{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Asiakaspalvelupisteen jonon muodostukseen vaikuttaa kaksi tekijää:\n",
    "\n",
    "● Asiakkaiden saapuminen palvelupisteeseen.\n",
    "\n",
    "● Palvelun kesto.\n",
    "\n",
    "Asiakkaiden saapumista voidaan monissa tapauksissa mallintaa onnistuneesti eksponentiaalisella jakaumalla. Tällöin tarvitaan tieto siitä, kuinka paljon asiakkaita saapuu keskimäärin tarkasteltavassa aikavälissä.\n",
    "\n",
    "Palvelun kestoa voidaan monissa tapauksissa mallintaa onnistuneesti normaalijakaumalla. Tällöin tarvitaan palveluajan keskiarvo ja keskihajonta."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "KESKIARVO_ASIAKAS = 5 #asiakkaiden väli minuutteina\n",
    "KESKIARVO_PALVELU = 2 #minuuttia\n",
    "KESKIHAJONTA_PALVELU = 0.5\n",
    "ASIAKKAITA = 1000"
   ]
  },
  {
   "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>seuraava_asiakas</th>\n",
       "      <th>saapumis_aika</th>\n",
       "      <th>palvelun_kesto</th>\n",
       "      <th>palvelun_aloitus</th>\n",
       "      <th>palvelun_lopetus</th>\n",
       "      <th>jonotus</th>\n",
       "      <th>kokonais_aika</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>4.559935</td>\n",
       "      <td>4.559935</td>\n",
       "      <td>1.970475</td>\n",
       "      <td>4.559935</td>\n",
       "      <td>6.530409</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.970475</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.170075</td>\n",
       "      <td>11.730009</td>\n",
       "      <td>1.750567</td>\n",
       "      <td>11.730009</td>\n",
       "      <td>13.480576</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.750567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2.125404</td>\n",
       "      <td>13.855414</td>\n",
       "      <td>2.863559</td>\n",
       "      <td>13.855414</td>\n",
       "      <td>16.718973</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.863559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14.641087</td>\n",
       "      <td>28.496501</td>\n",
       "      <td>2.058293</td>\n",
       "      <td>28.496501</td>\n",
       "      <td>30.554794</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.058293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>3.523031</td>\n",
       "      <td>32.019532</td>\n",
       "      <td>2.096044</td>\n",
       "      <td>32.019532</td>\n",
       "      <td>34.115576</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.096044</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.716269</td>\n",
       "      <td>32.735801</td>\n",
       "      <td>1.767038</td>\n",
       "      <td>34.115576</td>\n",
       "      <td>35.882613</td>\n",
       "      <td>1.379775</td>\n",
       "      <td>3.146812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5.303635</td>\n",
       "      <td>38.039436</td>\n",
       "      <td>1.753736</td>\n",
       "      <td>38.039436</td>\n",
       "      <td>39.793172</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.753736</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3.239577</td>\n",
       "      <td>41.279013</td>\n",
       "      <td>2.786673</td>\n",
       "      <td>41.279013</td>\n",
       "      <td>44.065686</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.786673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>12.890109</td>\n",
       "      <td>54.169123</td>\n",
       "      <td>2.685727</td>\n",
       "      <td>54.169123</td>\n",
       "      <td>56.854850</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.685727</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>3.937489</td>\n",
       "      <td>58.106611</td>\n",
       "      <td>2.637670</td>\n",
       "      <td>58.106611</td>\n",
       "      <td>60.744281</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.637670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>6.887558</td>\n",
       "      <td>64.994169</td>\n",
       "      <td>0.923588</td>\n",
       "      <td>64.994169</td>\n",
       "      <td>65.917757</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.923588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>16.207476</td>\n",
       "      <td>81.201645</td>\n",
       "      <td>2.562661</td>\n",
       "      <td>81.201645</td>\n",
       "      <td>83.764306</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.562661</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>12.078720</td>\n",
       "      <td>93.280365</td>\n",
       "      <td>2.098805</td>\n",
       "      <td>93.280365</td>\n",
       "      <td>95.379171</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.098805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>8.308787</td>\n",
       "      <td>101.589152</td>\n",
       "      <td>2.684418</td>\n",
       "      <td>101.589152</td>\n",
       "      <td>104.273571</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.684418</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.101702</td>\n",
       "      <td>101.690854</td>\n",
       "      <td>1.657744</td>\n",
       "      <td>104.273571</td>\n",
       "      <td>105.931314</td>\n",
       "      <td>2.582716</td>\n",
