{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "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>YEAR</th>\n",
       "      <th>MON</th>\n",
       "      <th>DAY</th>\n",
       "      <th>PP</th>\n",
       "      <th>TMAX</th>\n",
       "      <th>TMIN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>17.5</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>12.1</td>\n",
       "      <td>18.1</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5.5</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>12.1</td>\n",
       "      <td>17.6</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>16.0</td>\n",
       "      <td>3.2</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32137</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>27</td>\n",
       "      <td>3.1</td>\n",
       "      <td>15.6</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32138</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>28</td>\n",
       "      <td>2.2</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32139</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.4</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32140</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>30</td>\n",
       "      <td>2.3</td>\n",
       "      <td>17.6</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32141</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.2</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32142 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       YEAR  MON  DAY    PP  TMAX  TMIN\n",
       "0      1931    1    1  10.0  17.5   2.2\n",
       "1      1931    1    2  12.1  18.1   1.8\n",
       "2      1931    1    3   5.5  19.0   3.1\n",
       "3      1931    1    4  12.1  17.6   4.5\n",
       "4      1931    1    5   4.5  16.0   3.2\n",
       "...     ...  ...  ...   ...   ...   ...\n",
       "32137  2018   12   27   3.1  15.6   6.5\n",
       "32138  2018   12   28   2.2  18.0   5.0\n",
       "32139  2018   12   29   0.0  18.4   4.0\n",
       "32140  2018   12   30   2.3  17.6   4.5\n",
       "32141  2018   12   31   0.0  16.2   4.0\n",
       "\n",
       "[32142 rows x 6 columns]"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%reset -sf\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "file=\"chuquibambilla_diario.xlsx\"\n",
    "df=pd.read_excel(file)\n",
    "df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "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>YEAR</th>\n",
       "      <th>MON</th>\n",
       "      <th>DAY</th>\n",
       "      <th>PP</th>\n",
       "      <th>TMAX</th>\n",
       "      <th>TMIN</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1931-01-01</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>10.0</td>\n",
       "      <td>17.5</td>\n",
       "      <td>2.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931-01-02</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>12.1</td>\n",
       "      <td>18.1</td>\n",
       "      <td>1.8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931-01-03</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>5.5</td>\n",
       "      <td>19.0</td>\n",
       "      <td>3.1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931-01-04</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>12.1</td>\n",
       "      <td>17.6</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1931-01-05</th>\n",
       "      <td>1931</td>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>4.5</td>\n",
       "      <td>16.0</td>\n",
       "      <td>3.2</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-27</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>27</td>\n",
       "      <td>3.1</td>\n",
       "      <td>15.6</td>\n",
       "      <td>6.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-28</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>28</td>\n",
       "      <td>2.2</td>\n",
       "      <td>18.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-29</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>29</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.4</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-30</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>30</td>\n",
       "      <td>2.3</td>\n",
       "      <td>17.6</td>\n",
       "      <td>4.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>2018</td>\n",
       "      <td>12</td>\n",
       "      <td>31</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.2</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>32142 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            YEAR  MON  DAY    PP  TMAX  TMIN\n",
       "FECHA                                       \n",
       "1931-01-01  1931    1    1  10.0  17.5   2.2\n",
       "1931-01-02  1931    1    2  12.1  18.1   1.8\n",
       "1931-01-03  1931    1    3   5.5  19.0   3.1\n",
       "1931-01-04  1931    1    4  12.1  17.6   4.5\n",
       "1931-01-05  1931    1    5   4.5  16.0   3.2\n",
       "...          ...  ...  ...   ...   ...   ...\n",
       "2018-12-27  2018   12   27   3.1  15.6   6.5\n",
       "2018-12-28  2018   12   28   2.2  18.0   5.0\n",
       "2018-12-29  2018   12   29   0.0  18.4   4.0\n",
       "2018-12-30  2018   12   30   2.3  17.6   4.5\n",
       "2018-12-31  2018   12   31   0.0  16.2   4.0\n",
       "\n",
       "[32142 rows x 6 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "date1 = \"1931-01-01\"\n",
    "date2 = \"2018-12-31\"\n",
    "\n",
    "mydates = pd.date_range(date1,date2)\n",
    "df[\"FECHA\"]=mydates\n",
    "data_idx=df.set_index(\"FECHA\")\n",
