axis=1,ddof=1)) # N-1/ N-ddof\n",
    "print(\"eigenvalues:\\n\", e_values)\n",
    "print(\"% de explicacion :\\n\", 100*e_values/np.sum(e_values))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0., -0., -0., -0., -0., -0.,  0.,  0.,  0., -0., -0., -0.,  0.])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.round(np.mean(A,axis=1),14)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#reconstruccion con todo los eofs\n",
    "dat_from_eofs = e_vectors @ A\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13, 30)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat_from_eofs.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x247132b0cd0>]"
      ]
     },
     "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": [
    "plt.plot(dat_from_eofs[1,:],\"r--\",label=\"reconstruido\")\n",
    "plt.plot(serite_totest,label=\"original\",alpha=0.5)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x247142ee580>]"
      ]
     },
     "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"
    }
   ],
   "source": [
    "# pero nosotros normalmente buscamos solo usar menos informacion, usemos los primeros eof\n",
    "k=3\n",
    "dat_from_4eofs = e_vectors[:,:k] @ A[:k,:]\n",
    "plt.plot(np.arange(1981,2011),dat_from_4eofs[1,:],\"r--\",label=\"reconstruido\")\n",
    "plt.plot(np.arange(1981,2011),serite_totest,label=\"original\",alpha=0.5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ahora con SVD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Eigenvalues de la Matriz de Covarianza Approach:\n",
      " [6.35783833 1.83832905 1.30319737 0.89265812 0.62679012 0.5057207\n",
      " 0.43874511 0.31268619 0.24864346 0.17066375 0.16824152 0.07682027\n",
      " 0.05966601]\n",
      "Eigenvalues de la SVD:\n",
      " [6.35783833 1.83832905 1.30319737 0.89265812 0.62679012 0.5057207\n",
      " 0.43874511 0.31268619 0.24864346 0.17066375 0.16824152 0.07682027\n",
      " 0.05966601]\n",
      "\n",
      "Eigenvectors de la Matriz de Covarianza Approach: \n",
      " [[ 0.33152063  0.21252529 -0.18974734  0.06780558  0.11427178  0.115011\n",
      "  -0.03655852 -0.0547164   0.5155935  -0.008594    0.70691776 -0.0817827\n",
      "   0.03711875]\n",
      " [ 0.29456253  0.27127246  0.36351917  0.09309074 -0.07136717  0.28310722\n",
      "   0.00081359 -0.03000496 -0.15536672 -0.64148635 -0.03229516  0.35852894\n",
      "   0.21785003]\n",
      " [ 0.22697287 -0.00787514  0.52132127 -0.06209261  0.09625151 -0.71908179\n",
      "  -0.24073275 -0.23566964  0.05925384  0.09630514  0.08494658  0.10585781\n",
      "  -0.04179753]\n",
      " [ 0.26600151  0.24246286  0.11813212  0.524447   -0.32302207 -0.19050226\n",
      "   0.24332323  0.40484817  0.01471094  0.01142409 -0.13111239 -0.37927601\n",
      "  -0.23732854]\n",
      " [ 0.24994071 -0.34970042 -0.22758659 -0.05791601 -0.17966206 -0.20935207\n",
      "   0.67857998 -0.4203218   0.04326097 -0.20263071 -0.02930838  0.05493879\n",
      "  -0.00578122]\n",
      " [ 0.22319149 -0.44308012 -0.22483573  0.14707371  0.41627479 -0.23758593\n",
      "  -0.07982113  0.5056516  -0.07466385 -0.21018931 -0.00512759  0.01856216\n",
      "   0.37386089]\n",
      " [ 0.2879573  -0.24182919 -0.08559516 -0.41924516 -0.36098308  0.0485329\n",
      "  -0.392824    0.01974675 -0.24499936 -0.28085407  0.12200891 -0.43795476\n",
      "  -0.20626951]\n",
      " [ 0.24815882  0.05516833  0.34256623 -0.4336118   0.52058272  0.22917988\n",
      "   0.38407208  0.18324062 -0.02964218  0.10955314 -0.07679745 -0.22092004\n",
      "  -0.24041735]\n",
      " [ 0.35294311  0.16624266  0.00303111 -0.1933138  -0.26461585  0.0699822\n",
      "   0.05401977 -0.00465271 -0.1506797   0.49512733 -0.09009541 -0.07279059\n",
      "   0.67177763]\n",
      " [ 0.35596744  0.03046778 -0.26061667 -0.10602812 -0.12362218 -0.00493772\n",