       "      <td>4.240460</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>3.926541</td>\n",
       "      <td>105.617396</td>\n",
       "      <td>1.943939</td>\n",
       "      <td>105.931314</td>\n",
       "      <td>107.875253</td>\n",
       "      <td>0.313919</td>\n",
       "      <td>2.257858</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>9.675890</td>\n",
       "      <td>115.293285</td>\n",
       "      <td>1.975953</td>\n",
       "      <td>115.293285</td>\n",
       "      <td>117.269238</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.975953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>3.250767</td>\n",
       "      <td>118.544052</td>\n",
       "      <td>1.941022</td>\n",
       "      <td>118.544052</td>\n",
       "      <td>120.485074</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.941022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>8.665241</td>\n",
       "      <td>127.209293</td>\n",
       "      <td>1.322388</td>\n",
       "      <td>127.209293</td>\n",
       "      <td>128.531681</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.322388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>5.277812</td>\n",
       "      <td>132.487105</td>\n",
       "      <td>2.391272</td>\n",
       "      <td>132.487105</td>\n",
       "      <td>134.878377</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.391272</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>5.039594</td>\n",
       "      <td>137.526699</td>\n",
       "      <td>2.022646</td>\n",
       "      <td>137.526699</td>\n",
       "      <td>139.549345</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.022646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>3.944090</td>\n",
       "      <td>141.470789</td>\n",
       "      <td>1.160414</td>\n",
       "      <td>141.470789</td>\n",
       "      <td>142.631204</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.160414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>4.229980</td>\n",
       "      <td>145.700769</td>\n",
       "      <td>1.353824</td>\n",
       "      <td>145.700769</td>\n",
       "      <td>147.054593</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.353824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.925151</td>\n",
       "      <td>146.625920</td>\n",
       "      <td>2.340526</td>\n",
       "      <td>147.054593</td>\n",
       "      <td>149.395120</td>\n",
       "      <td>0.428673</td>\n",
       "      <td>2.769200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2.306118</td>\n",
       "      <td>148.932038</td>\n",
       "      <td>1.134182</td>\n",
       "      <td>149.395120</td>\n",
       "      <td>150.529301</td>\n",
       "      <td>0.463082</td>\n",
       "      <td>1.597263</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.299353</td>\n",
       "      <td>149.231391</td>\n",
       "      <td>2.667097</td>\n",
       "      <td>150.529301</td>\n",
       "      <td>153.196398</td>\n",
       "      <td>1.297910</td>\n",
       "      <td>3.965007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.225853</td>\n",
       "      <td>149.457244</td>\n",
       "      <td>2.107281</td>\n",
       "      <td>153.196398</td>\n",
       "      <td>155.303679</td>\n",
       "      <td>3.739154</td>\n",
       "      <td>5.846434</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.847106</td>\n",
       "      <td>150.304351</td>\n",
       "      <td>2.081570</td>\n",
       "      <td>155.303679</td>\n",
       "      <td>157.385249</td>\n",
       "      <td>4.999328</td>\n",
       "      <td>7.080898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>10.233806</td>\n",
       "      <td>160.538156</td>\n",
       "      <td>1.934800</td>\n",
       "      <td>160.538156</td>\n",
       "      <td>162.472957</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.934800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.616380</td>\n",
       "      <td>161.154536</td>\n",
       "      <td>2.640670</td>\n",
       "      <td>162.472957</td>\n",
       "      <td>165.113627</td>\n",
       "      <td>1.318420</td>\n",
       "      <td>3.959090</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>7.102974</td>\n",
       "      <td>4964.656230</td>\n",
       "      <td>2.428474</td>\n",
       "      <td>4964.656230</td>\n",
       "      <td>4967.084704</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.428474</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>971</th>\n",
       "      <td>0.138565</td>\n",
       "      <td>4964.794795</td>\n",
       "      <td>2.744121</td>\n",
       "      <td>4967.084704</td>\n",
       "      <td>4969.828825</td>\n",
       "      <td>2.289909</td>\n",
       "      <td>5.034030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>972</th>\n",
       "      <td>3.011328</td>\n",
       "      <td>4967.806123</td>\n",
       "      <td>2.080804</td>\n",
       "      <td>4969.828825</td>\n",
       "      <td>4971.909629</td>\n",
       "      <td>2.022702</td>\n",
       "      <td>4.103506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>973</th>\n",
       "      <td>16.542482</td>\n",
       "      <td>4984.348605</td>\n",