    "data_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x168e7551248>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYMAAAD4CAYAAAAO9oqkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAXR0lEQVR4nO3df4xd5X3n8fdnSROxaaNACbMupmsqOdVCvEvDCJCiraZLA4asalItuyAUTILkJAJtI/mPmrYSUVgk2q0biSil62wsjJRC0BKKFZwSx8qIVgqJTcJiCGE9EDcMtrASswkTKqrJfveP+0y5Nnd++I7nji/zfklX99zvec59nnk44w/n3DP3pKqQJK1s/2K5ByBJWn6GgSTJMJAkGQaSJAwDSRLwtuUeQL/OOuusWrNmTV/b/vznP+ed73znyR3QW5DztDDO08I4Twuz1PP0xBNP/Liq3nN8fWjDYM2aNezbt6+vbcfHxxkbGzu5A3oLcp4WxnlaGOdpYZZ6npL8Q6+6p4kkSYaBJMkwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAksQQ/wWyNJ81Wx4ZSD+b101zY1dfB+/80ED6lU4mjwwkSYaBJMkwkCRhGEiSMAwkSRgGkiQWEAZJzk3yzSTPJnkmyR+0+plJdic50J7PaPUkuSvJRJKnkry/6702tvYHkmzsql+UZH/b5q4kWYofVpLU20KODKaBzVX1b4BLgZuTnA9sAfZU1VpgT3sNcCWwtj02AXdDJzyA24BLgIuB22YCpLXZ1LXd+sX/aJKkhZo3DKrqcFV9ty2/CjwLnANsAHa0ZjuAq9vyBuDe6ngceHeSVcAVwO6qOlpVrwC7gfVt3buq6ltVVcC9Xe8lSRqAE/oL5CRrgN8Cvg2MVNVh6ARGkrNbs3OAF7s2m2y1ueqTPeq9+t9E5wiCkZERxsfHT2T4/2xqaqrvbVeSYZ+nzeumB9LPyOnH9jXMc7aUhn1/GpTlmqcFh0GSXwYeBD5VVT+b47R+rxXVR/3NxaptwDaA0dHR6vem0d6Ye2GGfZ5uHODXUWzd/8av0sHrxwbS77AZ9v1pUJZrnhZ0NVGSX6ITBF+qqq+08svtFA/t+UirTwLndm2+Gjg0T311j7okaUAWcjVRgC8Cz1bVX3St2gnMXBG0EXi4q35Du6roUuCn7XTSo8DlSc5oHxxfDjza1r2a5NLW1w1d7yVJGoCFnCb6APARYH+SJ1vtj4A7gQeS3AT8CLimrdsFXAVMAK8BHwWoqqNJbgf2tnafqaqjbfmTwD3A6cDX2kOSNCDzhkFV/T29z+sDXNajfQE3z/Je24HtPer7gPfNNxZJ0tLwL5AlSYaBJMkwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAkYRhIkjAMJEkYBpIkDANJEoaBJImF3fZye5IjSZ7uqn05yZPtcXDmDmhJ1iT5x651f9W1zUVJ9ieZSHJXu8UlSc5MsjvJgfZ8xlL8oJKk2S3kyOAeYH13oar+S1VdWFUXAg8CX+la/fzMuqr6RFf9bmATsLY9Zt5zC7CnqtYCe9prSdIAzRsGVfUYcLTXuvZ/9/8ZuG+u90iyCnhXVX2r3RbzXuDqtnoDsKMt7+iqS5IGZN57IM/j3wMvV9WBrtp5Sb4H/Az4k6r6O+AcYLKrzWSrAYxU1WGAqjqc5OzZOkuyic7RBSMjI4yPj/c16Kmpqb63XUmGfZ42r5seSD8jpx/b1zDP2VIa9v1pUJZrnhYbBtdx7FHBYeDXq+onSS4C/ibJBUB6bFsn2llVbQO2AYyOjtbY2NiJj5jOL2u/264kwz5PN255ZCD9bF43zdb9b/wqHbx+bCD9Dpth358GZbnmqe8wSPI24PeBi2ZqVfU68HpbfiLJ88B76RwJrO7afDVwqC2/nGRVOypYBRzpd0ySpP4s5tLS3wV+UFX/fPonyXuSnNaWf4POB8UvtNNArya5tH3OcAPwcNtsJ7CxLW/sqkuSBmQhl5beB3wL+M0kk0luaquu5c0fHP828FSS/w38L+ATVTXz4fMngf8JTADPA19r9TuBDyY5AHywvZYkDdC8p4mq6rpZ6jf2qD1I51LTXu33Ae/rUf8JcNl845AkLR3/AlmSZBhIkgwDSRKGgSQJw0CShGEgScIwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAksbCb22xPciTJ0121Tyd5KcmT7XFV17pbk0wkeS7JFV319a02kWRLV/28JN9OciDJl5O8/WT+gJKk+S3kyOAeYH2P+mer6sL22AWQ5Hw6d0C7oG3zl0lOa7fC/DxwJXA+cF1rC/Cn7b3WAq8ANx3fkSRpac0bBlX1GHB0vnbNBuD+qnq9qn5I5xaXF7fHRFW9UFX/BNwPbGj3Q/4PdG6RCbADuPoEfwZJ0iLNe9vLOdyS5AZgH7C5ql4BzgEe72oz2WoALx5XvwT4VeD/VtV0j/ZvkmQTsAlgZGSE8fHxvgY+NTXV97YrybDP0+Z10/M3OglGTj+2r2Ges6U07PvToCzXPPUbBncDtwPVnrcCHwPSo23R+wik5mjfU1VtA7YBjI6O1tjY2AkNesb4+Dj9bruSDPs83bjlkYH0s3ndNFv3v/GrdPD6sYH0O2yGfX8alOWap77CoKpenllO8gXgq+3lJHBuV9PVwKG23Kv+Y+DdSd7Wjg6620uSBqSvS0uTrOp6+WFg5kqjncC1Sd6R5DxgLfAdYC+wtl059HY6HzLvrKoCvgn8p7b9RuDhfsYkSerfvEcGSe4DxoCzkkwCtwFjSS6kc0rnIPBxgKp6JskDwPeBaeDmqvpFe59bgEeB04DtVfVM6+IPgfuT/Dfge8AXT9pPJ0lakHnDoKqu61Ge9R/sqroDuKNHfRewq0f9BTpXG0mSlol/gSxJMgwkSYaBJAnDQJKEYSBJwjCQJGEYSJIwDCRJGAaSJAwDSRKGgSQJw0CShGEgScIwkCRhGEiSMAwkSSwgDJJsT3IkydNdtf+e5AdJnkryUJJ3t/qaJP+Y5Mn2+KuubS5Ksj/JRJK7kqTVz0yyO8mB9nzGUvygkqTZLeTI4B5g/XG13cD7qurfAv8HuLVr3fNVdWF7fKKrfjewic59kdd2vecWYE9VrQX2tNeSpAGaNwyq6jHg6HG1r1fVdHv5OLB6rvdIsgp4V1V9q6oKuBe4uq3eAOxoyzu66pKkAZn3HsgL8DHgy12vz0vyPeBnwJ9U1d8B5wCTXW0mWw1gpKoOA1TV4SRnz9ZRkk10ji4YGRlhfHy8rwFPTU31ve1KMuzztHnd9PyNToKR04/ta5jnbCkN+/40KMs1T4sKgyR/DEwDX2qlw8CvV9VPklwE/E2SC4D02LxOtL+q2gZsAxgdHa2xsbG+xj0+Pk6/264kwz5PN255ZCD9bF43zdb9b/wqHbx+bCD9Dpth358GZbnmqe8wSLIR+I/AZe3UD1X1OvB6W34iyfPAe+kcCXSfSloNHGrLLydZ1Y4KVgFH+h2TJKk/fV1ammQ98IfA71XVa1319yQ5rS3/Bp0Pil9op4FeTXJpu4roBuDhttlOYGNb3thVlyQNyLxHBknuA8aAs5JMArfRuXroHcDudoXo4+3Kod8GPpNkGvgF8Imqmvnw+ZN0rkw6HfhaewDcCTyQ5CbgR8A1J+UnkyQt2LxhUFXX9Sh/cZa2DwIPzrJuH/C+HvWfAJfNNw5J0tLxL5AlSYaBJMkwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAkYRhIkjAMJEkYBpIkDANJEgsMgyTbkxxJ8nRX7cwku5McaM9ntHqS3JVkIslTSd7ftc3G1v5Au23mTP2iJPvbNne1u6FJkgZkoUcG9wDrj6ttAfZU1VpgT3sNcCWd212uBTYBd0MnPOjcJe0S4GLgtpkAaW02dW13fF+SpCW0oDCoqseAo8eVNwA72vIO4Oqu+r3V8Tjw7naj+yuA3VV1tKpeAXYD69u6d1XVt6qqgHu73kuSNACL+cxgpN3onvZ8dqufA7zY1W6y1eaqT/aoS5IGZN57IPeh1/n+6qP+5jdONtE5ncTIyAjj4+N9DXBqaqrvbVeSYZ+nzeumB9LPyOnH9jXMc7aUhn1/GpTlmqfFhMHLSVZV1eF2qudIq08C53a1Ww0cavWx4+rjrb66R/s3qaptwDaA0dHRGhsb69VsXuPj4/S77Uoy7PN045ZHBtLP5nXTbN3/xq/SwevHBtLvsBn2/WlQlmueFnOaaCcwc0XQRuDhrvoN7aqiS4GfttNIjwKXJzmjfXB8OfBoW/dqkkvbVUQ3dL2XJGkAFnRkkOQ+Ov9Xf1aSSTpXBd0JPJDkJuBHwDWt+S7gKmACeA34KEBVHU1yO7C3tftMVc18KP1JOlcsnQ58rT0kSQOyoDCoqutmWXVZj7YF3DzL+2wHtveo7wPet5CxSJJOPv8CWZJkGEiSDANJEoaBJAnDQJKEYSBJwjCQJGEYSJIwDCRJGAaSJAwDSRKGgSQJw0CShGEgScIwkCRhGEiSWEQYJPnNJE92PX6W5FNJPp3kpa76VV3b3JpkIslzSa7oqq9vtYkkWxb7Q0mSTsyC7nTWS1U9B1wIkOQ04CXgITq3ufxsVf15d/sk5wPXAhcAvwZ8I8l72+rPAx8EJoG9SXZW1ff7HZsk6cT0HQbHuQx4vqr+oXNP+542APdX1evAD5NMABe3dRNV9QJAkvtbW8NAkgbkZIXBtcB9Xa9vSXIDsA/YXFWvAOcAj3e1mWw1gBePq1/Sq5Mkm4BNACMjI4yPj/c12Kmpqb63XUmGfZ42r5seSD8jpx/b1zDP2VIa9v1pUJZrnhYdBkneDvwecGsr3Q3cDlR73gp8DOh1yFD0/tyievVVVduAbQCjo6M1NjbW15jHx8fpd9uVZNjn6cYtjwykn83rptm6/41fpYPXjw2k32Ez7PvToCzXPJ2MI4Mrge9W1csAM88ASb4AfLW9nATO7dpuNXCoLc9WlyQNwMm4tPQ6uk4RJVnVte7DwNNteSdwbZJ3JDkPWAt8B9gLrE1yXjvKuLa1lSQNyKKODJL8SzpXAX28q/xnSS6kc6rn4My6qnomyQN0PhieBm6uql+097kFeBQ4DdheVc8sZlySpBOzqDCoqteAXz2u9pE52t8B3NGjvgvYtZixSJL6518gS5IMA0mSYSBJwjCQJGEYSJIwDCRJGAaSJAwDSRKGgSSJk/cV1kNl/0s/Hdg3WnY7eOeHBt6nJC2ERwaSJMNAkmQYSJIwDCRJGAaSJAwDSRInIQySHEyyP8mTSfa12plJdic50J7PaPUkuSvJRJKnkry/6302tvYHkmxc7LgkSQt3so4MfqeqLqyq0fZ6C7CnqtYCe9prgCvp3Pt4LbAJuBs64QHcBlwCXAzcNhMgkqSlt1SniTYAO9ryDuDqrvq91fE48O4kq4ArgN1VdbSqXgF2A+uXaGySpOOcjL9ALuDrSQr4H1W1DRipqsMAVXU4ydmt7TnAi13bTrbabPVjJNlE54iCkZERxsfH+xrwyOmwed10X9suRr/jXS5TU1NDN+Zug/pvfPz+NMxztpSGfX8alOWap5MRBh+oqkPtH/zdSX4wR9v0qNUc9WMLnaDZBjA6OlpjY2N9DBc+96WH2bp/8N/EcfD6sYH3uRjj4+P0O8engkF95cjmddPH7k/7fz6Qfns5lb/yZNj3p0FZrnla9GmiqjrUno8AD9E55/9yO/1Dez7Smk8C53Ztvho4NEddkjQAiwqDJO9M8iszy8DlwNPATmDmiqCNwMNteSdwQ7uq6FLgp+100qPA5UnOaB8cX95qkqQBWOy5khHgoSQz7/XXVfW3SfYCDyS5CfgRcE1rvwu4CpgAXgM+ClBVR5PcDuxt7T5TVUcXOTZJ0gItKgyq6gXg3/Wo/wS4rEe9gJtnea/twPbFjEeS1B//AlmSZBhIkgwDSRKGgSQJw0CShGEgScIwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAksYgwSHJukm8meTbJM0n+oNU/neSlJE+2x1Vd29yaZCLJc0mu6Kqvb7WJJFsW9yNJkk7UYm5uMw1srqrvtltfPpFkd1v32ar68+7GSc4HrgUuAH4N+EaS97bVnwc+SOdeyHuT7Kyq7y9ibJKkE9B3GLR7Fx9uy68meRY4Z45NNgD3V9XrwA+TTAAXt3UT7a5pJLm/tTUMJGlAFnsPZACSrAF+C/g28AHgliQ3APvoHD28QicoHu/abJI3wuPF4+qXzNLPJmATwMjICOPj432Nd+R02Lxuuq9tF6Pf8S6XqampoRtzt0H9N16u/amXU/m/17DvT4OyXPO06DBI8svAg8CnqupnSe4GbgeqPW8FPgakx+ZF788tqldfVbUN2AYwOjpaY2NjfY35c196mK37T0oOnpCD148NvM/FGB8