      "  -0.05145152  0.25712889 -0.1612143   0.27035283  0.02103618  0.65300683\n",
      "  -0.42800163]\n",
      " [ 0.26609997 -0.23988631  0.04974453  0.51513278  0.25748443  0.2983735\n",
      "  -0.15112295 -0.41692093 -0.40397808  0.23883908  0.07248724 -0.10763601\n",
      "  -0.12141078]\n",
      " [-0.06639864  0.56406212 -0.39541555 -0.07125877  0.26850237 -0.3225696\n",
      "   0.07685871 -0.1238844  -0.51587153 -0.14395933  0.12546622 -0.12648809\n",
      "   0.00242111]\n",
      " [ 0.31267693  0.19489046 -0.30386768 -0.00373563  0.19407993  0.00995138\n",
      "  -0.2802308  -0.23459595  0.39991425 -0.08298462 -0.65084003 -0.08023989\n",
      "  -0.06100555]]\n",
      "Eigenvectors de la SVD :\n",
      " [[ 0.33152063  0.21252529 -0.18974734  0.06780558 -0.11427178  0.115011\n",
      "  -0.03655852  0.0547164  -0.5155935   0.008594   -0.70691776 -0.0817827\n",
      "  -0.03711875]\n",
      " [ 0.29456253  0.27127246  0.36351917  0.09309074  0.07136717  0.28310722\n",
      "   0.00081359  0.03000496  0.15536672  0.64148635  0.03229516  0.35852894\n",
      "  -0.21785003]\n",
      " [ 0.22697287 -0.00787514  0.52132127 -0.06209261 -0.09625151 -0.71908179\n",
      "  -0.24073275  0.23566964 -0.05925384 -0.09630514 -0.08494658  0.10585781\n",
      "   0.04179753]\n",
      " [ 0.26600151  0.24246286  0.11813212  0.524447    0.32302207 -0.19050226\n",
      "   0.24332323 -0.40484817 -0.01471094 -0.01142409  0.13111239 -0.37927601\n",
      "   0.23732854]\n",
      " [ 0.24994071 -0.34970042 -0.22758659 -0.05791601  0.17966206 -0.20935207\n",
      "   0.67857998  0.4203218  -0.04326097  0.20263071  0.02930838  0.05493879\n",
      "   0.00578122]\n",
      " [ 0.22319149 -0.44308012 -0.22483573  0.14707371 -0.41627479 -0.23758593\n",
      "  -0.07982113 -0.5056516   0.07466385  0.21018931  0.00512759  0.01856216\n",
      "  -0.37386089]\n",
      " [ 0.2879573  -0.24182919 -0.08559516 -0.41924516  0.36098308  0.0485329\n",
      "  -0.392824   -0.01974675  0.24499936  0.28085407 -0.12200891 -0.43795476\n",
      "   0.20626951]\n",
      " [ 0.24815882  0.05516833  0.34256623 -0.4336118  -0.52058272  0.22917988\n",
      "   0.38407208 -0.18324062  0.02964218 -0.10955314  0.07679745 -0.22092004\n",
      "   0.24041735]\n",
      " [ 0.35294311  0.16624266  0.00303111 -0.1933138   0.26461585  0.0699822\n",
      "   0.05401977  0.00465271  0.1506797  -0.49512733  0.09009541 -0.07279059\n",
      "  -0.67177763]\n",
      " [ 0.35596744  0.03046778 -0.26061667 -0.10602812  0.12362218 -0.00493772\n",
      "  -0.05145152 -0.25712889  0.1612143  -0.27035283 -0.02103618  0.65300683\n",
      "   0.42800163]\n",
      " [ 0.26609997 -0.23988631  0.04974453  0.51513278 -0.25748443  0.2983735\n",
      "  -0.15112295  0.41692093  0.40397808 -0.23883908 -0.07248724 -0.10763601\n",
      "   0.12141078]\n",
      " [-0.06639864  0.56406212 -0.39541555 -0.07125877 -0.26850237 -0.3225696\n",
      "   0.07685871  0.1238844   0.51587153  0.14395933 -0.12546622 -0.12648809\n",
      "  -0.00242111]\n",
      " [ 0.31267693  0.19489046 -0.30386768 -0.00373563 -0.19407993  0.00995138\n",
      "  -0.2802308   0.23459595 -0.39991425  0.08298462  0.65084003 -0.08023989\n",
      "   0.06100555]]\n"
     ]
    }
   ],
   "source": [
    "u, d, vt = np.linalg.svd(matriz_F, full_matrices=False)\n",
    "\n",
    "print(\"Eigenvalues de la Matriz de Covarianza Approach:\\n\", e_values)\n",
    "print(\"Eigenvalues de la SVD:\\n\", (d ** 2)/29 )  # Note the power of 2. and (N-1)\n",
    "\n",
    "vecs_svd = u\n",
    "print(\"\\nEigenvectors de la Matriz de Covarianza Approach: \\n\", e_vectors)\n",
    "print(\"Eigenvectors de la SVD :\\n\", vecs_svd)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2471433bd60>"