       "      <td>1.713767</td>\n",
       "      <td>4984.348605</td>\n",
       "      <td>4986.062372</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.713767</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>974</th>\n",
       "      <td>3.610126</td>\n",
       "      <td>4987.958731</td>\n",
       "      <td>1.303616</td>\n",
       "      <td>4987.958731</td>\n",
       "      <td>4989.262347</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.303616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>975</th>\n",
       "      <td>0.523492</td>\n",
       "      <td>4988.482223</td>\n",
       "      <td>1.887123</td>\n",
       "      <td>4989.262347</td>\n",
       "      <td>4991.149470</td>\n",
       "      <td>0.780124</td>\n",
       "      <td>2.667247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>976</th>\n",
       "      <td>5.928719</td>\n",
       "      <td>4994.410942</td>\n",
       "      <td>1.555162</td>\n",
       "      <td>4994.410942</td>\n",
       "      <td>4995.966104</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.555162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>977</th>\n",
       "      <td>17.111571</td>\n",
       "      <td>5011.522513</td>\n",
       "      <td>1.243976</td>\n",
       "      <td>5011.522513</td>\n",
       "      <td>5012.766489</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.243976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>978</th>\n",
       "      <td>7.167799</td>\n",
       "      <td>5018.690312</td>\n",
       "      <td>1.888549</td>\n",
       "      <td>5018.690312</td>\n",
       "      <td>5020.578861</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.888549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>979</th>\n",
       "      <td>3.154027</td>\n",
       "      <td>5021.844339</td>\n",
       "      <td>1.980424</td>\n",
       "      <td>5021.844339</td>\n",
       "      <td>5023.824763</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.980424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>980</th>\n",
       "      <td>10.400865</td>\n",
       "      <td>5032.245204</td>\n",
       "      <td>2.148101</td>\n",
       "      <td>5032.245204</td>\n",
       "      <td>5034.393305</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.148101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>981</th>\n",
       "      <td>0.204477</td>\n",
       "      <td>5032.449681</td>\n",
       "      <td>2.214375</td>\n",
       "      <td>5034.393305</td>\n",
       "      <td>5036.607680</td>\n",
       "      <td>1.943624</td>\n",
       "      <td>4.157999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>982</th>\n",
       "      <td>1.020533</td>\n",
       "      <td>5033.470214</td>\n",
       "      <td>1.290481</td>\n",
       "      <td>5036.607680</td>\n",
       "      <td>5037.898161</td>\n",
       "      <td>3.137466</td>\n",
       "      <td>4.427948</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>983</th>\n",
       "      <td>1.700163</td>\n",
       "      <td>5035.170377</td>\n",
       "      <td>2.548396</td>\n",
       "      <td>5037.898161</td>\n",
       "      <td>5040.446557</td>\n",
       "      <td>2.727784</td>\n",
       "      <td>5.276180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>984</th>\n",
       "      <td>4.861728</td>\n",
       "      <td>5040.032105</td>\n",
       "      <td>1.653602</td>\n",
       "      <td>5040.446557</td>\n",
       "      <td>5042.100159</td>\n",
       "      <td>0.414452</td>\n",
       "      <td>2.068054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>985</th>\n",
       "      <td>4.912337</td>\n",
       "      <td>5044.944442</td>\n",
       "      <td>1.842041</td>\n",
       "      <td>5044.944442</td>\n",
       "      <td>5046.786483</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.842041</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>986</th>\n",
       "      <td>6.195677</td>\n",
       "      <td>5051.140119</td>\n",
       "      <td>2.012578</td>\n",
       "      <td>5051.140119</td>\n",
       "      <td>5053.152697</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.012578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>987</th>\n",
       "      <td>4.246305</td>\n",
       "      <td>5055.386424</td>\n",
       "      <td>3.641099</td>\n",
       "      <td>5055.386424</td>\n",
       "      <td>5059.027523</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.641099</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>988</th>\n",
       "      <td>0.351196</td>\n",
       "      <td>5055.737619</td>\n",
       "      <td>2.405110</td>\n",
       "      <td>5059.027523</td>\n",
       "      <td>5061.432633</td>\n",
       "      <td>3.289904</td>\n",
       "      <td>5.695014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>989</th>\n",
       "      <td>6.389141</td>\n",
       "      <td>5062.126760</td>\n",
       "      <td>1.465794</td>\n",
       "      <td>5062.126760</td>\n",
       "      <td>5063.592554</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.465794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>990</th>\n",
       "      <td>0.332100</td>\n",