fp985PhXcuOWRgfSzed30suxPvZzK+9iw70+DslzztKg9OMkv0QmCL1XVVwCq6uWu9V8AvtpeTgLndm2+GjjUlmerS5IGYDFXEwX4IvBsVf1FV31VV7MPA0+35Z3AtUnekeQ8YC3wHWAvsDbJeUneTudD5p39jkuSdOIWc2TwAeAjwP4kT7baHwHXJbmQzqmeg8DHAarqmSQP0PlgeBq4uap+AZDkFuBR4DRge1U9s4hxSZJO0GKuJvp7en8OsGuObe4A7uhR3zXXdpKkpeVfIEuSDANJkmEgScIwkCRhGEiSMAwkSRgGkiQMA0kShoEkCcNAkoRhIEnCMJAkYRhIkjAMJEkYBpIkDANJEqdQGCRZn+S5JBNJtiz3eCRpJVnMbS9PmiSnAZ8HPghMAnuT7Kyq7y/vyKThsmbLI8vS78E7P7Qs/erkOVWODC4GJqrqhar6J+B+YMMyj0mSVoxT4sgAOAd4sev1JHDJ8Y2SbAI2tZdTSZ7rs7+zgB/3uW3f8qeD7nHRlmWehs1/dZ4Wum+v+HlaoKWep3/dq3iqhEF61OpNhaptwLZFd5bsq6rRxb7PW53ztDDO08I4TwuzXPN0qpwmmgTO7Xq9Gji0TGORpBXnVAmDvcDaJOcleTtwLbBzmcckSSvGKXGaqKqmk9wCPAqcBmyvqmeWsMtFn2paIZynhXGeFsZ5WphlmadUvenUvCRphTlVThNJkpaRYSBJemuHQZJrkjyT5P8lGT1u3a3tqy+eS3JFV33Ffy1Gkk8neSnJk+1xVde6nvO2Urm/zC7JwST72z60r9XOTLI7yYH2fMZyj3PQkmxPciTJ0121nvOSjrva/vVUkvcv1bje0mEAPA38PvBYdzHJ+XSuWLoAWA/8ZZLTur4W40rgfOC61nYl+mxVXdgeu2D2eVvOQS4n95cF+Z22D838z9gWYE9VrQX2tNcrzT10fn+6zTYvVwJr22MTcPdSDeotHQZV9WxV9for5Q3A/VX1elX9EJig85UYfi3G3Gabt5XK/eXEbQB2tOUdwNXLOJZlUVWPAUePK882LxuAe6vjceDdSVYtxbje0mEwh15ff3HOHPWV6JZ2WLq961De+TmW8zG3Ar6e5In2VTIAI1V1GKA9n71sozu1zDYvA9vHTom/M1iMJN8A/lWPVX9cVQ/PtlmPWtE7HN+S197ONW90DkVvp/Oz3w5sBT7GAr82ZAVxPub2gao6lORsYHeSHyz3gIbQwPaxoQ+DqvrdPjab6+svVsTXYix03pJ8Afhqe+nXhhzL+ZhDVR1qz0eSPETntNrLSVZV1eF2uuPIsg7y1DHbvAxsH1upp4l2AtcmeUeS8+h8OPMd/FoMAI47J/lhOh/Ew+zztlK5v8wiyTuT/MrMMnA5nf1oJ7CxNdsIzHb0vtLMNi87gRvaVUWXAj+dOZ10sg39kcFcknwY+BzwHuCRJE9W1RVV9UySB4DvA9PAzVX1i7bNIL8W41T1Z0kupHM4ehD4OMBc87YSLcPXqAyTEeChJND5d+avq+pvk+wFHkhyE/Aj4JplHOOySHIfMAaclWQSuA24k97zsgu4is7FGq8BH12ycfl1FJKklXqaSJLUxTCQJBkGkiTDQJKEYSBJwjCQJGEYSJKA/w/vvwPQXHZMSQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "pp_data=data_idx[\"PP\"]\n",
    "pp_data.hist() #-99.9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FECHA\n",
       "1931-12-31     24.0\n",
       "1932-12-31    105.5\n",
       "1933-12-31     46.3\n",
       "1934-12-31     62.0\n",
       "1935-12-31     68.0\n",
       "              ...  \n",
       "2014-12-31     32.1\n",
       "2015-12-31     47.6\n",
       "2016-12-31     38.1\n",
       "2017-12-31     29.7\n",
       "2018-12-31     32.6\n",
       "Freq: A-DEC, Name: PP, Length: 88, dtype: float64"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# annual maximum daily rainfall (AMDR)\n",
    "\n",
    "pp_data_amdr=pp_data.groupby(pd.Grouper(freq=\"Y\")).max()\n",
    "pp_data_amdr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x168e9523888>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAD4CAYAAADlwTGnAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAYSklEQVR4nO3df5BV533f8feni0EOtVCDqh0HiBYP1DUS4yTeAbV2OzcmUtDI8SoTGK1KLZKhszOJmaQNnhZ1xmrCKDOmU6rWY+rxxuAgpg5ocFRvK2TiBN9xydgEVMmRkMxkjTdlhRqFgVBdXITB3/5xnm1vru6yZ2Hvj93n85rZ2XOe85znPs+5d/dzz3N/HEUEZmaWn7/V6Q6YmVlnOADMzDLlADAzy5QDwMwsUw4AM7NMzet0B6bjzjvvjL6+vk53o7TLly+zcOHCTnejY3IfP/gY5D5+6I5j8MILL5yPiL/bWD6rAqCvr4+TJ092uhulVatVKpVKp7vRMbmPH3wMch8/dMcxkPQXzco9BWRmlikHgJlZphwAZmaZcgCYmWXKAWBmlikHgJlZphwAZmaZcgCYmWXKAWBmlqlZ9Ung2ahv+3Mdu+2xzzzUsds2s+7nMwAzs0w5AMzMMuUAMDPLlAPAzCxTDgAzs0w5AMzMMuUAMDPLlAPAzCxTpQJA0npJpyWNStreZPsCSQfT9uOS+hq2/6SkmqRPlW3TzMxaa8oAkNQD7AYeBFYBj0pa1VBtC3AxIlYATwE7G7Y/BTw/zTbNzKyFypwBrAFGI+JMRFwFDgADDXUGgH1p+RCwTpIAJD0MnAFOTbNNMzNroTLfBbQEOFu3Pg6snaxORFyTdAlYLOn/AP8KuB/4VLP6N2gTAElDwBBAb28v1Wq1RJe7Q61WY9vq6x27/U4fq1qt1vE+dFruxyD38UN3H4MyAaAmZVGyzm8DT0VELZ0QTKfNojBiGBgG6O/vj0qlMlV/u0a1WmXXscsdu/2xTZWO3TYU459N91cr5H4Mch8/dPcxKBMA48CyuvWlwLlJ6oxLmgcsAi5QPKvfIOnfAncAP5J0BXihRJtmZtZCZQLgBLBS0nLgdWAQ+CcNdUaAzcC3gA3A0YgI4B9NVJD0W0AtIj6XQmKqNs3MrIWmDIA0p78VOAL0AHsj4pSkHcDJiBgB9gD7JY1SPPMfvJk2b3EsZmY2DaUuCBMRh4HDDWVP1C1fATZO0cZvTdWmmZm1jz8JbGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZpkqdT0Am536tj/Xkdsd+8xDHbldM5ueUmcAktZLOi1pVNL2JtsXSDqYth+X1JfK10h6Kf18R9Iv1u0zJunltO3kTA3IzMzKmfIMQFIPsBu4n+Li7yckjUTEq3XVtgAXI2KFpEFgJ/AI8ArQny4B+V7gO5L+a0RcS/v9bEScn8kBmZlZOWXOANYAoxFxJiKuAgeAgYY6A8C+tHwIWCdJEfGDun/2twExE502M7NbV+Y1gCXA2br1cWDtZHXSs/1LwGLgvKS1wF7gbuATdYEQwB9KCuALETHc7MYlDQFDAL29vVSr1TLj6gq1Wo1tq693uhttN3Ef1Wq1WXV/tULuxyD38UN3H4MyAaAmZY3P5CetExHHgXskfQDYJ+n5dBH5D0fEOUl3AV+X9N2I+OY7GimCYRigv78/KpVKiS53h2q1yq5jlzvdjbYb21QBivHPpvurFXI/BrmPH7r7GJSZAhoHltWtLwXOTVZH0jxgEXChvkJEvAZcBu5N6+fS7zeBZymmmszMrE3KBMAJYKWk5ZLmA4PASEOdEWBzWt4AHI2ISPvMA5B0N/B+YEzSQknvSeULgQcoXjA2M7M2mXIKKM3pbwWOAD3A3og4JWkHcDIiRoA9wH5JoxTP/AfT7h8Btkv6IfAj4Nci4ryk9wHPSprow5cj4mszPTgzM5tcqQ+CRcRh4HBD2RN1y1eAjU322w/sb1J+BvjgdDtrZmYzx18FYWaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZpkqFQCS1ks6LWlU0vYm2xdIOpi2H5fUl8rXSHop/XxH0i+WbdPMzFprygCQ1APsBh4EVgGPSlrVUG0LcDEiVgBPATtT+StAf0T8FLAe+IKkeSXbNDOzFipzBrAGGI2IMxFxFTgADDTUGQD2peVDwDpJiogfRMS1VH4bENNo08zMWqjMJSGXAGfr1seBtZPVSdcQvgQsBs5LWgvsBe4GPpG2l2kTAElDwBBAb28v1Wq1RJe7Q61WY9vq653uRttN3Ee1Wm1W3V+tkPsxyH380N3HoEwAqElZlK0TEceBeyR9ANgn6fmSbZL2HwaGAfr7+6NSqZTocneoVqvsOna5091ou7FNFaAY/2y6v1oh92OQ+/ihu49BmSmgcWBZ3fpS4NxkdSTNAxYBF+orRMRrwGXg3pJtmplZC5UJgBPASknLJc0HBoGRhjojwOa0vAE4GhGR9pkHIOlu4P3AWMk2zcyshaacAkpz9luBI0APsDciTknaAZyMiBFgD7Bf0ijFM//BtPtHgO2Sfgj8CPi1iDgP0KzNGR6bmZndQJnXAIiIw8DhhrIn6pavABub7Lcf2F+2TTMzax9/EtjMLFMOADOzTDkAzMwy5QAwM8uUA8DMLFMOADOzTDkAzMwy5QAwM8uUA8DMLFMOADOzTDkAzMwy5QAwM8uUA8DMLFMOADOzTDkAzMwyVSoAJK2XdFrSqKTtTbYvkHQwbT8uqS+V3y/pBUkvp98frdunmtp8Kf3cNVODMjOzqU15QRhJPcBu4H6Ka/mekDQSEa/WVdsCXIyIFZIGgZ3AI8B54Bci4pykeymuALakbr9NEXFyhsZiZmbTUOYMYA0wGhFnIuIqcAAYaKgzAOxLy4eAdZIUES9GxMTF3k8Bt0laMBMdNzOzW1PmkpBLgLN16+PA2snqpGsIXwIWU5wBTPgl4MWIeLuu7EuSrgNfAZ6MiGi8cUlDwBBAb28v1Wq1RJe7Q61WY9vq653uRttN3Ee1Wm1W3V+tkPsxyH380N3HoEwAqElZ4z/qG9aRdA/FtNADdds3RcTrkt5DEQCfAJ5+RyMRw8AwQH9/f1QqlRJd7g7VapVdxy53uhttN7apAhTjn033VyvkfgxyHz909zEoMwU0DiyrW18KnJusjqR5wCLgQlpfCjwLPBYR35vYISJeT7/fAr5MMdVkZmZtUiYATgArJS2XNB8YBEYa6owAm9PyBuBoRISkO4DngMcj4k8mKkuaJ+nOtPwu4GPAK7c2FDMzm44pAyAirgFbKd7B8xrwTESckrRD0sdTtT3AYkmjwG8CE28V3QqsAD7d8HbPBcARSX8GvAS8DvzuTA7MzMxurMxrAETEYeBwQ9kTdctXgI1N9nsSeHKSZj9UvptmZjbT/ElgM7NMOQDMzDLlADAzy5QDwMwsUw4AM7NMOQDMzDLlADAzy5QDwMwsUw4AM7NMOQDMzDLlADAzy5QDwMwsUw4AM7NMOQDMzDLlADAzy1SpAJC0XtJpSaOStjfZvkDSwbT9uKS+VH6/pBckvZx+f7Runw+l8lFJn5XU7LrCZmbWIlMGgKQeYDfwILAKeFTSqoZqW4CLEbECeIriAvAA54FfiIjVFJeM3F+3z+eBIWBl+ll/C+MwM7NpKnMGsAYYjYgzEXEVOAAMNNQZAPal5UPAOkmKiBcjYuIC8qeA29LZwnuB2yPiWxERwNPAw7c8GjMzK61MACwBztatj6eypnXSNYQvAYsb6vwS8GJEvJ3qj0/RppmZtVCZawI3m5uP6dSRdA/FtNAD02hzYt8hiqkient7qVarU3S3e9RqNbatvt7pbrTdxH1Uq9Vm1f3VCrkfg9zHD919DMoEwDiwrG59KXBukjrjkuYBi4ALAJKWAs8Cj0XE9+rqL52iTQAiYhgYBujv749KpVKiy92hWq2y69jlTnej7cY2VYBi/LPp/mqF3I9B7uOH7j4GZaaATgArJS2XNB8YBEYa6oxQvMgLsAE4GhEh6Q7gOeDxiPiTicoR8QbwlqT70rt/HgO+eotjMTOzaZgyANKc/lbgCPAa8ExEnJK0Q9LHU7U9wGJJo8BvAhNvFd0KrAA+Leml9HNX2varwBeBUeB7wPMzNSgzM5tamSkgIuIwcLih7Im65SvAxib7PQk8OUmbJ4F7p9NZMzObOf4ksJlZphwAZmaZcgCYmWXKAWBmlikHgJlZphwAZmaZcgCYmWXKAWBmlikHgJlZphwAZmaZcgCYmWXKAWBmlikHgJlZphwAZmaZcgCYmWXKAWBmlqlSASBpvaTTkkYlbW+yfYGkg2n7cUl9qXyxpG9Iqkn6XMM+1dRm45XCzMysDaa8IpikHmA3cD/FxdxPSBqJiFfrqm0BLkbECkmDwE7gEeAK8GmKK381u/rXpnRlMDMza7MyZwBrgNGIOBMRV4EDwEBDnQFgX1o+BKyTpIi4HBHHKILAzMy6SJlrAi8BztatjwNrJ6sTEdckXQIWA+enaPtLkq4DXwGejIhorCBpCBgC6O3tpVqtluhyd6jVamxbfb3T3Wi7ifuoVqvNqvurFXI/BrmPH7r7GJQJADUpa/xHXaZOo00R8bqk91AEwCeAp9/RSMQwMAzQ398flUplyg53i2q1yq5jlzvdjbYb21QBivHPpvurFXI/BrmPH7r7GJSZAhoHltWtLwXOTVZH0jxgEXDhRo1GxOvp91vAlymmmszMrE3KBMAJYKWk5ZLmA4PASEOdEWBzWt4AHG02nTNB0jxJd6bldwEfA16ZbufNzOzmTTkFlOb0twJHgB5gb0SckrQDOBkRI8AeYL+kUYpn/oMT+0saA24H5kt6GHgA+AvgSPrn3wP8EfC7MzoyMzO7oTKvARARh4HDDWVP1C1fATZOsm/fJM1+qFwXzcysFUoFgNl09G1/DoBtq6/xy2m5XcY+81Bbb89sNvNXQZiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWqVIBIGm9pNOSRiVtb7J9gaSDaftxSX2pfLGkb0iqSfpcwz4fkvRy2uezkppdV9jMzFpkygCQ1APsBh4EVgGPSlrVUG0LcDEiVgBPATtT+RXg08CnmjT9eWAIWJl+1t/MAMzM7OaUOQNYA4xGxJmIuAocAAYa6gwA+9LyIWCdJEXE5Yg4RhEE/4+k9wK3R8S30rWDnwYevpWBmJnZ9JS5ItgS4Gzd+jiwdrI66RrCl4DFwPkbtDne0OaSZhUlDVGcKdDb20u1Wi3R5e5Qq9XYtvp6p7vRMb3vLq4K1k7d9vio1Wpd16d2yn380N3HoEwANJubj5uoc1P1I2IYGAbo7++PSqVyg2a7S7VaZdexy53uRsdsW32NXS+396qjY5sqbb29qVSrVWbTY3am5T5+6O5jUGYKaBxYVre+FDg3WR1J84BFwIUp2lw6RZtmZtZCZQLgBLBS0nJJ84FBYKShzgiwOS1vAI6muf2mIuIN4C1J96V3/zwGfHXavTczs5s25fl5mtPfChwBeoC9EXFK0g7gZESMAHuA/ZJGKZ75D07sL2kMuB2YL+lh4IGIeBX4VeD3gHcDz6cfMzNrk1ITtBFxGDjcUPZE3fIVYOMk+/ZNUn4SuLdsR83MbGb5k8BmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWKQeAmVmmHABmZplyAJiZZcoBYGaWqVIBIGm9pNOSRiVtb7J9gaSDaftxSX112x5P5acl/Xxd+ZiklyW9JOnkTAzGzMzKm/KCMJJ6gN3A/RTX8j0haSRd1WvCFuBiRKyQNAjsBB6RtIri6mD3AD8B/JGkvxcR19N+PxsR52dwPJPq2/5cO27mb9i2+holr7ljZtZ2Zc4A1gCjEXEmIq4CB4CBhjoDwL60fAhYl671OwAciIi3I+L7wGhqz8zMOqzM09MlwNm69XFg7WR10jWELwGLU/m3G/ZdkpYD+ENJAXwhIoab3bikIWAIoLe3l2q1WqLL71Q8G2+v3nd35na7RSfGf7OPj1ap1Wpd16d2yn380N3HoEwAqElZlKxzo30/HBHnJN0FfF3SdyPim++oXATDMEB/f39UKpUSXX6nX+7QFNCul/OdAurE+Mc2Vdp6e1OpVqvc7GN2Lsh9/NDdx6DMFNA4sKxufSlwbrI6kuYBi4ALN9o3IiZ+vwk8i6eGzMzaqkwAnABWSlouaT7Fi7ojDXVGgM1peQNwNCIilQ+mdwktB1YCfyppoaT3AEhaCDwAvHLrwzEzs7KmPD9Pc/pbgSNAD7A3Ik5J2gGcjIgRYA+wX9IoxTP/wbTvKUnPAK8C14BPRsR1Sb3As8XrxMwDvhwRX2vB+MzMbBKlJmgj4jBwuKHsibrlK8DGSfb9HeB3GsrOAB+cbmfNzGzm+JPAZmaZcgCYmWXKAWBmlikHgJlZphwAZmaZyvdjqjYndeJL/25k2+prLf8U+thnHmpp+zZ3+QzAzCxTDgAzs0w5AMzMMuUAMDPLlAPAzCxTDgAzs0z5baBms1yn3vqa49tPb+ZYz8RbgVt1rH0GYGaWKQeAmVmmHABmZpkqFQCS1ks6LWlU0vYm2xdIOpi2H5fUV7ft8VR+WtLPl23TzMxaa8oAkNQD7AYeBFYBj0pa1VBtC3AxIlYATwE7076rKC4PeQ+wHvhPknpKtmlmZi1U5gxgDTAaEWci4ipwABhoqDMA7EvLh4B1Ki74OwAciIi3I+L7wGhqr0ybZmbWQmXeBroEOFu3Pg6snaxOuoj8JWBxKv92w75L0vJUbQIgaQgYSqs1SadL9Lkr/DrcCZzvdD86Jffxw9w+BtpZqtqcHX9ZM/EYKHmsb+TuZoVlAkBNyqJkncnKm515NLZZFEYMA8M36mC3knQyIvo73Y9OyX384GOQ+/ihu49BmSmgcWBZ3fpS4NxkdSTNAxYBF26wb5k2zcyshcoEwAlgpaTlkuZTvKg70lBnBNicljcARyMiUvlgepfQcmAl8Kcl2zQzsxaacgoozelvBY4APcDeiDglaQdwMiJGgD3AfkmjFM/8B9O+pyQ9A7wKXAM+GRHXAZq1OfPD67hZOXU1g3IfP/gY5D5+6OJjoOKJupmZ5cafBDYzy5QDwMwsUw6AGSBpmaRvSHpN0ilJv5HKf1zS1yX9efr9dzrd11ZLn/R+UdJ/S+vL09eD/Hn6upD5ne5jq0i6Q9IhSd9Nj4V/kNtjQNK/SH8Dr0j6fUm3zeXHgKS9kt6U9EpdWdP7XIXPpq+/+TNJP9O5nhccADPjGrAtIj4A3Ad8Mn21xXbgjyNiJfDHaX2u+w3gtbr1ncBT6RhcpPjakLnqPwJfi4i/D3yQ4jhk8xiQtAT4daA/Iu6leIPHIHP7MfB7FF9zU2+y+/xBindCrqT4cOvn29THSTkAZkBEvBER/yMtv0Xxh7+Ev/kVGfuAhzvTw/aQtBR4CPhiWhfwUYqvB4E5fAwk3Q78Y4p3xBERVyPir8nsMUDxzsJ3p88D/RjwBnP4MRAR36R452O9ye7zAeDpKHwbuEPSe9vT0+YcADMsfRPqTwPHgd6IeAOKkADu6lzP2uI/AP8S+FFaXwz8dURcS+v1XwUy17wP+CvgS2kK7IuSFpLRYyAiXgf+HfA/Kf7xXwJeIJ/HwITJ7vNmX6vT0WPhAJhBkv428BXgn0fE/+50f9pJ0seANyPihfriJlXn6vuO5wE/A3w+In4auMwcnu5pJs11DwDLgZ8AFlJMezSaq4+BqXTd34MDYIZIehfFP///HBF/kIr/cuIUL/1+s1P9a4MPAx+XNEbx7a4fpTgjuCNNB8Dc/sqPcWA8Io6n9UMUgZDTY+DngO9HxF9FxA+BPwD+Ifk8BiZMdp933VfgOABmQJrr3gO8FhH/vm5T/VdkbAa+2u6+tUtEPB4RSyOij+KFv6MRsQn4BsXXg8AcPgYR8b+As5Len4rWUXwCPpvHAMXUz32Sfiz9TUwcgyweA3Umu89HgMfSu4HuAy5NTBV1ij8JPAMkfQT478DL/P/5739N8TrAM8BPUvxxbIyIxheM5hxJFeBTEfExSe+jOCP4ceBF4J9GxNud7F+rSPopihfA5wNngF+heJKVzWNA0m8Dj1C8M+5F4J9RzHPPyceApN8HKhRf+fyXwL8B/gtN7vMUip+jeNfQD4BfiYiTnej3BAeAmVmmPAVkZpYpB4CZWaYcAGZmmXIAmJllygFgZpYpB4CZWaYcAGZmmfq/Zn2ZYY1AOd0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#removemos filas con -99.9\n",
    "indexrows = pp_data_amdr[pp_data_amdr == -99.9].index\n",
    "pp_data_amdr.drop(indexrows,inplace=True)\n",
    "pp_data_amdr.hist(density=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "FECHA\n",
       "1931-12-31     27.120\n",
       "1932-12-31    119.215\n",
       "1933-12-31     52.319\n",
       "1934-12-31     70.060\n",
       "1935-12-31     76.840\n",
       "               ...   \n",
       "2014-12-31     36.273\n",
       "2015-12-31     53.788\n",
       "2016-12-31     43.053\n",
       "2017-12-31     33.561\n",
       "2018-12-31     36.838\n",
       "Name: PP, Length: 77, dtype: float64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Miller et al 1973, AMDR, 1.13\n",
    "pp_data_amdr=pp_data_amdr*1.13\n",
    "pp_data_amdr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 27.12 , 119.215,  52.319,  70.06 ,  76.84 ,  47.46 ,  38.985,\n",
       "        27.685,  28.815,  38.646,  28.25 ,  36.725,  37.29 ,  36.951,\n",
       "        33.9  ,  35.595,  29.041,  30.736,  30.736,  33.674,  22.713,\n",
       "        27.572,  44.183,  44.07 ,  50.737,  40.68 ,  41.245,  12.769,\n",
       "        12.43 ,  27.233,  28.024,  41.923,  65.088,  33.109,  27.911,\n",
       "        28.589,  49.381,  33.561,  30.397,  52.658,  29.38 ,  17.628,\n",
       "        47.008,  28.815,  30.284,  40.454,  35.369,  30.51 ,  30.962,\n",