      ]
     },
     "execution_count": 23,
     "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.figure()\n",
    "plt.plot(vt[0,:],\"r--\",label=\"PC1 DEL SVD\")\n",
    "plt.plot(A[0,:],label=\"PC1 DE MATRIX DE COV\",alpha=0.5)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2471439fcd0>"
      ]
     },
     "execution_count": 24,
     "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": [
    "PCsvd = np.dot(np.diag(d), vt)\n",
    "plt.figure()\n",
    "plt.plot(PCsvd[0,:]*-1,\"r--\",label=\"PC1 DEL SVD\")\n",
    "plt.plot(A[0,:],label=\"PC1 DE MATRIX DE COV\",alpha=0.5)\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x24713268850>"
      ]
     },
     "execution_count": 25,
     "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 i in range(0,13):\n",
    "    plt.plot(PCsvd[i,:],label=\"PC\"+str(i+1))\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x2471448c8b0>"
      ]
     },
     "execution_count": 26,
     "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(PCsvd[0,:],\"r--\",label=\"PC1 DEL SVD\")\n",
    "plt.plot(PCsvd[12,:],\"b--\",label=\"PC13 DEL SVD\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x247144f2ca0>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(PCsvd[0,:]/np.sqrt(e_values[0]),\"r--\",label=\"PC1 DEL SVD normalizado\")\n",
    "plt.plot(PCsvd[12,:]/np.sqrt(e_values[12]),\"b--\",label=\"PC13 DEL SVD normalizado\")\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x2471456b3d0>]"
      ]
     },
     "execution_count": 28,
     "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(e_values*100/np.sum(e_values),\"o-\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "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": [
    "# la regla de North et al Thumb\n",
    "var_errors=e_values*np.sqrt(2/29) # grados de libertad N*\n",
    "plt.errorbar(np.arange(1,14), e_values*100/np.sum(e_values), yerr=var_errors*100/np.sum(e_values), fmt='xb');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# ploteo en mapa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.8359211348218168\n",
      "0.7427321906173152\n",
      "0.5723065087740323\n",
      "0.6707162593260351\n",
      "0.630219352366087\n",
      "0.5627718644106396\n",
      "0.7260772570569243\n",
      "0.6257263612324615\n",
      "0.889937388175669\n",
      "0.8975631527177583\n",
      "0.6709645261932163\n",
      "-0.1674225289717921\n",
      "0.7884071970810994\n",
      "------------------------\n",
      "0.2881523954536117\n",
      "0.3678047439943605\n",
      "-0.0106775058556661\n",
      "0.3287432525906505\n",
      "-0.4741412975586302\n",
      "-0.6007501509509409\n",
      "-0.32788408842143246\n",
      "0.07479997772221568\n",
      "0.22540009665441635\n",
      "0.041309739219592224\n",
      "-0.3252498417248159\n",
      "0.7647835951775759\n",
      "0.2642422135533964\n",
      "------------------------\n",
      "-0.21661114205523221\n",
      "0.4149850196544303\n",
      "0.5951282148920634\n",
      "0.1348568783104275\n",
      "-0.2598075465534881\n",
      "-0.25666723148510834\n",
      "-0.09771344433585076\n",
      "0.3910656248576455\n",
      "0.0034602468110558754\n",
      "-0.29751392012291195\n",
      "0.0567872011479494\n",
      "-0.451397182580349\n",
      "-0.3468882588985033\n",
      "------------------------\n",
      "0.06406310664978139\n",
      "0.08795267546132016\n",
      "-0.05866546445193443\n",
      "0.4955006025674053\n",
      "-0.05471938796825414\n",
      "0.13895610280387655\n",
      "-0.3961052825568559\n",
      "-0.40967897530062214\n",
      "-0.18264401601766908\n",
      "-0.10017598800095835\n",
      "0.48670046885266255\n",
      "-0.06732569923432045\n",
      "-0.0035294477268514976\n",
      "------------------------\n",