       "      <td>5062.458860</td>\n",
       "      <td>1.876872</td>\n",
       "      <td>5063.592554</td>\n",
       "      <td>5065.469426</td>\n",
       "      <td>1.133695</td>\n",
       "      <td>3.010566</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>991</th>\n",
       "      <td>4.218615</td>\n",
       "      <td>5066.677475</td>\n",
       "      <td>2.249977</td>\n",
       "      <td>5066.677475</td>\n",
       "      <td>5068.927451</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.249977</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>992</th>\n",
       "      <td>44.402375</td>\n",
       "      <td>5111.079850</td>\n",
       "      <td>1.959461</td>\n",
       "      <td>5111.079850</td>\n",
       "      <td>5113.039311</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.959461</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>993</th>\n",
       "      <td>11.676260</td>\n",
       "      <td>5122.756110</td>\n",
       "      <td>1.253784</td>\n",
       "      <td>5122.756110</td>\n",
       "      <td>5124.009894</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.253784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>994</th>\n",
       "      <td>2.951483</td>\n",
       "      <td>5125.707593</td>\n",
       "      <td>2.392283</td>\n",
       "      <td>5125.707593</td>\n",
       "      <td>5128.099877</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.392283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>1.418355</td>\n",
       "      <td>5127.125948</td>\n",
       "      <td>2.397739</td>\n",
       "      <td>5128.099877</td>\n",
       "      <td>5130.497616</td>\n",
       "      <td>0.973929</td>\n",
       "      <td>3.371668</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>1.772244</td>\n",
       "      <td>5128.898192</td>\n",
       "      <td>1.610387</td>\n",
       "      <td>5130.497616</td>\n",
       "      <td>5132.108002</td>\n",
       "      <td>1.599424</td>\n",
       "      <td>3.209810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>0.498313</td>\n",
       "      <td>5129.396505</td>\n",
       "      <td>2.140898</td>\n",
       "      <td>5132.108002</td>\n",
       "      <td>5134.248901</td>\n",
       "      <td>2.711497</td>\n",
       "      <td>4.852395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>6.645040</td>\n",
       "      <td>5136.041545</td>\n",
       "      <td>2.460836</td>\n",
       "      <td>5136.041545</td>\n",
       "      <td>5138.502382</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.460836</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>10.574862</td>\n",
       "      <td>5146.616407</td>\n",
       "      <td>2.721448</td>\n",
       "      <td>5146.616407</td>\n",
       "      <td>5149.337855</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.721448</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     seuraava_asiakas  saapumis_aika  palvelun_kesto  palvelun_aloitus  \\\n",
       "0            4.559935       4.559935        1.970475          4.559935   \n",
       "1            7.170075      11.730009        1.750567         11.730009   \n",
       "2            2.125404      13.855414        2.863559         13.855414   \n",
       "3           14.641087      28.496501        2.058293         28.496501   \n",
       "4            3.523031      32.019532        2.096044         32.019532   \n",
       "5            0.716269      32.735801        1.767038         34.115576   \n",
       "6            5.303635      38.039436        1.753736         38.039436   \n",
       "7            3.239577      41.279013        2.786673         41.279013   \n",
       "8           12.890109      54.169123        2.685727         54.169123   \n",
       "9            3.937489      58.106611        2.637670         58.106611   \n",
       "10           6.887558      64.994169        0.923588         64.994169   \n",
       "11          16.207476      81.201645        2.562661         81.201645   \n",
       "12          12.078720      93.280365        2.098805         93.280365   \n",
       "13           8.308787     101.589152        2.684418        101.589152   \n",
       "14           0.101702     101.690854        1.657744        104.273571   \n",
       "15           3.926541     105.617396        1.943939        105.931314   \n",
       "16           9.675890     115.293285        1.975953        115.293285   \n",
       "17           3.250767     118.544052        1.941022        118.544052   \n",
       "18           8.665241     127.209293        1.322388        127.209293   \n",
       "19           5.277812     132.487105        2.391272        132.487105   \n",
       "20           5.039594     137.526699        2.022646        137.526699   \n",
       "21           3.944090     141.470789        1.160414        141.470789   \n",
       "22           4.229980     145.700769        1.353824        145.700769   \n",
       "23           0.925151     146.625920        2.340526        147.054593   \n",
       "24           2.306118     148.932038        1.134182        149.395120   \n",
       "25           0.299353     149.231391        2.667097        150.529301   \n",