       "        47.686,  40.341,  43.279,  39.55 ,  27.572,  27.346,  40.906,\n",
       "        31.64 ,  29.945,  25.199,  59.551,  28.589,  54.014,  47.008,\n",
       "        38.533,  43.844,  31.527,  40.906,  30.058,  66.896,  27.798,\n",
       "        35.03 ,  35.595,  36.273,  53.788,  43.053,  33.561,  36.838])"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#datframe a numpy\n",
    "data=pp_data_amdr.to_numpy()\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import scipy.stats\n",
    "from scipy.stats import norm, pearson3, chi2, lognorm, gumbel_l, gamma\n",
    "from scipy.stats import gumbel_r,genextreme,weibull_min\n",
    "import statsmodels.api as sm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "dist_names=[\"norm\",\"lognorm\",\"gamma\",\"genextreme\",\"gumbel_r\",\"weibull_min\",\"chi2\",\"gumbel_l\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-> norm -kstest:   0.15974785172420305\n",
      "-> lognorm -kstest:   0.13611817480291924\n",
      "-> gamma -kstest:   0.1421196911799853\n",
      "-> genextreme -kstest:   0.13149239345488528\n",
      "-> gumbel_r -kstest:   0.12881125080691389\n",
      "-> weibull_min -kstest:   0.1858130325146953\n",
      "-> chi2 -kstest:   0.14211926245150047\n",
      "-> gumbel_l -kstest:   0.28986357151127573\n"
     ]
    }
   ],
   "source": [
    "ksval=[]\n",
    "\n",
    "percentile_bins=np.linspace(0,100,11)\n",
    "percentile_cutoffs = np.percentile(data,percentile_bins)\n",
    "\n",
    "observed_frequency, bins = (np.histogram(data,bins=percentile_cutoffs,density=True))\n",
    "observed_frequency= np.round(observed_frequency,8)\n",
    "\n",
    "for distribution in dist_names:\n",
    "# esto es para los ajustes a distribucion\n",
    "    bin_centers=0.5*(np.array(bins[1:])+np.array(bins[:-1]))\n",
    "    dist = getattr(scipy.stats, distribution)\n",
    "    param = dist.fit(data)\n",
    "    expected_frequency = dist.pdf(bin_centers, *param)\n",
    "    expected_frquency = np.round(expected_frequency,8)\n",
    "    \n",
    "# Kolmogor Sminor? test\n",
    "    kst=scipy.stats.kstest(data,distribution,param)[0] # solo el D\n",
    "    ksval.append(kst)\n",
    "    \n",
    "    print(\"->\",distribution,\"-kstest:  \",kst)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": [
    "# forma cualitiva, histogramas\n",
    "fig1=plt.figure()\n",
    "plt.hist(data,density=True)\n",
    "\n",
    "for i in dist_names:\n",
    "    \n",
    "    fitbest=getattr(scipy.stats, i)\n",
    "    P = fitbest.fit(data)\n",
    "    rX = np.linspace(0,100,1000)\n",
    "    rP = fitbest.pdf(rX, *P)\n",
    "    plt.plot(rX, rP, label=i)\n",
    "    \n",
    "    plt.legend()\n",
    "    \n",
    "plt.ylim(0,0.04)\n",
    "plt.savefig(\"hist_ajustes_dist_parametricas.png\",dpi=300)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYAAAAEWCAYAAABv+EDhAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nO3debyWc/7H8denUqYiJIy02FVUSLKGDAZjGetMlpFKCmHs2aYR2UaMpFNZ0sGQbIlEQtY2lcr2SymFUCqH1s/vj+91uDud+5z71LnPdS/v5+NxHue+r/taPnfL93t9l+vzNXdHRETyT7W4AxARkXioAhARyVOqAERE8pQqABGRPKUKQEQkT6kCEBHJU6oAJKOY2WFmNj/mGJab2U5xxiBSFVQByG/M7B9mNt3MiszsGzN7wMzqlXNMLTO7zcy+MrNfzOxzM7vCzKwK4n3EzG6pwP6HmdnaqIBfbmbzzewpM9svcT93r+vus1M4V6wVVWUws5vNbFjccUg8VAEIAGb2T+B24EqgHtAOaAq8amablHHo00AH4FhgM+Bs4ALg7nTGuxEWuHtdQqztgE+At82sQ7xhZSYLVE7kKnfXT57/AJsDy4HTS2yvC3wHnJvkuA7Ar0CjEtv3B9YAOyU5bg5wLTATWAw8DGwafXYYMD9h32bAOGAJMAM4IdreFVgFrIxifzGF77nOuRO23w9MTHjvwC7R62OjOJcBXwNXAHWAX4C10bWXA9uncP36wIvAUmACcAswPuHzPYAxwI/Ap4l/H8AjQH/gpSiWD4CdyzsWqAl8BFwcva8OvAPcCBwT/fmtir7D1GifcUCfaL9fgF0INwVDgIXRn8MtQPVo/39E+94T/T3NBg6Mts8r+W8IqAXcBXwFfAs8CPwh7v8H+fgTewD6if8nKghWAzVK+exRoDDJcX2BN5N8NhfokuSzOcDHQCNgq6jwuCX67LdCGtgE+AK4LirIjogKv92jzx8pPi7F7/nbuUtsPyIqzOtE7xMrgIXAIdHrLYF9kp0LOBhYUsb1n4x+agPNo8JxfPRZnej9eUANYB/ge6BFwnf9EWgbfV4IPJnisXsSKtpmQC/g/YTC+2ZgWIk4x0WFc4vofJsAzwEDo2ttA3wIXBDt/4/o3895hArmluj4/oTC/qjo761utH8/4IXo734zQqV4W9z/D/LxR007Adga+N7dV5fy2UKgQRnHLUzyWVnHAdzv7vPc/UfC3ebfStmnHaEV0tfdV7r7WGBkkn03xgLAgC1K+WwV0NzMNnf3xe4+OdlJ3H28u5d2DsysOnAKcJO7F7n7TELlWux4YI67P+zuq6PrPAOcmrDPCHf/MPp7KgRap3Ksu39MKJSfJbRgznb3NWX/kfCIu8+IrrUV8GfgUnf/2d2/I9ztn5mw/5fR9dcA/yNU7r3dfYW7v0poaewSjQ11AS5z9x/dfRlwa4lzSRWpEXcAkhG+B7Y2sxqlVAJ/BBZBmB2TsL15dNyuSc7523FJzEt4PRfYvpR9tgfmufvaEvs2LOO8G6Ih4a5/SSmfnQJcD/Q1s2nANe7+3gZcowHh/1vi90583QTY38wSY6gBPJbw/puE10WEyjHVYx8lVLTPuPvnKcRbMrZNgIUJY/vVSuzzbcLrXwDcveS2uoQ/h9rApIRzGaHlIFVMFYAAvAesAP4KPFW80czqEO78rocwOybxIDN7DbjUzBq5+7yE7W2BxsBbZVyzUcLrxoS78JIWAI3MrFpCJdAY+Cx6XVmpbE8GJrv7zyU/cPcJwInRQPhFhD+fRhtw7UWEbpId+D3+xD+DeYTutD9V8LypHvsAofV0tJkd7O7jo+3Jvkfi9nmEfx9bJ2klVsT3hMqghbt/vZHnko2kLiDB3X8C/gX818yOMbNNzKwpYYbP94TuhtKOew14HXjGzFqYWXUzaxftP9TdPy3jsj3MbAcz24rQx/+/Uvb5APgZuCqK6TDgL4R+dAh3nevM14+mhj5S3neOZrc0NLObgM5RDCX3qWlmHc2snruvIgzeFnedfAvUL2+abLGoa2QEcLOZ1TazPYBzEnYZCexmZmdH33UTM9vPzJqlcPoyjzWzs4F9CX31lwCPmllxZf4t0LSsmT7uvhB4FbjbzDY3s2pmtrOZtU/lu5c411pgEHCPmW0TxdfQzI6u6Llk46kCEADc/Q5CIXgXYcDuS0JT/cjS7owTnAK8AbxCmBH0XvS6azmXfJxQqMyOftabz+/uK4ETCK2Q7wl3see4+yfRLkMI/fNLzOy5aFsjwqByMttHXVnLCTNx9gIOi/qpS3M2MMfMlgLdgLOi2D4BngBmR9ff3swOKdFNVtJFhNk03xC6Z54g3FkT9YUfRegLXxDtczthELVMZR1rZo0Jg67nuPtyd38cmEjow4dQyQP8YGZJxzcIlVVNfp+5NZzQzbchriYM7r8f/bm+Buy+geeSjWDuWhBG1mdmnQitgoPc/asKHPcooU/92KgAL22fOUDnqAVRacysJjAVaBndsWc0M7sd2M7dz407FslPagFIqdz9IUKL4MAKHtqZMB99n0oPqhzRTKFmmVr4m9keZtYy6n5qC5xPmJkjEgsNAktS7v5Y+Xutd8wqQveDrG8zQrfP9oSHo+4Gno81Islr6gISEclT6gISEclTWdUFtPXWW3vTpk3jDkNEJPOtXAlz5sCyZUwKT/qv92R+VlUATZs2ZeLEiXGHISKSudasgf794brrwAzuvx+76KK5pe2qLiARkVwxaxYceij07AmHHAIffww9eiTdXRWAiEi2W7UK+vSB1q3hk09g6FAYNQqaNCnzsKzqAhIRkRImT4ZOnWDqVDjtNPjvf2HbbVM6VC0AEZFs9MsvcM010LYtfPstjBgBTz2VcuEPagGIiGSft96Czp3h88/h/PPhzjthyy0rfBq1AETyQGEhNG0K1aqF34Wl5neVjLd0aRjUbd8+9PuPGQODB29Q4Q9qAYjkvMJC6NoViorC+7lzw3uAjh3ji0sq6OWX4YILYP58uPRSuOUWqFNno06pFoBIjuvV6/fCv1hRUdguWeCHH+Ccc+DYY6FuXXjnHbjnno0u/EEVgEjO+ypJMu9k2yVDuIdB3WbN4Ikn4IYbYMoUOOCASruEKgCRHNe4ccW2SwZYsABOPhnOOCP8RU2cCL17Q61y1weqkFgrADO7zMxmmNnHZvaEmW0aZzwiuahPH6hde91ttWuH7ZJh3GHIEGjeHEaPhjvugPffh1at0nK52CoAM2tIWJ+0jbvvCVQnLGknIpWoY0coKAgPhZqF3wUFGgDOOLNnw5FHhumdrVrBtGlw5ZVQI31zdeKeBVQD+IOZrSKsP7sg5nhEclLHjirwM9aaNeHp3V69oHp1GDAgTNOqlv7789haAO7+NWEB8q+AhcBPpS3MbWZdzWyimU1ctGhRVYcpIpI+M2bAQQfBZZfBYYeF9926VUnhD/F2AW0JnAjsSFgir46ZnVVyP3cvcPc27t6mQYP10lmLiGSflSvh3/+GvfeGL76AYcNg5Eho1KhKw4hzEPhI4Et3XxStIzuCii9ALiKSXSZMgDZt4MYb4ZRTYObM0D9nVuWhxFkBfAW0M7PaZmZAB2BWjPGIiKRPUVEY1G3XLjzc9fzzYX7/NtvEFlJsg8Du/oGZDQcmA6uBKUBBXPGIiKTNuHHQpUvo7unSJSRvq1cv7qjinQXk7jcBN8UZg4hI2vz0E1x9NQwcCDvtBK+/DkccEXdUv9GTwCIi6fDSS9CiBQwaBJdfDtOnZ1ThD6oAREQq16JFYVD3+ONhiy3g3Xfh7rvXfxw7A6gCEBGpDO5hULd5c3j6abj55rBc4/77xx1ZUnE/CSwikv3mz4cLLwxz+du2Dfl89twz7qjKpRaAiMiGWrs2JFZq0SIM8N59d+jyyYLCH9QCEBHZMMVTOseNg8MPD4O9O+8cd1QVohaAiEhFrFkT7vRbtgx9/AUF4e4/ywp/UAtARCR1H38MnTqFdA5/+UvI3NmwYdxRbTC1AEREyrNiRZjVs88+8OWXYbbP889ndeEPagGIiJTtgw/g/PNDquaOHaFfP9h667ijqhRqAYiIlObnn8MTvAccEFI6jBwZ0jbnSOEPagGIiKxv7Ngww2f27LBAy+23w+abxx1VpVMLQESk2JIloeDv0CGsyjVuXBjozcHCH1QBiIgEL7wQHuh66KGQt3/qVGjfPu6o0koVgIjkt+++gzPPhBNPhPr1w6DvHXdkZPK2yqYKQETyk3sY1G3WDJ59NqzRO3FiWK4xT2gQWETyz7x5YXB31KiwROOQISGLZ55RC0BE8sfatWFQt0WLMMDbrx+MH5+XhT+oBSAi+eLzz6FzZ3jrrTDLp6AgLNOYx9QCEJHctnp1GNRt2TLM7BkyBMaMyfvCH9QCEJFcNnVqSOMwaRKcdBL07w/bbx93VBlDLQARyT0rVsANN4QZPfPmwVNPwYgRKvxLUAtARHLLe++Fu/5Zs+Ccc+A//wnz+2U9agGISG5YvhwuvRQOOii8HjUKHn1UhX8Z1AIQkew3Zgx07Qpz5kCPHnDbbbDZZnFHlfHUAhCR7LV4cejuOeooqFkzTPG8/34V/ilSBSAi2enZZ8MDXI8+CtdcE2b8HHJI3FFlFXUBiUh2+eYbuPhiGD4cWreGl14KSzVKhakFICLZwR2GDg13/S+8AH36wIcfqvDfCGoBiEjmmzsXLrgARo+GAw8MT/PusUfcUWW9WFsAZraFmQ03s0/MbJaZHRBnPCKSYdauDU/v7rlnSNp2333w9tsq/CtJ3C2Ae4FX3P1UM6sJ5P4KDCKSmk8/Dcnbxo8Ps3wGDoSmTeOOKqfE1gIws82BQ4EhAO6+0t2XxBWPiGSIVaugb19o1QpmzIBHHoFXXlHhnwZxdgHtBCwCHjazKWY22MzqlNzJzLqa2UQzm7ho0aKqj1JEqs6UKbD//nDttXD88TBzJpx7LpjFHVlOirMCqAHsAwxw972Bn4FrSu7k7gXu3sbd2zRo0KCqYxSRqvDrr3DddbDffrBgQZjiOXw4bLdd3JHltDgrgPnAfHf/IHo/nFAhiEg+eeedMJ//ttvg7LPDXf8pp8QdVV6IrQJw92+AeWa2e7SpAzAzrnhEpIotWxYe6DrkkNACGD0aHn4Yttoq7sjyRoVmAZlZNaCuuy+tpOtfDBRGM4BmA+dV0nlFJJONHh2St82bFyqBPn2gbt24o8o75bYAzOxxM9s8GqCdCXxqZldWxsXd/aOof7+lu5/k7osr47wikqF+/BH+8Q845hioXTvM6b/3XhX+MUmlC6h5dMd/EjAKaAycndaoRCT3DB8OzZrBsGHQq1eY8XPQQXFHlddS6QLaxMw2IVQA97v7KjPzNMclIrli4UK46KKwJOPee4fun9at445KSK0FMBCYA9QB3jKzJkBljQGISK5yD4O6zZuHjJ19+4bkbSr8M0a5LQB3vw+4L2HTXDM7PH0hiUjWmzMnDPKOGRNm+QwaBLvvXu5hUrVSGQTe1syGmNnL0fvmwLlpj0xEss+aNSFh2557hsXZ+/eHceNU+GeoVLqAHgFGA9tH7z8DLk1XQCKSpWbNCnf7PXuG3zNmQPfuUE3LjmSqVP5mtnb3p4C1AO6+GliT1qhEJHusWhXm8bduHTJ4Dh0Ko0ZB48ZxRyblSGUW0M9mVh9wADNrB/yU1qhEJDtMmgSdOsG0aXD66aH7Z9tt445KUpRKBXA58AKws5m9AzQATk1rVCKS2X75Bf71L7jrLmjQICzQftJJcUclFZTKLKDJZtYe2B0w4FN3X5X2yEQkM731Vlio5fPP4fzz4c47Ycst445KNkDSCsDM/prko93MDHcfkaaYRCQTLV0a8vQ/8ADsuCO89hp06BB3VLIRymoB/KWMzxxQBSCSL0aNgm7dYP58uPRSuOUWqLPe+k2SZZJWAO6uzJwi+e777+Gyy0L+nubN4d13oV27uKOSSpJSOmgzOw5oAWxavM3de6crKBGJmTs8/XTI4bN4MdxwQ0jgVqtW3JFJJSq3AjCzB4HawOHAYMIMoA/THJeIxGXBgvAA1/PPw777hr7+li3jjkrSIJUHwQ5093OAxe7+L+AAoFF6wxKRKucOQ4aErp7Ro8PsnvffV+Gfw1LpAvo1+l1kZtsDPwA7pi8kEalys2dDly4wdiy0bw+DB8Muu8QdlaRZKi2AF81sC+BOYDIhNfQT6QxKRKrImjVwzz2w114wYQI8+GCoBFT454UyWwDRGsCvu/sS4BkzGwls6u5KBSGS7WbMCA9yffABHHdcKPx32CHuqKQKldkCcPe1wN0J71eo8BfJcitXQu/eYXWuL76AwkJ48UUV/nkolS6gV83sFDOztEcjIuk1YQK0aQM33QSnnhpSOP/976D/3nkp1WRwdYDVZvYrIR+Qu/vmaY1MRCpPUVEo9P/zH/jjH+GFF+AvZT3sL/kglWRwm1VFICKSJuPGhRk+X3wRlmm84w6oVy/uqCQDpLIk5OupbBORDPPTTyF/z+GHhzn+Y8fCwIEq/OU3ZWUD3ZTwBPDWZrYloesHYHN+Xx5SRDLRyJGh8F+4EP75zzDoW7t23FFJhimrC+gCwtq/2wOT+L0CWAr0T3NcIrIhFi0Ka/I+8URYmH3ECGjbNu6oJEMl7QJy93vdfUfgCnffyd13jH5aufv9VRijSF4oLISmTcMa6k2bhvcpcw+FfvPmMHw43HxzWK5Rhb+UIZVpoN+Y2WYAZna9mY0ws33SHJdIXiksDOOzc+eGsnzu3PA+pUpg/nw44YQwnXOnnWDy5DDjp2bNtMct2S2VCuAGd19mZgcDRwOPAgPSG5ZIfunVK8zUTFRUFLYntXYtFBRAixbw+uthiue774auH5EUpFIBrIl+HwcMcPfnAd1aiFSir76q2Ha++CIsx3jBBSFl8/TpYeGW6tXTFqPknlQqgK/NbCBwOjDKzGqleFxKzKy6mU2J8gyJ5KXGjVPcvno13HVXSN42eTIMGhTu/nfeOe0xSu5JpSA/HRgNHBMlhdsKuLISY+gJzKrE84lknT591p+lWbt22P6b6dPhwAPhyivhT3+CmTOhc2elcZANVm4F4O5FwHfAwdGm1cDnlXFxM9uB0LU0uDLOJ5KtOnYM3flNmoTyvEmT8L5jR2DFijCou88+MGcOPPlkWK2rYcO4w5Ysl8qSkDcBbYDdgYeBTYBhwEGVcP1+wFVA0nQTZtYV6ArQOFk7WSQHdOwYFfiJPvggpGyeMQPOOivk7t9661jik9yTShfQycAJwM8A7r6AMgrsVJnZ8cB37j6prP3cvcDd27h7mwYNGmzsZUWyw88/w+WXwwEHhJQOI0fCY4+p8JdKlUo20JXu7mbmAGZWp5KufRBwgpkdC2wKbG5mw9z9rEo6v0h2Gjs2JG+bPRsuvBD69oXNlXxXKl8qLYCnollAW5hZF+A1YNDGXtjdr3X3Hdy9KXAmMFaFv+S1JUtCwd+hQ3gceNw4eOABFf6SNqmkg77LzP5EyAG0O3Cju49Je2Qi+eT558Pd/rffwlVXhVQOf/hD3FFJjktpPr+7j3H3K939inQU/u4+zt2Pr+zzisQl5bw+330HZ54JJ50EDRqEQd/bb1fhL1UilVlAywCP3tYkzAL6WSuCiZSuOK9PcWqH4rw+kDDLxz3s2LMnLF8O//43XH01bLJJLDFLfkrlOYDN3H3z6GdT4BRA2UBFkig3r8+8eXD88XD22bDbbjBlClx/vQp/qXIVTung7s8BR6QhFpGckCx/z7y5a2HAgJC8bdw46NcPxo8PKZxFYpBKF9BfE95WIzwU5kl2F8l7jRuHbp9Eu/IZj9XqDN3fhiOPDI/57rhjPAGKRFJpAfwl4edoYBlwYjqDEslmiXl9qrOaK7mDqbSidfXp8NBD8OqrKvwlI6QyDfS8qghEJBsUFoa+/K++Cnf6ffqsn76h+P2wK6dyy8JO7MtkvmpzMo1f6A9//GPVBy2SRCpdQDsCFwNNE/d39xPSF5ZI5klpdg/AihV0/OQWOi7qC9tsBf2fpvEppyhrp2Qccy+7O9/MpgJDgOnA2uLt7v5mekNbX5s2bXzixIlVfVkRIMznL9m3DyFz55w50Zv33gvJ22bNgnPOCat01a9fhVGKrM/MJrl7m5LbUxkD+NXd73P3N9z9zeKfNMQokhGSPcRV5qpdy5fDpZfCQQeFRG4vvwyPPqrCXzJaKsng7o1SQr8KrCje6O6T0xaVSEzK6uYpbXYPwN8bjIG9uoZmQI8ecNttsNlGJ8wVSbtUKoC9gLMJc/+Lu4AcPQsgOaish7j69Fm3ctiCxdxb/Z+c893D4YGut96CQw6p+qBFNlAqFcDJwE7uvjLdwYjEraxunuKB3l69YJ+5z/Jg9e5s7Yvg2mvhxhth002rLlCRSpDKGMBUYIt0ByKSCcpbnL1jh2+Ys99pjOCvbLPXdlSb8CHceqsKf8lKqVQA2wKfmNloM3uh+CfdgYnEIeni7Lc4DB0a0ja8+GIo9D/8MKzTK5KlUukCuintUYhkiMRunuKHvfpdNpeThl0Ao0fDgQfCkCGwxx7xBipSCVJ5ElhTPiWv/LY4+9q1YUWua64JH/z3v9C9e5gfKpIDUmkBiOSfTz8ND3S98w4cfTQMHBie+BLJIbqVEUm0alWYx9+qFcycCY88Eh7qUuEvOahCLQAz2xJo5O7T0hSPSHymTAl3/VOmwKmnhi6f7baLOyqRtCm3BWBm48xsczPbijAl9GEz+0/6QxNJr+KUD3+wX+lf7zrWttkPFiyAZ56Bp59W4S85L5UuoHruvhT4K/Cwu+8LHJnesETSqzjlww5zxzOF1vRYehvD7Bye7j0L/vrX8k8gkgNSqQBqmNkfgdOBkWmOR6RK3HrtMm4vuojxHEItVnAUozl3zUNceeuWcYcmUmVSGQPoDYwG3nH3CWa2E/B5esMSSaPRoxk1ryuNmMe9XEIv+vAzdYHkqSBEclEqzwE8DTyd8H42cEo6gxJJix9/hMsug6FDWVVjDw5ePZ73OHCdXZKlghDJRakMAu9mZq+b2cfR+5Zmdn36QxOpRMOHQ7Nm8Pjj0KsXEwqmMLX2uoV/7dohFYRIvkhlDGAQcC2wCiCaAnpmOoMSqTQLF8Ipp8Bpp8EOO8CECXDLLfztvE0pKAjT+83C74KC9df3FcllqYwB1Hb3D23d9UxXpykekcrhHh7iuvxy+OUX6NsX/vlPqPH7P/nfUj6I5KlUKoDvzWxnwiIwmNmpwMK0RiWyMb78MszxfO21sEDL4MFhwRYRWUcqFUAPoADYw8y+Br4EzkprVCIbYs0a6N8/LNBSrVpI5HbBBUreJpJEuf8z3H22ux8JNAD2cPeD3X1O2iMTqYhZs8Ldfs+efL1rew6sN4NqPS6k6U7VKCxMvtC7SD5L2