      "-0.09046905719378791\n",
      "0.056501446875109336\n",
      "-0.07620239441742035\n",
      "0.25573682220571403\n",
      "0.14223859043985865\n",
      "-0.32956507697437565\n",
      "0.2857905845374799\n",
      "-0.4121457410698337\n",
      "0.20949657456214657\n",
      "0.09787177976663124\n",
      "-0.20385062614435936\n",
      "-0.2125735368894285\n",
      "-0.1536532285700001\n",
      "------------------------\n",
      "0.08178897286401206\n",
      "0.20132898888697806\n",
      "-0.511368129491567\n",
      "-0.13547385541313284\n",
      "-0.14887872126166862\n",
      "-0.16895695888528128\n",
      "0.034513708559932556\n",
      "0.1629790797786481\n",
      "0.049767173609191674\n",
      "-0.0035114147500514563\n",
      "0.2121854556596865\n",
      "-0.22939227818121302\n",
      "0.007076827913741425\n",
      "------------------------\n",
      "-0.024215573863144987\n",
      "0.0005389050217329842\n",
      "-0.15945616596765377\n",
      "0.16117204388850298\n",
      "0.44947670070614476\n",
      "-0.052871790021616516\n",
      "-0.26019811980035334\n",
      "0.25440104179621226\n",
      "0.03578152650591617\n",
      "-0.03408037297685298\n",
      "-0.10010057415243079\n",
      "0.050909546520201944\n",
      "-0.1856188194811939\n",
      "------------------------\n",
      "0.030596509243424608\n",
      "0.016778277761931994\n",
      "0.13178257268229443\n",
      "-0.22638441894671524\n",
      "0.23503701554575143\n",
      "-0.28275203459953535\n",
      "-0.01104205847834579\n",
      "-0.10246513060929752\n",
      "0.0026017167170775293\n",
      "-0.14378223438755314\n",
      "0.23313530919617595\n",
      "0.0692741117469854\n",
      "0.1311821877869107\n",
      "------------------------\n",
      "-0.2570963772575908\n",
      "0.07747231103392792\n",
      "-0.02954642859853583\n",
      "-0.007335486889625973\n",
      "-0.02157172053791672\n",
      "0.03723050393978034\n",
      "0.12216687864512889\n",
      "0.01478082459591657\n",
      "0.07513516995648183\n",
      "0.08038816107472002\n",
      "0.2014402820987864\n",
      "0.257235013967585\n",
      "-0.19941388647785444\n",
      "------------------------\n",
      "0.0035503085303879743\n",
      "0.26500743560643214\n",
      "-0.039785069952406556\n",
      "-0.004719458887617682\n",
      "0.08370972371426694\n",
      "0.08683229369837109\n",
      "0.11602494504222216\n",
      "-0.04525801112004107\n",
      "-0.20454437576883036\n",
      "-0.11168672882647482\n",
      "-0.09866793168000228\n",
      "0.05947171581812229\n",
      "0.03428216465402901\n",
      "------------------------\n",
      "-0.28995826053566953\n",
      "0.013246588980009032\n",
      "-0.034842756786675366\n",
      "0.053778705413928256\n",
      "0.012021491115721684\n",
      "0.002103195616944407\n",
      "-0.050044706717294496\n",
      "0.03150020711201957\n",
      "0.036954663535844846\n",
      "-0.008628464249951394\n",
      "-0.029732276299855125\n",
      "-0.05146280081299128\n",
      "0.266956717651091\n",
      "------------------------\n",
      "-0.022667276410168545\n",
      "0.09937156480123917\n",
      "0.029340048187385587\n",
      "-0.10512191984827995\n",
      "0.015227093281757443\n",
      "0.005144774628906305\n",
      "-0.12138559784798142\n",
      "-0.06123123553019432\n",
      "-0.02017498274024739\n",
      "0.1809904401166842\n",
      "-0.02983290270260621\n",
      "-0.035058034050902395\n",
      "-0.022239664199124792\n",
      "------------------------\n",
      "-0.009066857614748954\n",
      "-0.0532134142379069\n",
      "0.010209727660693104\n",
      "0.05797135607707525\n",
      "0.001412157222502325\n",
      "-0.09132160520956356\n",
      "0.05038468253475888\n",