       "26           0.225853     149.457244        2.107281        153.196398   \n",
       "27           0.847106     150.304351        2.081570        155.303679   \n",
       "28          10.233806     160.538156        1.934800        160.538156   \n",
       "29           0.616380     161.154536        2.640670        162.472957   \n",
       "..                ...            ...             ...               ...   \n",
       "970          7.102974    4964.656230        2.428474       4964.656230   \n",
       "971          0.138565    4964.794795        2.744121       4967.084704   \n",
       "972          3.011328    4967.806123        2.080804       4969.828825   \n",
       "973         16.542482    4984.348605        1.713767       4984.348605   \n",
       "974          3.610126    4987.958731        1.303616       4987.958731   \n",
       "975          0.523492    4988.482223        1.887123       4989.262347   \n",
       "976          5.928719    4994.410942        1.555162       4994.410942   \n",
       "977         17.111571    5011.522513        1.243976       5011.522513   \n",
       "978          7.167799    5018.690312        1.888549       5018.690312   \n",
       "979          3.154027    5021.844339        1.980424       5021.844339   \n",
       "980         10.400865    5032.245204        2.148101       5032.245204   \n",
       "981          0.204477    5032.449681        2.214375       5034.393305   \n",
       "982          1.020533    5033.470214        1.290481       5036.607680   \n",
       "983          1.700163    5035.170377        2.548396       5037.898161   \n",
       "984          4.861728    5040.032105        1.653602       5040.446557   \n",
       "985          4.912337    5044.944442        1.842041       5044.944442   \n",
       "986          6.195677    5051.140119        2.012578       5051.140119   \n",
       "987          4.246305    5055.386424        3.641099       5055.386424   \n",
       "988          0.351196    5055.737619        2.405110       5059.027523   \n",
       "989          6.389141    5062.126760        1.465794       5062.126760   \n",
       "990          0.332100    5062.458860        1.876872       5063.592554   \n",
       "991          4.218615    5066.677475        2.249977       5066.677475   \n",
       "992         44.402375    5111.079850        1.959461       5111.079850   \n",
       "993         11.676260    5122.756110        1.253784       5122.756110   \n",
       "994          2.951483    5125.707593        2.392283       5125.707593   \n",
       "995          1.418355    5127.125948        2.397739       5128.099877   \n",
       "996          1.772244    5128.898192        1.610387       5130.497616   \n",
       "997          0.498313    5129.396505        2.140898       5132.108002   \n",
       "998          6.645040    5136.041545        2.460836       5136.041545   \n",
       "999         10.574862    5146.616407        2.721448       5146.616407   \n",
       "\n",
       "     palvelun_lopetus   jonotus  kokonais_aika  \n",
       "0            6.530409  0.000000       1.970475  \n",
       "1           13.480576  0.000000       1.750567  \n",
       "2           16.718973  0.000000       2.863559  \n",
       "3           30.554794  0.000000       2.058293  \n",
       "4           34.115576  0.000000       2.096044  \n",
       "5           35.882613  1.379775       3.146812  \n",
       "6           39.793172  0.000000       1.753736  \n",
       "7           44.065686  0.000000       2.786673  \n",
       "8           56.854850  0.000000       2.685727  \n",
       "9           60.744281  0.000000       2.637670  \n",
       "10          65.917757  0.000000       0.923588  \n",
       "11          83.764306  0.000000       2.562661  \n",
       "12          95.379171  0.000000       2.098805  \n",
       "13         104.273571  0.000000       2.684418  \n",
       "14         105.931314  2.582716       4.240460  \n",
       "15         107.875253  0.313919       2.257858  \n",
       "16         117.269238  0.000000       1.975953  \n",
       "17         120.485074  0.000000       1.941022  \n",
       "18         128.531681  0.000000       1.322388  \n",
       "19         134.878377  0.000000       2.391272  \n",
       "20         139.549345  0.000000       2.022646  \n",
       "21         142.631204  0.000000       1.160414  \n",
       "22         147.054593  0.000000       1.353824  \n",
       "23         149.395120  0.428673       2.769200  \n",
       "24         150.529301  0.463082       1.597263  \n",
       "25         153.196398  1.297910       3.965007  \n",
       "26         155.303679  3.739154       5.846434  \n",
       "27         157.385249  4.999328       7.080898  \n",
       "28         162.472957  0.000000       1.934800  \n",
       "29         165.113627  1.318420       3.959090  \n",
       "..                ...       ...            ...  \n",
       "970       4967.084704  0.000000       2.428474  \n",
       "971       4969.828825  2.289909       5.034030  \n",
       "972       4971.909629  2.022702       4.103506  \n",
       "973       4986.062372  0.000000       1.713767  \n",