gIws8uTbAfA3TcqHYSZNQKGAtsR1houcPd7N+ackodWrYI77oDevaFuXd7p9hhHPdqRol/Cv9O5c+G888JA78poUdPEhd41BiD5rKwWwGbl/Gys1cA/3b0Z0A7oYWbNK+G8ki8mTYI2beD66xlZ4yS2/XEW7Qed9VvhX2zVqt8L/2LFC72L5LOkLQB3/1c6L+zuC4kGk919mZnNAhoCM9N5XckBv/zCjNNvZveRd/Md29CDZ3mu6KTw2ZrUT6OnfiXfldUFdJW732Fm/yWaAZTI3S+prCDMrCmwN/BBKZ91BboCNNZjmvLWWyw9ozMtvvmcQXTmSu7kJ7bYoFPpn5Pku7JmAc2Kfk9MZwBmVhd4Brg0yjq6DncvIMxCok2bNutVRJInli4NSzMOGMCSGjtyMq8xlg4pHbrJJuuOAYCe+hWBsruAXoxeFkX5gH5jZqdVxsXNbBNC4V/o7iMq45ySg0aNgm7d8PnzGbLZZfRc9m+KqFPmIdWrhyV9Gzf+vaBPXOi9Tx8NAIuk8hzAtSQkgytjW4VYmE40BJi1sTOKJEd9/31I3jZsGEsaNuekmu/y5rJ25R5Wu3bpaR1U4Iusq6wxgD8DxwINzey+hI82p3JSQRwEnA1MN7OPom3XufuoSji3ZDP3sCLXRRfB4sVw4420feQ6Pl9RK+khZuGwJk10dy+SqrJaAAsI/f8nAJMSti8DLtvYC7v7eMDK3VHyy4IF0L07PP88tGnDS5e9Ro+BLZlbxowdFfoiG6asMYCpwFQze9zdV1VhTJKP3GHIELjiClixAu66i8cb9KTLhTUoKkp+WJMmMGdOlUUpklNSGQNoa2Y3A02i/Q1wd98pnYFJHpk9G7p0gbFjoX37kLxtl124rillFv6aySOycVKpAIYQunwmUaHHbETKsWYN3Hcf9OrFKq/BjVsN5I43O7Nlu/CA+g8/JD9U3T4iGy+VCuAnd3857ZFIXhl5+wwa3ng+e6/8gJEcRzce5OtfdwDKLvhB3T4ilSWVCuANM7sTGAGsKN7o7pPTFpXkrpUrmfr3vhz1zC38RD3+xuM8yZmkOh9A3T4ilSeVCmD/6HebhG0OHFH54UhOmzABOnWi1ccfU8jfuZR+fE+DlA9Xt49I5Sq3AnD3w6siEMlhRUVw441wzz3wxz9yAi/wIn+p0CnU7SNS+VJpAWBmxwEtgE2Lt7l773QFJTlk3Djo3Bn+7//C6ly33860VvVgbuqnULePSHqUuyKYmT0InAFcTOioPY0wJVQkuZ9+CgX+4aEB+dp1Y2n6yoPYFvXKTcNcpw7Urx+e7m3SpPS0DiKy8VJZLPVAdz8HWBytEXAA0Ci9YUlWGzkSWrSAwYOZeewVNFo8jT/dejhzo7t+L5HTtXjJ3iZNYNgwWL48pAFauzZ0+6jwF0mPVLqAfol+F5nZ9sAPwI7pC0my1qJFzDmxJ03fe4Lp7ElnRvDhqLblHtaokfr3ReKQSgtgpJltAdwJTAbmAE+mMyjJMu7wxBP8unNztn9vODfyL/ZlEh9SfuEPWplLJC6pzAL6d/TyGTMbCWzq7j+lNyzJGvPnw4UXwsiRTGV/OjGEmbSo0Cm0MpdIPMqtAMzsnFK24e5D0xOSZIW1a2HQILjySlavWE2vTf7DXasuYS3VK3QazfARiU8qYwD7JZINbLAAABHBSURBVLzeFOhA6ApSBZCvvviCb07ownazxvE6R9CFQXxJ6rkBq1UL9Yce7BKJVypdQBcnvjezesBjaYtIMk5hYVhOcf7c1VxGP3pzA3+gJp0ZxBDOJ9U0DvXrw733qsAXyRQpPQhWQhGwa2UHIpmpsBC6doWdiqbzLufTlgk8zwl05wEW0DClc+hOXyQzpTIG8CIh9w+EWUPNgafSGZRkjisvWcFVRbdyHbeymC05nf/xNKeRyl3/sGEq9EUyWSotgLsSXq8G5rr7/DTFIxmguMtnu7nvM4bzacFMHuMsLqUfP1I/pXPUr6/CXyTTlbUo/C7Atu7+Zonth5hZLXf/v7RHJ1Wue3cYOuBnenMDl9KPr2nIsbzEyxyb8jlq1w59/SKS2cp6EKwfYQH4kn6JPpMcU1gInw14nWnsxeXcw4N0owUzUir8E9M5KHePSHYoqwuoqbtPK7nR3SeaWdO0RSTxWLKEtedfyWsM5jN25VDe5G0OLfMQzeoRyW5ltQA2LeOzP1R2IFL1Cgth663hRHueBVs2528rHqYvV9OKqUkLf7MwuOseErap8BfJXmVVABPMrEvJjWZ2PmGBeMli3bvDZWd9x/0/nMnznMR3bMP+fMC19OXXJPW7GXTrpkJfJFeU1QV0KfCsmXXk9wK/DVATODndgUnlKyyEnj3hhx+cjhQyi57UZTm9uIU7uIrVbJL0WM3lF8k9SSsAd/8WONDMDgf2jDa/5O5jqyQyqTS/F/zQiK8YSjeO5WXe5QDOZwif0CzpsfXrh64eEck9qaSCeAN4owpikTQofpL3l6K1dGMgd3AV1VjLJdxLf3qUmbzNTNM5RXLZhqSCkCzSsyc0LPqMwXTmUN5mDEfSlQLmlLOmj/r7RXJfKgvCSJYpnt1Tw1bT6Yc7mEor9mI65/EQR/Fq0sLfouwOTZrAY4/BAw9UYdAiUuXUAsgx3bvDgAHQkqmMphP7MpkRnEwP+vMNf0x63IUXqsAXyTextgDM7Bgz+9TMvjCza+KMJRcUFsLDA37l31zPRNrQkK85heGcwoikhX/9+mFevwp/kfwTWwvAzKoD/YE/AfMJzx284O4z44op2w3r/i6TOZ9mfMIjnMvl/IfFbLXefprZIyIQbwugLfCFu89295WEheZPjDGe7LV8OW+07MlLSw+mNkUczSucxyOlFv6a2SMixeKsABoC8xLez4+2rcPMuprZRDObuGjRoioLLtMVD/T+ycbw5WZ7cfj0++hPD/bkY17l6KTHaWaPiBSLswIobUURX2+De4G7t3H3Ng0aNKiCsDJTcYFvFn4uOmsxd/zQiTEcxQpqcTBvcwn/ZTmblXq8+vpFpKQ4ZwHNBxolvN8BWBBTLBmtsBDOOw9WrQrvT2YE/elBAxZxK9fSmxtZkSR3n/r7RSSZOFsAE4BdzWxHM6sJnAm8EGM8Gaf4rv+ss0Lhvy3f8DSnMoJT+Ibt2I8J9OLWpIW/+vtFpCyxVQDuvhq4CBgNzAKecvcZccWTCUp285x1VsjfA845PMpMmnM8I7mWW2nLh3zE3mWeT/39IlKWWB8Ec/dRwKg4Y4hLYoK2sjRmLgO5gGMYzXgOojOD+ZQ9yj2/HuwSkfIoFUSaFRZC06bhjr5atdLu7ktnrKUH9zODFhzEO/Tgfg7lrXILfw32ikiqlAoiDZLd3ft6c5xKtxufMoTzOZh3eIWjuYCBfEWTUvfVsowisqHUAqhkxTN2yuvaKU0NVnENtzGVVjRnJufwKH/m5XUK/5o1f1+SUcsyisjGUAugkvXq9ft0zYpozRQeohN78xFPcyoXcT/fse06+9StCw8+qAJfRCqHWgCVqLAQ5s6t2DG1+JVbuZYJ7Md2fMNfeYbTeXqdwr+4X3/ZMhX+IlJ51AKoJMUrb1XEQYxnCOezO5/xEOdxpd3Nj76l1t8VkSqhFkAl6dULiopS27cuy7ifixjPIdSuvpLXr36VTv4QP6zdEneYM0eFv4iknyqASvLVV8k/K+7CcQd/ZTTLGu9JD3sAevak0ZLpdOj7p6oLVEQkoi6gStK4cen9/02ahDt6fvgBzr0chg6FZs3gnXfggAOqOkwRkd+oBbCRih/0mjv39zV1i9WuDX1ucRg+HJo3h8cfh+uvhylTVPiLSOzUAtgIxQO/xX3/7qEScA93/ndfsZBTRvSAZ5+FffeFV1+FVq3iDVpEJKIKYCOUNvDrDk0aO3NuegQuvxx+/RVuvz28rqE/bhHJHCqRNkJpA79N+ZKCr7pCp9fg0ENh0CDYbbeqD05EpBwaA9gIjRv//roaa7iY+/iYPWlnH8CAAfDGGyr8RSRjqQLYCH36hIHeZszkbQ7hPnoyvlp7Xus3IyTjr6Y/XhHJXCqhNkLH01fx7rG3MIW92Y3P6Fl/GN8/+hInX9Ko/INFRGKmMYANNWkSdOpEq2nT4IwzqHXffdy7zTZxRyUikjK1ACrql1/g6quhbVtYtAieew6efBJU+ItIllEFUBFvvRXm8d9xB5+3P5+WNWZS7eQTado0PBMgIpJNVAGkYulS6N4d2reHNWt47drXaf1BAdPnbYF7eAq4a1dVAiKSXVQBlGfUKGjRAgYODA9zTZtG58ePWO8BsKKi8GCYiEi2UAWQzPffh5XbjzsONt8c3n0X7r4b6tRJmvmzrIygIiKZRhVASe7wv/+F5G3/+x/cdBNMngz77//bLokPgCVKtl1EJBOpAki0YAGcdBKceWZI8Tl5Mtx8M9Sqtc5uxQ+AJapdO2wXEckWqgAg3PUPHhzu+seMgbvugvfeg732KnX3jh2hoCBk/DQLvwsKtIqXiGQXPQg2ezZ06QJjx8Jhh4XkbbvsUu5hHTuqwBeR7Ja/LYA1a+Cee2DPPWHixDDL5/XXUyr8RURyQX5WAB9/DAceGKZ1dugAM2aEifxlJG8rXvmrWjX04JeI5IT8qgBWroR//Qv22Sd0/Tz+OLzwAuywwzq7lSzsu3cP9cPcuejBLxHJGebucceQsjZt2vjEiRM37OAJE6BTp3D3//e/Q79+0KDBeruVXOYRfl/msaTfFnwXEclgZjbJ3duU3B5LC8DM7jSzT8xsmpk9a2ZbpO1iRUVwxRXQrh0sXgwvvhhK+VIKf0i+zGNp9OCXiGSzuLqAxgB7untL4DPg2rRcZdw4aNkyPMHbpUvo6z/++DIPqUihrge/RCSbxVIBuPur7r46evs+sENZ+1fYTz/BBRfA4YeH92+8AQ8+CPXqlXtoskLdbN33evBLRLJdJgwCdwJeTvahmXU1s4lmNnHRokXln+3FF8MDXYMHh66fadPC/P4UJXvKt1s3PfglIrklbQ+CmdlrwHalfNTL3Z+P9ukFrAaSzqdx9wKgAMIgcNILLloEPXvCE0+EJ3ifew7226/CcRcX6r16he6gxo1DpaDCXkRyTdoqAHc/sqzPzexc4Higg2/MVCT3UOhfcknI29+7d1ixq2bNDT6lnvIVkXwQSyoIMzsGuBpo7+5F5e2f1Pz5cOGFMHJkyNY5ZEjI3S8iIuWKawzgfmAzYIyZfWRmD1bo6LVrQ+qG5s1DDp977oF33lHhLyJSAbG0ANx9wxPufPFFmNI5blxI41BQADvtVHnBiYjkiezKBvrtt2GAt1atMMunU6f152eKiEhKsqsCmD8fTjwRHngAtt8+7mhERLJaVuUCMrNFwNwUd98a+D6N4WSifPvO+r65Td+38jRx9/Xy32RVBVARZjaxtORHuSzfvrO+b27T902/THgSWEREYqAKQEQkT+VyBVAQdwAxyLfvrO+b2/R90yxnxwBERKRsudwCEBGRMqgCEBHJUzldAVTp0pMxMrNjzOxTM/vCzK6JO550MrNGZvaGmc0ysxlm1jPumKqCmVU3sylmNjLuWKqCmW1hZsOj/7+zzOyAuGNKJzO7LPr3/LGZPWFmm1bFdXO6AqCqlp6MkZlVB/oDfwaaA38zs+bxRpVWq4F/unszoB3QI8e/b7GewKy4g6hC9wKvuPseQCty+LubWUPgEqCNu+8JVAfOrIpr53QFkPalJzNDW+ALd5/t7iuBJ4ETY44pbdx9obtPjl4vIxQMDeONKr3MbAfgOGBw3LFUBTPbHDgUGALg7ivdfUm8UaVdDeAPZlYDqA0sqIqL5nQFUEKZS09msYbAvIT388nxArGYmTUF9gY+iDeStOsHXAWsjTuQKrITsAh4OOr2GmxmdeIOKl3c/WvgLuArYCHwk7u/WhXXzvoKwMxei/rNSv6cmLBPuUtPZrHS0qHm/NxeM6sLPANc6u5L444nXczseOA7d58UdyxVqAawDzDA3fcGfgZydmzLzLYktNp3BLYH6pjZWVVx7ezKBlqKKlt6MnPNBxolvN+BKmo+xsXMNiEU/oXuPiLueNLsIOAEMzsW2BTY3MyGuXuVFBAxmQ/Md/filt1wcrgCAI4EvnT3RQBmNgI4EBiW7gtnfQugLAlLT56wUUtPZrYJwK5mtqOZ1SQMHr0Qc0xpY2ZG6Bue5e7/iTuedHP3a919B3dvSvi7HZvjhT/u/g0wz8x2jzZ1AGbGGFK6fQW0M7Pa0b/vDlTRoHfWtwDKcT9Qi7D0JMD77t4t3pAql7uvNrOLgNGE2QMPufuMmMNKp4OAs4HpZvZRtO06dx8VY0xS+S4GCqObmtnAeTHHkzbu/oGZDQcmE7qqp1BFaSGUCkJEJE/ldBeQiIgkpwpARCRPqQIQEclTqgBERPKUKgARkTylCkAylpltZ2ZPmtn/mdlMMxtlZrtV8jVaRw9ZFb8/oTijqpndbGZXbOT5m5rZ3zc2zhLnfLcyzyf5SxWAZKTogZhngXHuvrO7NweuA7at5Eu1Bn6rANz9BXfvW4nnbwpUSgUQZX7F3Q+sjPOJqAKQTHU4sMrdHyze4O4fufvbZnZYYl58M7vfzP4Rvb7RzCZE+aAKoooEMxtnZreb2Ydm9pmZHRI9ZNQbOMPMPjKzM8zsH2Z2f8lgzGxnM3vFzCaZ2dtmtke0/bToWlPN7K1Svkdf4JDo/JdFef3vjGKcZmYXROexaPvHZjbdzM6Ith8WrX/wODA92rY8Ia6rov2nmlnfaFtrM3vffl8HY8to+yVRS2qamT25EX83kiNy/UlgyV57AhuSAO1+d+8NYGaPEfJAvRh9VsPd20ZdPje5+5FmdiMhD/tF0TH/SHLeAqCbu39uZvsDDwBHADcCR7v711b6gkPXAFe4+/HR+bsSsj3uZ2a1gHfM7FVC8rPWhNz3WwMTEiqUtoR1Lb5MPLGZ/Rk4Cdjf3YvMbKvoo6HAxe7+ppn1Bm4CLo1i2dHdVySJVfKMKgDJNYeb2VWEnOpbATP4vQIoThw3idA1k5Io8+iBwNNRgwJCihGAd4BHzOyphPOX5SigpZmdGr2vB+wKHAw84e5rgG/N7E1gP2Ap8GHJwj9yJPBwcZ4rd//RzOoBW7j7m9E+jwJPR6+nEdIrPAc8l0KskuNUAUimmgGcmuSz1azbfbkpgIVl9B4g3NHPM7Obiz+LrIh+r6Fi//arAUvcvXXJD9y9W9QiOA74yMxau/sPZZzLCHfno9fZmDAQXYqfyzhXRXK5HEdYaOUE4AYza5GwYJLkIY0BSKYaC9Qysy7FG8xsPzNrD8wFmptZreiOt0O0S3Fh/310156sAkm0DNisrB2i9Qa+NLPTojjMzFpFr3d29w/c/Ubge9ZNzV3a+UcDF1pIaY2Z7WZhsZO3CGMR1c2sAaGg/rCc2F8FOplZ7ehcW7n7T8BiMzsk2uds4E0zqwY0cvc3CIvLbAHULef8kuPUApCM5O5uZicD/aJpmb8CcwgLwMyLulymAZ8Tsifi7kvMbBBhsHQOIVV2ed4ArrGQWfS2MvbrCAwws+uBTQhLb04F7jSzXQl3469H2xJNA1ab2VTgEcJat02BydEA9SJCP/6zwAHR8Q5c5e7fFA82l8bdXzGz1sBEM1sJjCLMlDoXeDCqGIozaVYHhkUVpgH35MEyi1IOZQMVEclT6gISEclTqgBERPKUKgARkTylCkBEJE+pAhARyVOqAERE8pQqABGRPPX/0i+Yq5KQuRoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "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": [
    "# Q-Q plot quantile quantile plot\n",
    "for i in dist_names:\n",
    "    fitbest=getattr(scipy.stats,i)\n",
    "    fig = sm.qqplot(data, fitbest, fit=True, line = \"45\")\n",
    "    plt.title(\"Q-Q plot, Dist: \"+i)\n",
    "    plt.ylabel(\"Cuantiles muestrales\")\n",
    "    plt.xlabel(\"Cuantiles teoricos\")\n",
    "    \n",
    "    plt.savefig(\"qqplot_dist_\"+i+\".png\",dpi=300)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Christian\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:11: RuntimeWarning: divide by zero encountered in double_scalars\n",
      "  # This is added back by InteractiveShellApp.init_path()\n"
     ]
    }
   ],
   "source": [
    "# RP con gumbel-r\n",
    "\n",
    "fitbest=getattr(scipy.stats,\"gumbel_r\") # obtenienen atributos\n",
    "\n",
    "P = fitbest.fit(data)\n",
    "\n",
    "yrp= np.linspace(0,1000,100001)\n",
    "rpd=[]\n",
    "\n",
    "for i in yrp:\n",
    "    rpd.append(fitbest.ppf([1-(1/i)], *P)[0] )\n",
    "    \n",
    "results_rpd=pd.DataFrame()\n",
    "results_rpd[\"RP\"] = yrp\n",
    "results_rpd[\"PP\"] = np.array(rpd)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "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>RP</th>\n",
       "      <th>PP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.01</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.02</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.03</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.04</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99996</th>\n",
       "      <td>999.96</td>\n",
       "      <td>105.567007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99997</th>\n",
       "      <td>999.97</td>\n",
       "      <td>105.567113</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99998</th>\n",
       "      <td>999.98</td>\n",
       "      <td>105.567219</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99999</th>\n",
       "      <td>999.99</td>\n",
       "      <td>105.567325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100000</th>\n",
       "      <td>1000.00</td>\n",
       "      <td>105.567431</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>100001 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             RP          PP\n",
       "0          0.00         NaN\n",
       "1          0.01         NaN\n",
       "2          0.02         NaN\n",
       "3          0.03         NaN\n",
       "4          0.04         NaN\n",
       "...         ...         ...\n",
       "99996    999.96  105.567007\n",
       "99997    999.97  105.567113\n",
       "99998    999.98  105.567219\n",
       "99999    999.99  105.567325\n",
       "100000  1000.00  105.567431\n",
       "\n",
       "[100001 rows x 2 columns]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_rpd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "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>RP</th>\n",
       "      <th>PP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>5000</th>\n",
       "      <td>50.0</td>\n",
       "      <td>73.71962</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        RP        PP\n",
       "5000  50.0  73.71962"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_rpd[results_rpd[\"RP\"]==50]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "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>RP</th>\n",
       "      <th>PP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>10000</th>\n",
       "      <td>100.0</td>\n",
       "      <td>81.118667</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          RP         PP\n",
       "10000  100.0  81.118667"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_rpd[results_rpd[\"RP\"]==100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>RP</th>\n",
       "      <th>PP</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20000</th>\n",
       "      <td>200.0</td>\n",
       "      <td>88.490716</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          RP         PP\n",
       "20000  200.0  88.490716"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results_rpd[results_rpd[\"RP\"]==200]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# realizar periodo de retorno,50,100,200 con estacion huanuco"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}