      "0.05872585000375509\n",
      "-0.1640926148863373\n",
      "0.10454635999529462\n",
      "0.02965655759514392\n",
      "-0.0005913955713120644\n",
      "0.014901598118123428\n",
      "------------------------\n"
     ]
    }
   ],
   "source": [
    "# correlation PCs vs EOFs\n",
    "\n",
    "matriz_F_corr=np.zeros([PCsvd.shape[0],PCsvd.shape[0]],dtype=float)\n",
    "\n",
    "for i in np.arange(0,PCsvd.shape[0]):\n",
    "    for j in np.arange(0,matriz_F.shape[0]):\n",
    "        pcinfo=PCsvd[i,:]\n",
    "        finfo=matriz_F[j,:]\n",
    "        \n",
    "        print(np.corrcoef(pcinfo,finfo)[0 , 1])\n",
    "        \n",
    "        matriz_F_corr[j,i]=np.corrcoef(pcinfo,finfo)[0 , 1]\n",
    "    \n",
    "    print(\"------------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(13, 13)"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "matriz_F_corr.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ESTACIONES</th>\n",
       "      <th>LON</th>\n",
       "      <th>LAT</th>\n",
       "      <th>ALTURA</th>\n",
       "      <th>NAME</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>St_100110</td>\n",
       "      <td>-70.01208</td>\n",
       "      <td>-15.82625</td>\n",
       "      <td>3812</td>\n",
       "      <td>PUNO</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>St_114035</td>\n",
       "      <td>-70.71569</td>\n",
       "      <td>-14.78478</td>\n",
       "      <td>3971</td>\n",
       "      <td>CHUQUIBAMBILLA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>St_114040</td>\n",
       "      <td>-70.02353</td>\n",
       "      <td>-14.69011</td>\n",
       "      <td>3980</td>\n",
       "      <td>PROGRESO</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>St_115044</td>\n",
       "      <td>-70.91242</td>\n",
       "      <td>-15.76446</td>\n",
       "      <td>4521</td>\n",
       "      <td>CRUCERO ALTO</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>St_115047</td>\n",
       "      <td>-69.97247</td>\n",
       "      <td>-15.31167</td>\n",
       "      <td>3849</td>\n",
       "      <td>TARACO</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>St_115049</td>\n",
       "      <td>-69.69100</td>\n",
       "      <td>-15.72047</td>\n",
       "      <td>3850</td>\n",
       "      <td>ISLA TAQUILE</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>St_115053</td>\n",
       "      <td>-69.35556</td>\n",
       "      <td>-15.01667</td>\n",
       "      <td>4344</td>\n",
       "      <td>COJATA</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>St_114041</td>\n",
       "      <td>-70.19075</td>\n",
       "      <td>-14.91436</td>\n",
       "      <td>3863</td>\n",
       "      <td>AZANGARO</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>St_116061</td>\n",
       "      <td>-69.45992</td>\n",
       "      <td>-16.20378</td>\n",
       "      <td>3812</td>\n",
       "      <td>JULI</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>St_116060</td>\n",
       "      <td>-69.03883</td>\n",
       "      <td>-16.56335</td>\n",
       "      <td>3808</td>\n",
       "      <td>DESAGUADERO</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>St_114096</td>\n",
       "      <td>-69.54900</td>\n",
       "      <td>-14.48892</td>\n",
       "      <td>3414</td>\n",
       "      <td>CUYO CUYO</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>St_113119</td>\n",
       "      <td>-70.40492</td>\n",
       "      <td>-13.44081</td>\n",
       "      <td>635</td>\n",
       "      <td>SAN GABAN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>St_116026</td>\n",
       "      <td>-69.71547</td>\n",
       "      <td>-16.73900</td>\n",
       "      <td>4003</td>\n",
       "      <td>MAZO CRUZ</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ESTACIONES       LON       LAT  ALTURA            NAME  Unnamed: 5\n",