       "974       4989.262347  0.000000       1.303616  \n",
       "975       4991.149470  0.780124       2.667247  \n",
       "976       4995.966104  0.000000       1.555162  \n",
       "977       5012.766489  0.000000       1.243976  \n",
       "978       5020.578861  0.000000       1.888549  \n",
       "979       5023.824763  0.000000       1.980424  \n",
       "980       5034.393305  0.000000       2.148101  \n",
       "981       5036.607680  1.943624       4.157999  \n",
       "982       5037.898161  3.137466       4.427948  \n",
       "983       5040.446557  2.727784       5.276180  \n",
       "984       5042.100159  0.414452       2.068054  \n",
       "985       5046.786483  0.000000       1.842041  \n",
       "986       5053.152697  0.000000       2.012578  \n",
       "987       5059.027523  0.000000       3.641099  \n",
       "988       5061.432633  3.289904       5.695014  \n",
       "989       5063.592554  0.000000       1.465794  \n",
       "990       5065.469426  1.133695       3.010566  \n",
       "991       5068.927451  0.000000       2.249977  \n",
       "992       5113.039311  0.000000       1.959461  \n",
       "993       5124.009894  0.000000       1.253784  \n",
       "994       5128.099877  0.000000       2.392283  \n",
       "995       5130.497616  0.973929       3.371668  \n",
       "996       5132.108002  1.599424       3.209810  \n",
       "997       5134.248901  2.711497       4.852395  \n",
       "998       5138.502382  0.000000       2.460836  \n",
       "999       5149.337855  0.000000       2.721448  \n",
       "\n",
       "[1000 rows x 7 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulointi = pd.DataFrame(index = range(ASIAKKAITA))\n",
    "simulointi['seuraava_asiakas'] = np.random.exponential(KESKIARVO_ASIAKAS, size = ASIAKKAITA)\n",
    "simulointi['saapumis_aika'] = simulointi['seuraava_asiakas'].cumsum()\n",
    "simulointi['palvelun_kesto'] = np.random.normal(loc = KESKIARVO_PALVELU, scale = KESKIHAJONTA_PALVELU,\n",
    "                                               size = ASIAKKAITA)\n",
    "simulointi['palvelun_aloitus'] = simulointi['saapumis_aika']\n",
    "simulointi['palvelun_lopetus'] = simulointi['saapumis_aika'] + simulointi['palvelun_kesto']\n",
    "\n",
    "for i in range(1, len(simulointi)):\n",
    "    if simulointi.loc[i, 'saapumis_aika'] < simulointi.loc[i-1, 'palvelun_lopetus']:\n",
    "        simulointi.loc[i, 'palvelun_aloitus'] = simulointi.loc[i-1,'palvelun_lopetus']\n",
    "    simulointi['palvelun_lopetus'] = simulointi['palvelun_aloitus'] + simulointi['palvelun_kesto']\n",
    "    \n",
    "simulointi['jonotus'] = simulointi['palvelun_aloitus'] - simulointi['saapumis_aika']\n",
    "simulointi['kokonais_aika'] = simulointi['jonotus'] + simulointi['palvelun_kesto']\n",
    "simulointi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>jonotus</th>\n",
       "      <th>kokonais_aika</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.719808</td>\n",
       "      <td>2.700317</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.245056</td>\n",
       "      <td>1.332166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.668122</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.858800</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.314290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.122697</td>\n",
       "      <td>3.137720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>10.021099</td>\n",
       "      <td>11.976497</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           jonotus  kokonais_aika\n",
       "count  1000.000000    1000.000000\n",
       "mean      0.719808       2.700317\n",
       "std       1.245056       1.332166\n",
       "min       0.000000       0.668122\n",
       "25%       0.000000       1.858800\n",
       "50%       0.000000       2.314290\n",
       "75%       1.122697       3.137720\n",
       "max      10.021099      11.976497"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulointi[['jonotus', 'kokonais_aika']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1b4a3ecca58>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Tästä näkee nousevana trendinä, jos jono kasvaa ajan kuluessa\n",
    "simulointi[['jonotus', 'kokonais_aika']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<matplotlib.axes._subplots.AxesSubplot object at 0x000001B4A57CD6A0>,\n",
       "       <matplotlib.axes._subplots.AxesSubplot object at 0x000001B4A3F45A90>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYgAAAD8CAYAAABthzNFAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADl0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uIDMuMC4zLCBodHRwOi8vbWF0cGxvdGxpYi5vcmcvnQurowAAH5NJREFUeJzt3XuQFdW59/HvwzA6IhcVEJEBB85BUEAuGUQgB9GJMd4AqyTHFOFq5CTHeHmTqGhSJ8Yy5yXRY8BKSoMXRIJHBEGJaIwSCN6iAhKMDChRLlsIDkQBRYTB5/2je3hHaGZ69uw9vffM71M1Nd1rr+5+luB+WL261zJ3R0RE5HDNkg5ARERykxKEiIhEUoIQEZFIShAiIhJJCUJERCIpQYiISCQlCBERiaQEISIikZQgREQkUvOkA6iPdu3aeUlJSdJhiIjklZUrV+5w9/a11cvrBFFSUsKKFSuSDkNEJK+Y2aY49XSLSUREIilBiIhIJCUIERGJlNdjECKSnAMHDpBKpdi3b1/SochRFBUVUVxcTGFhYVrHK0GISFpSqRStWrWipKQEM0s6HDmMu7Nz505SqRRdu3ZN6xy6xSQiadm3bx9t27ZVcshRZkbbtm3r1cNTghCRtCk55Lb6/vkoQYiISCSNQYhIRpRMWZzR822ceklGzyd1px6EiOStjRs30rt371h1H374Yb7//e9nNZ4hQ4Zk7Fzf+c53WLt2LQAtW7bM2HnrQj0IEZEMeeWVVzJ2rgceeCBj50qXehAi0ii899579O/fnxdffJGJEyfSp08f+vfvz9KlS4+ou3jxYgYPHsyOHTvYtGkTZWVlnHXWWZSVlbF582YAJkyYwHXXXceQIUPo1q0b8+fPB+CTTz6hrKyMAQMG0KdPH5566qlD5636l/62bdsYNmwY/fr1o3fv3rz44otHjft73/sepaWl9OrVi5/+9KeHyocPH37EXHM7duxg8ODBLF68uMY4MkU9CBHJe+vXr+fKK69k5syZLFmyBIC33nqLdevW8fWvf5133nnnUN2FCxdy991388wzz3DiiScyceJExo0bx/jx43nooYe47rrrePLJJ4Hgi/6ll15i3bp1jBgxgiuuuIKioiIWLlxI69at2bFjB+eccw4jRoz40hNDjz76KBdeeCE//vGPOXjwIHv37j1q7D//+c856aSTOHjwIGVlZaxZs4azzjrriHrbt29nxIgR3HHHHVxwwQVUVlbWGkd9KUGISF6rqKhg5MiRPPHEE/Tq1Yuf/exnXHvttQD07NmT00477VCCWLp0KStWrOCPf/wjrVu3BuDVV19lwYIFAIwdO5abbrrp0LlHjRpFs2bNOPPMM9m+fTsQvIB26623snz5cpo1a8YHH3zA9u3bOeWUUw4dN3DgQCZNmsSBAwcYNWoU/fr1O2r8jz/+ODNmzKCyspJt27axdu3aIxLEgQMHKCsr4ze/+Q3nnntu7DjqS7eYRCSvtWnThs6dO/Pyyy8DwRfn0XTr1o09e/Z8qUdxuOr/Aj/22GMPbVedd86cOVRUVLBy5UpWr15Nhw4djngZbdiwYSxfvpxOnToxduxYHnnkkchrvf/++9x1110sWbKENWvWcMkll0S+2Na8eXO+8pWv8Nxzzx0qixNHfakHISIZkdRjqccccwxPPvkkF154IS1btmTYsGHMmTOH888/n3feeYfNmzfTo0cPVq1axWmnncZdd93F5Zdfzrx58+jVqxdDhgzhscceY+zYscyZM4evfvWrNV5v165dnHzyyRQWFrJ06VI2bTpyaYVNmzbRqVMnrr76aj799FNWrVrFuHHjjqi3e/dujj/+eNq0acP27dt59tlnGT58+BH1zIyHHnqI0aNHM3XqVKZMmRIrjvpSghCRvHf88cfz9NNPc8EFF/CTn/yENWvW0KdPH5o3b87DDz/8pZ5Ajx49mDNnDqNHj+b3v/8999xzD5MmTeLOO++kffv2zJw5s8ZrjRkzhssuu4zS0lL69etHz549j6izbNky7rzzTgoLC2nZsuVRexB9+/alf//+9OrVi27dujF06NCjXregoIDHHnuMyy67jNatW8eKo76spu5YristLXWtKCeSjPLycs4444ykw5BaRP05mdlKdy+t7ViNQYiISKSs3mIysxOAB4DegAOTgPXAXKAE2Ah8090/smBkaDpwMbAXmODuq7IZn4hIQxk0aBCff/75l8pmz55Nnz59Eoqodtkeg5gO/MHdrzCzY4AWwK3AEnefamZTgCnAzcBFQPfwZxBwb/hbRHKUu2tG15hee+21Br9mfYcQsnaLycxaA8OABwHcfb+7fwyMBGaF1WYBo8LtkcAjHvgLcIKZdcxWfCJSP0VFRezcubPeX0KSHVULBhUVFaV9jmz2ILoBFcBMM+sLrASuBzq4+zYAd99mZieH9TsBW6odnwrLtmUxRhFJU3FxMalUioqKiqRDkaOoWnI0XbEShJn1dve/pXHuAcC17v6amU0nuJ101MtElB3xTxMzmwxMBujSpUsdQxKRTCksLEx7KUvJD3FvMd1nZq+b2X+GA89xpICUu1fdeJtPkDC2V906Cn9/WK1+52rHFwNbDz+pu89w91J3L23fvn3MUEREpK5iJQh3/yowhuALfIWZPWpmF9RyzD+ALWbWIywqA9YCi4DxYdl4oGoKwkXAOAucA+yquhUlIiINL/YYhLu/a2Y/AVYA9wD9w0dTb3X3BUc57FpgTvgE03vARIKk9LiZXQVsBkaHdZ8heMR1A8FjrhPTaI+IiGRI3DGIswi+sC8Bngcuc/dVZnYq8CoQmSDcfTUQ9bZeWURdB66JGbeIiGRZ3B7Er4H7CXoLn1UVuvvWsFchIiKNTNwEcTHwmbsfBDCzZkCRu+9199lZi05ERBIT9ymmF4Djqu23CMtERKSRipsgitz9k6qdcLtFdkISEZFcEDdBfGpmA6p2zOwrwGc11BcRkTwXdwziBmCemVW9uNYR+PfshCQiIrkgVoJw9zfMrCfQg2BKjHXufiCrkYmISKLqMlnfQII1HJoTvCSHu0evoyciInkv7otys4F/AVYDB8NiB5Qg0lAyZXEi101qUXkRyU9xexClwJmuid9FRJqMuE8x/Q04JZuBiIhIbonbg2gHrDWz14FDi6q6+4isRCUiIomLmyBuy2YQIiKSe+I+5vpnMzsN6O7uL5hZC6Agu6GJiEiSYo1BmNnVBCvC/TYs6gQ8ma2gREQkeXEHqa8BhgK7IVg8CDg5W0GJiEjy4iaIz919f9WOmTUneA+iVmZWYGZvmtnT4X5XM3vNzN41s7nhanOY2bHh/obw85K6NUVERDIpboL4s5ndChwXrkU9D/h9zGOvB8qr7f8C+JW7dwc+Aq4Ky68CPnL3fwV+FdYTEZGExE0QU4AK4C3gPwjWj651JTkzKyZYpvSBcN+A8wnGMwBmAaPC7ZHhPuHnZWF9ERFJQNynmL4gWHL0/jqefxpwE9Aq3G8LfOzuleF+imDAm/D3lvB6lWa2K6y/o47XFBGRDIg7F9P7RIw5uHu3Go65FPjQ3Vea2fCq4oiqHuOz6uedDEwG6NKlS82Bi4hI2uoyF1OVImA0cFItxwwFRpjZxeExrQl6FCeYWfOwF1EMVK0xkQI6A6lwELwN8M/DT+ruM4AZAKWlpZobSkQkS2KNQbj7zmo/H7j7NIKxhJqOucXdi929BLgS+JO7jwGWAleE1cYDT4Xbi8J9ws//pMkBRUSSE/cW04Bqu80IehStjlK9NjcDj5nZHcCbwINh+YPAbDPbQNBzuDLN84uISAbEvcX0P9W2K4GNwDfjXsTdlwHLwu33gLMj6uwjuHUlIiI5IO5TTOdlOxAREcktcW8x/aCmz9397syEIyIiuaIuTzENJBhIBrgMWE743oKIiDQ+dVkwaIC77wEws9uAee7+nWwFJiIiyYo71UYXYH+1/f1AScajERGRnBG3BzEbeN3MFhK83Xw58EjWohIRkcTFfYrp52b2LPBvYdFEd38ze2GJiEjS4t5iAmgB7Hb36QTTYXTNUkwiIpID4i45+lOCN6BvCYsKgd9lKygREUle3DGIy4H+wCoAd99qZulOtSEJKZmyOLFrb5x6SWLXFpH0xL3FtD+cOM8BzOz47IUkIiK5IG6CeNzMfkswVffVwAvUffEgERHJI3GfYrorXIt6N9AD+C93fz6rkYmISKJqTRBmVgA85+5fA5QURESaiFpvMbn7QWCvmbVpgHhERCRHxH2KaR/wlpk9D3xaVeju12UlKhERSVzcBLE4/InNzDoTTMdxCvAFMMPdp5vZScBcgrmcNgLfdPePzMyA6cDFwF5ggruvqss1RUQkc2pMEGbWxd03u/usNM5dCfzQ3VeF70ysDHsgE4Al7j7VzKYAUwhewrsI6B7+DALuDX+LiEgCahuDeLJqw8yeqMuJ3X1bVQ8gnCa8HOgEjASqEs4sYFS4PRJ4xAN/IXiktmNdrikiIplTW4Kwatvd0r2ImZUQvIn9GtDB3bdBkESAk8NqnfjyAkSpsOzwc002sxVmtqKioiLdkEREpBa1JQg/ynZsZtYSeAK4wd1311S1lusHBe4z3L3U3Uvbt2+fTkgiIhJDbYPUfc1sN8GX93HhNuG+u3vrmg42s0KC5DDH3ReExdvNrKO7bwtvIX0YlqeAztUOLwa21qEtIiKSQTX2INy9wN1bu3srd28eblft15YcDHgQKHf3u6t9tAgYH26PB56qVj7OAucAu6puRYmISMOL+5hrOoYCYwnen1gdlt0KTCWY2+kqYDMwOvzsGYJHXDcQPOY6MYuxiYhILbKWINz9JaLHFQDKIuo7cE224hERkbqpy4pyIiLShChBiIhIJCUIERGJpAQhIiKRlCBERCRSNh9zFTmkZEqdJgPOmI1TL0nkuiKNgXoQIiISSQlCREQiKUGIiEgkJQgREYmkBCEiIpGUIEREJJIShIiIRNJ7ENKo6f0LkfSpByEiIpGabA8iqX9Ziojki5zqQZjZN8xsvZltMLMpSccjItKU5UyCMLMC4DfARcCZwLfM7MxkoxIRabpy6RbT2cAGd38PwMweA0YCaxONSiQNSd7C1AC5ZEouJYhOwJZq+ylg0OGVzGwyMDnc/cTM1qd5vS7A5jSPzTVqS25KpC32i6yctrH8uTSWdkD92nJanEq5lCAsosyPKHCfAcyo98XMKty9tL7nyQVqS25SW3JPY2kHNExbcmYMgqDH0LnafjGwNYvX+ziL525oaktuUltyT2NpBzRAW3IpQbwBdDezrmZ2DHAlsCiL19uVxXM3NLUlN6ktuaextAMaoC05c4vJ3SvN7PvAc0AB8JC7v53FS9b7NlUOUVtyk9qSexpLO6AB2mLuR9zmFxERyalbTCIikkOUIEREJJIShIiIRFKCEBGRSEoQIiISSQlCREQiKUGIiEgkJQgREYmkBCEiIpGUIEREJJIShIiIRFKCEBGRSEoQIiISSQlCREQi5cx6EOlo166dl5SUJB2GiEheWbly5Q53b19bvbxOECUlJaxYsSLpMERE8oqZbYpTT7eYREQkkhKEiIhEUoIQEZFIeT0GUS+3tUnw2ruSu7ZII3LgwAFSqRT79u1LOpScVFRURHFxMYWFhWkd33QThIjkvVQqRatWrSgpKcHMkg4np7g7O3fuJJVK0bVr17TOoVtMIpK39u3bR9u2bZUcIpgZbdu2rVfvSglCRPKaksPR1fe/jRKEiEg9DRkyJKPnmzZtGnv37s3oOdOhMQgRaTwy/fBJzAdKXnnllYxedtq0aXz729+mRYsWGT1vXakHISJSTy1btsTdufHGG+nduzd9+vRh7ty5ACxbtozhw4dzxRVX0LNnT8aMGYO7A7BkyRL69+9Pnz59mDRpEp9//jn33HMPW7du5bzzzuO88847dP4q8+fPZ8KECQDMmzeP3r1707dvX4YNG5bxdqkHISKSAQsWLGD16tX89a9/ZceOHQwcOPDQl/abb77J22+/zamnnsrQoUN5+eWXKS0tZcKECSxZsoTTTz+dcePGce+993LDDTdw9913s3TpUtq1a1fjNW+//Xaee+45OnXqxMcff5zxNqkHISKSAS+99BLf+ta3KCgooEOHDpx77rm88cYbAJx99tkUFxfTrFkz+vXrx8aNG1m/fj1du3bl9NNPB2D8+PEsX768TtccOnQoEyZM4P777+fgwYMZb5MShIhIBlTdNopy7LHHHtouKCigsrKyxvqHq/40UvXHVu+77z7uuOMOtmzZQr9+/di5c2cdo66ZEoSISAYMGzaMuXPncvDgQSoqKli+fDlnn332Uev37NmTjRs3smHDBgBmz57NueeeC0CrVq3Ys2fPobodOnSgvLycL774goULFx4q//vf/86gQYO4/fbbadeuHVu2bMlomzQGISJST2bG5Zdfzquvvkrfvn0xM375y19yyimnsG7dushjioqKmDlzJqNHj6ayspKBAwfy3e9+F4DJkydz0UUX0bFjR5YuXcrUqVO59NJL6dy5M7179+aTTz4B4MYbb+Tdd9/F3SkrK6Nv376ZbVddujm5prS01NNeD0JzMYnkvfLycs4444xEY9i5cycDBgxg06ZYSyw0uKj/Rma20t1LaztWt5hERNK0detWBg8ezI9+9KOkQ8kK3WISEUnTqaeeyjvvvJN0GFmjHoSIiETKaoIwsxPMbL6ZrTOzcjMbbGYnmdnzZvZu+PvEsK6Z2T1mtsHM1pjZgGzGJiKNQz6Po2Zbff/bZLsHMR34g7v3BPoC5cAUYIm7dweWhPsAFwHdw5/JwL1Zjk1E8lxRURE7d+5UkohQtR5EUVFR2ufI2hiEmbUGhgETANx9P7DfzEYCw8Nqs4BlwM3ASOARD/6k/xL2Pjq6+7ZsxSgi+a24uJhUKkVFRUXSoeSkqhXl0pXNQepuQAUw08z6AiuB64EOVV/67r7NzE4O63cCqr/lkQrLvpQgzGwyQQ+DLl26ZDF8Ecl1hYWFaa+WJrWLdYvJzHqnce7mwADgXnfvD3zK/7+dFHmZiLIj+o3uPsPdS929tH379mmEJSIiccQdg7jPzF43s/80sxNiHpMCUu7+Wrg/nyBhbDezjgDh7w+r1e9c7fhiYGvMa4mISIbFShDu/lVgDMEX+Aoze9TMLqjlmH8AW8ysR1hUBqwFFgHjw7LxwFPh9iJgXPg00znALo0/iIgkJ/YYhLu/a2Y/AVYA9wD9LZhi8FZ3X3CUw64F5pjZMcB7wESCpPS4mV0FbAZGh3WfAS4GNgB7w7oiIpKQWAnCzM4i+MK+BHgeuMzdV5nZqcCrQGSCcPfVQNR8H2URdR24JmbcIiKSZXF7EL8G7ifoLXxWVejuW8NehYiINDJxE8TFwGfufhDAzJoBRe6+191nZy06ERFJTNynmF4Ajqu23yIsExGRRipugihy90+qdsLtFtkJSUREckHcBPFp9cnzzOwrwGc11BcRkTwXdwziBmCemVW9uNYR+PfshCQiIrkgVoJw9zfMrCfQg2BKjHXufiCrkYmISKLqMlnfQKAkPKa/meHuj2QlKhERSVzcF+VmA/8CrAYOhsUOKEGIiDRScXsQpcCZrlU5RESajLhPMf0NOCWbgYiISG6J24NoB6w1s9eBz6sK3X1EVqISEZHExU0Qt2UzCBERyT1xH3P9s5mdBnR39xfMrAVQkN3QREQkSXGXHL2aYEW434ZFnYAnsxWUiIgkL+4g9TXAUGA3BIsHASfHOdDMCszsTTN7Otzvamavmdm7ZjY3XEwIMzs23N8Qfl5S18aIiEjmxE0Qn7v7/qodM2tO8B5EHNcD5dX2fwH8yt27Ax8BV4XlVwEfufu/Ar8K64mISELiJog/m9mtwHHhWtTzgN/XdpCZFROsQvdAuG/A+QS3qwBmAaPC7ZHhPuHnZWF9ERFJQNwEMQWoAN4C/oNg/eg4K8lNA24Cvgj32wIfu3tluJ8iGM8g/L0FIPx8V1hfREQSEPcppi8Ilhy9P+6JzexS4EN3X2lmw6uKo04f47Pq550MTAbo0qVL3HBERKSO4s7F9D4RX9bu3q2Gw4YCI8zsYqAIaE3QozjBzJqHvYRioGoK8RTQGUiFYxxtgH9GXHMGMAOgtLRUU3+IiGRJXeZiqlIEjAZOqukAd78FuAUg7EH8yN3HmNk84ArgMWA88FR4yKJw/9Xw8z9p7icRkeTEGoNw953Vfj5w92kEg83puBn4gZltIBhjeDAsfxBoG5b/gGDcQ0REEhL3FtOAarvNCHoUreJexN2XAcvC7feAsyPq7CPomYiISA6Ie4vpf6ptVwIbgW9mPBoREckZcZ9iOi/bgYiISG6Je4vpBzV97u53ZyYcERHJFXV5imkgwZNGAJcBywlfbBMRkcanLgsGDXD3PQBmdhswz92/k63AREQkWXGn2ugC7K+2vx8oyXg0IiKSM+L2IGYDr5vZQoI3qi8HHslaVCIikri4TzH93MyeBf4tLJro7m9mLywREUla3FtMAC2A3e4+nWC+pK5ZiklERHJA3CVHf0owRcYtYVEh8LtsBSUiIsmL24O4HBgBfArg7lupw1QbIiKSf+ImiP3hzKoOYGbHZy8kERHJBXETxONm9luCtRyuBl6gDosHiYhI/on7FNNd4VrUu4EewH+5+/NZjUxERBJVa4IwswLgOXf/GqCkICLSRNR6i8ndDwJ7zaxNA8QjIiI5Iu6b1PuAt8zsecInmQDc/bqjHWBmnQnetj4F+AKY4e7TzewkYC7BVB0bgW+6+0dmZsB04GJgLzDB3VfVuUUiIpIRcRPE4vCnLiqBH7r7KjNrBawME8wEYIm7TzWzKQRLi94MXAR0D38GAfeGv0VEJAE1Jggz6+Lum919Vl1P7O7bgG3h9h4zKwc6ASOB4WG1WQRLkd4clj8SPk77FzM7wcw6hucREZEGVtsYxJNVG2b2RLoXMbMSoD/wGtCh6ks//H1yWK0TX15fIhWWiYhIAmpLEFZtu1s6FzCzlsATwA3uvjvmtap4xPkmm9kKM1tRUVGRTkgiIhJDbQnCj7Idi5kVEiSHOe6+ICzebmYdw887Ah+G5Smgc7XDi4GtRwTkPsPdS929tH379nUNSUREYqotQfQ1s91mtgc4K9zebWZ7zKym3gDhU0kPAuWHrVm9CBgfbo8HnqpWPs4C5wC7NP4gIpKcGgep3b2gHuceCowleDx2dVh2KzCVYOqOq4DNwOjws2cIHnHdQPCY68R6XFtEROop7mOudebuLxE9rgBQFlHfgWuyFY+IiNRNXRYMEhGRJkQJQkREImXtFpPU4LaEprW6bVcy1xWRvKQehIiIRFKCEBGRSEoQIiISSQlCREQiKUGIiEgkJQgREYmkBCEiIpGUIEREJJIShIiIRNKb1E1JUm9wg97iFslD6kGIiEgkJQgREYmkBCEiIpFyKkGY2TfMbL2ZbTCzKUnHIyLSlOXMILWZFQC/AS4AUsAbZrbI3dcmG5lkhKY4F8k7udSDOBvY4O7vuft+4DFgZMIxiYg0WTnTgwA6AVuq7aeAQQnFIo1Fko/2JkW9JsmQXEoQFlHmR1QymwxMDnc/MbP1aV6vC7A5zWNzjdqSm5Jpy8+i/leqt8by59JY2gH1a8tpcSqZ+xHfwYkws8HAbe5+Ybh/C4C7/98sXa/C3dtn49wNTW3JTWpL7mks7YCGaUsujUG8AXQ3s65mdgxwJbAoi9f7OIvnbmhqS25SW3JPY2kHNEBbcuYWk7tXmtn3geeAAuAhd387i5dsTDdq1ZbcpLbknsbSDmiAtuRMggBw92eAZxrocjMa6DoNQW3JTWpL7mks7YAGaEvOjEGIiEhuyaUxCBERySFNMkE0lik9zKyzmS01s3Ize9vMrk86pvowswIze9PMnk46lvowsxPMbL6ZrQv/bAYnHVO6zOz/hH+3/mZm/2tmRUnHFJeZPWRmH5rZ36qVnWRmz5vZu+HvE5OMMa6jtOXO8O/YGjNbaGYnZPq6TS5BVJvS4yLgTOBbZnZmslGlrRL4obufAZwDXJPHbQG4HihPOogMmA78wd17An3J0zaZWSfgOqDU3XsTPDxyZbJR1cnDwDcOK5sCLHH37sCScD8fPMyRbXke6O3uZwHvALdk+qJNLkHQiKb0cPdt7r4q3N5D8EXUKdmo0mNmxcAlwANJx1IfZtYaGAY8CODu+909nx+tbA4cZ2bNgRbA1oTjic3dlwP/PKx4JDAr3J4FjGrQoNIU1RZ3/6O7V4a7fwGKM33dppggoqb0yMsv1erMrAToD7yWbCRpmwbcBHyRdCD11A2oAGaGt8seMLPjkw4qHe7+AXAXwdu624Bd7v7HZKOqtw7uvg2Cf2ABJyccT6ZMAp7N9EmbYoKINaVHPjGzlsATwA3uvjvpeOrKzC4FPnT3lUnHkgHNgQHAve7eH/iU/LmN8SXh/fmRQFfgVOB4M/t2slHJ4czsxwS3m+dk+txNMUGkgM7V9ovJo27z4cyskCA5zHH3BUnHk6ahwAgz20hwy+98M/tdsiGlLQWk3L2qJzefIGHko68B77t7hbsfABYAQxKOqb62m1lHgPD3hwnHUy9mNh64FBjjWXhnoSkmiIae0iNrzMwI7nWXu/vdSceTLne/xd2L3b2E4M/jT+6el/9Sdfd/AFvMrEdYVAbk65omm4FzzKxF+HetjDwdcK9mETA+3B4PPJVgLPViZt8AbgZGuPvebFyjySWIcFCnakqPcuDxLE/pkU1DgbEE/+JeHf5cnHRQwrXAHDNbA/QD/jvheNIS9oLmA6uAtwi+L/LmTWQz+1/gVaCHmaXM7CpgKnCBmb1LsDjZ1CRjjOsobfk10Ap4Pvx//76MX1dvUouISJQm14MQEZF4lCBERCSSEoSIiERSghARkUhKECIiEkkJQkREIilBiIhIJCUIERGJ9P8AaAPbbTfDvOMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "simulointi[['kokonais_aika', 'jonotus']].plot.hist(subplots=True, sharex=True, sharey=True)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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