       "0   St_100110 -70.01208 -15.82625    3812            PUNO         NaN\n",
       "1   St_114035 -70.71569 -14.78478    3971  CHUQUIBAMBILLA         NaN\n",
       "2   St_114040 -70.02353 -14.69011    3980        PROGRESO         NaN\n",
       "3   St_115044 -70.91242 -15.76446    4521    CRUCERO ALTO         NaN\n",
       "4   St_115047 -69.97247 -15.31167    3849          TARACO         NaN\n",
       "5   St_115049 -69.69100 -15.72047    3850    ISLA TAQUILE         NaN\n",
       "6   St_115053 -69.35556 -15.01667    4344          COJATA         NaN\n",
       "7   St_114041 -70.19075 -14.91436    3863        AZANGARO         NaN\n",
       "8   St_116061 -69.45992 -16.20378    3812            JULI         NaN\n",
       "9   St_116060 -69.03883 -16.56335    3808     DESAGUADERO         NaN\n",
       "10  St_114096 -69.54900 -14.48892    3414       CUYO CUYO         NaN\n",
       "11  St_113119 -70.40492 -13.44081     635       SAN GABAN         NaN\n",
       "12  St_116026 -69.71547 -16.73900    4003       MAZO CRUZ         NaN"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "location"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-70.01208, -70.71569, -70.02353, -70.91242, -69.97247, -69.691  ,\n",
       "       -69.35556, -70.19075, -69.45992, -69.03883, -69.549  , -70.40492,\n",
       "       -69.71547])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "location.LON.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: cartopy in c:\\users\\betza\\anaconda3\\lib\\site-packages (0.19.0.post1)\n",
      "Requirement already satisfied: numpy>=1.13.3 in c:\\users\\betza\\anaconda3\\lib\\site-packages (from cartopy) (1.20.1)\n",
      "Requirement already satisfied: pyshp>=2 in c:\\users\\betza\\anaconda3\\lib\\site-packages (from cartopy) (2.1.3)\n",
      "Requirement already satisfied: shapely>=1.5.6 in c:\\users\\betza\\anaconda3\\lib\\site-packages (from cartopy) (1.7.1)\n",
      "Note: you may need to restart the kernel to use updated packages.\n"
     ]
    }
   ],
   "source": [
    "pip install cartopy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x247145a7a00>"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mapa de PCs con corr F\n",
    "\n",
    "import cartopy.crs as ccrs\n",
    "from cartopy.io.shapereader import Reader\n",
    "from cartopy.feature import ShapelyFeature\n",
    "import matplotlib.ticker as mticker\n",
    "from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\n",
    "\n",
    "\n",
    "fname = 'INEI_LIMITE_DEPARTAMENTAL_GEOGPSPERU_JUANSUYO_931381206.shp'\n",
    "shape_feature = ShapelyFeature(Reader(fname).geometries(),\n",
    "                              ccrs.PlateCarree(), facecolor='none',edgecolor='k',linewidth=0.5 )\n",
    "\n",
    "plain_crs = ccrs.PlateCarree()\n",
    "puno_extent = [-71.25, -68.7, -17.4,-12.9]\n",
    "to_test = [(plain_crs, puno_extent)]\n",
    "\n",
    "projection=plain_crs\n",
    "extent=puno_extent\n",
    "\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "ax = fig.add_subplot(1, 1, 1, projection=projection)\n",
    "ax.add_feature(shape_feature)\n",
    "\n",
    "ax.set_extent(extent, crs=plain_crs)\n",
    "\n",
    "ax.set_xticks([-71,-70,-69], crs=ccrs.PlateCarree())\n",
    "ax.set_yticks([-17.5,-17,-16.5,-16,-15.5,-15,-14.5,-14,-13.5,-13], crs=ccrs.PlateCarree())\n",
    "lon_formatter = LongitudeFormatter(zero_direction_label=True,\n",
    "                                   number_format='.1f')\n",
    "lat_formatter = LatitudeFormatter(number_format='.1f')\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "\n",
    "x=location.LON.values.tolist()\n",
    "y=location.LAT.values.tolist()\n",
    "\n",
    "\n",
    "plt.scatter(x, y, c=list(matriz_F_corr[:,0]),s=200,cmap='bwr',vmin=-1, vmax=1)\n",
    "\n",
    "    \n",
    "plt.title(\"EOF-1 with corr\")\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x24715282ca0>"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mapa de PCs con corr F\n",
    "\n",
    "import cartopy.crs as ccrs\n",
    "from cartopy.io.shapereader import Reader\n",
    "from cartopy.feature import ShapelyFeature\n",
    "import matplotlib.ticker as mticker\n",
    "from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\n",
    "\n",
    "\n",
    "fname = 'INEI_LIMITE_DEPARTAMENTAL_GEOGPSPERU_JUANSUYO_931381206.shp'\n",
    "shape_feature = ShapelyFeature(Reader(fname).geometries(),\n",
    "                              ccrs.PlateCarree(), facecolor='none',edgecolor='k',linewidth=0.5 )\n",
    "\n",
    "plain_crs = ccrs.PlateCarree()\n",
    "puno_extent = [-71.25, -68.7, -17.4,-12.9]\n",
    "to_test = [(plain_crs, puno_extent)]\n",
    "\n",
    "projection=plain_crs\n",
    "extent=puno_extent\n",
    "\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "ax = fig.add_subplot(1, 1, 1, projection=projection)\n",
    "ax.add_feature(shape_feature)\n",
    "\n",
    "ax.set_extent(extent, crs=plain_crs)\n",
    "\n",
    "ax.set_xticks([-71,-70,-69], crs=ccrs.PlateCarree())\n",
    "ax.set_yticks([-17.5,-17,-16.5,-16,-15.5,-15,-14.5,-14,-13.5,-13], crs=ccrs.PlateCarree())\n",
    "lon_formatter = LongitudeFormatter(zero_direction_label=True,\n",
    "                                   number_format='.1f')\n",
    "lat_formatter = LatitudeFormatter(number_format='.1f')\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "x=location.LON.values.tolist()\n",
    "y=location.LAT.values.tolist()\n",
    "\n",
    "\n",
    "\n",
    "plt.scatter(x, y, c=list(matriz_F_corr[:,1]),s=200,cmap='bwr',vmin=-1, vmax=1)\n",
    "\n",
    "    \n",
    "plt.title(\"EOF-2 with corr\")\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x24715184d90>"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# mapa de PCs con corr F\n",
    "\n",
    "import cartopy.crs as ccrs\n",
    "from cartopy.io.shapereader import Reader\n",
    "from cartopy.feature import ShapelyFeature\n",
    "import matplotlib.ticker as mticker\n",
    "from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter\n",
    "\n",
    "\n",
    "fname = 'INEI_LIMITE_DEPARTAMENTAL_GEOGPSPERU_JUANSUYO_931381206.shp'\n",
    "shape_feature = ShapelyFeature(Reader(fname).geometries(),\n",
    "                              ccrs.PlateCarree(), facecolor='none',edgecolor='k',linewidth=0.5 )\n",
    "\n",
    "plain_crs = ccrs.PlateCarree()\n",
    "puno_extent = [-71.25, -68.7, -17.4,-12.9]\n",
    "to_test = [(plain_crs, puno_extent)]\n",
    "\n",
    "projection=plain_crs\n",
    "extent=puno_extent\n",
    "\n",
    "fig = plt.figure(figsize=(8, 6))\n",
    "ax = fig.add_subplot(1, 1, 1, projection=projection)\n",
    "ax.add_feature(shape_feature)\n",
    "\n",
    "ax.set_extent(extent, crs=plain_crs)\n",
    "\n",
    "ax.set_xticks([-71,-70,-69], crs=ccrs.PlateCarree())\n",
    "ax.set_yticks([-17.5,-17,-16.5,-16,-15.5,-15,-14.5,-14,-13.5,-13], crs=ccrs.PlateCarree())\n",
    "lon_formatter = LongitudeFormatter(zero_direction_label=True,\n",
    "                                   number_format='.1f')\n",
    "lat_formatter = LatitudeFormatter(number_format='.1f')\n",
    "ax.xaxis.set_major_formatter(lon_formatter)\n",
    "ax.yaxis.set_major_formatter(lat_formatter)\n",
    "\n",
    "\n",
    "x=location.LON.values.tolist()\n",
    "y=location.LAT.values.tolist()\n",
    "\n",
    "plt.scatter(x, y, c=list(matriz_F_corr[:,2]),s=200,cmap='bwr',vmin=-1, vmax=1)\n",
    "\n",
    "    \n",
    "plt.title(\"EOF-3 with corr\")\n",
    "plt.colorbar()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}