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Shinichi-Nakagawa/mantle_career_r.ipynb

Created November 17, 2019 06:04
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ミッキー・マントル(MLB)のOPS推移とパフォーマンス軌跡
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mantle_career_r.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"─ \u001b[1mAttaching packages\u001b[22m ──────────────────── tidyverse 1.2.1 ─\n",
"\u001b[32m✔\u001b[39m \u001b[34mggplot2\u001b[39m 3.2.1 \u001b[32m✔\u001b[39m \u001b[34mpurrr \u001b[39m 0.3.3\n",
"\u001b[32m✔\u001b[39m \u001b[34mtibble \u001b[39m 2.1.3 \u001b[32m✔\u001b[39m \u001b[34mdplyr \u001b[39m 0.8.3\n",
"\u001b[32m✔\u001b[39m \u001b[34mtidyr \u001b[39m 1.0.0 \u001b[32m✔\u001b[39m \u001b[34mstringr\u001b[39m 1.4.0\n",
"\u001b[32m✔\u001b[39m \u001b[34mreadr \u001b[39m 1.3.1 \u001b[32m✔\u001b[39m \u001b[34mforcats\u001b[39m 0.4.0\n",
"─ \u001b[1mConflicts\u001b[22m ───────────────────── tidyverse_conflicts() ─\n",
"\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mfilter()\u001b[39m masks \u001b[34mstats\u001b[39m::filter()\n",
"\u001b[31m✖\u001b[39m \u001b[34mdplyr\u001b[39m::\u001b[32mlag()\u001b[39m masks \u001b[34mstats\u001b[39m::lag()\n"
]
}
],
"source": [
"library(tidyverse)\n",
"library(Lahman)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"Master %>%\n",
" filter(nameFirst == \"Mickey\", nameLast == \"Mantle\") %>%\n",
" pull(playerID) -> mantle_id"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"'mantlmi01'"
],
"text/latex": [
"'mantlmi01'"
],
"text/markdown": [
"'mantlmi01'"
],
"text/plain": [
"[1] \"mantlmi01\""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"mantle_id"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"batting <- Batting %>%\n",
" replace_na(list(SF = 0, HBP = 0))"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.frame: 105861 × 22</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>playerID</th><th scope=col>yearID</th><th scope=col>stint</th><th scope=col>teamID</th><th scope=col>lgID</th><th scope=col>G</th><th scope=col>AB</th><th scope=col>R</th><th scope=col>H</th><th scope=col>X2B</th><th scope=col>⋯</th><th scope=col>RBI</th><th scope=col>SB</th><th scope=col>CS</th><th scope=col>BB</th><th scope=col>SO</th><th scope=col>IBB</th><th scope=col>HBP</th><th scope=col>SH</th><th scope=col>SF</th><th scope=col>GIDP</th></tr>\n",
"\t<tr><th scope=col>&lt;chr&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;fct&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>⋯</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;int&gt;</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>abercda01</td><td>1871</td><td>1</td><td>TRO</td><td>NA</td><td> 1</td><td> 4</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>addybo01 </td><td>1871</td><td>1</td><td>RC1</td><td>NA</td><td>25</td><td>118</td><td>30</td><td>32</td><td> 6</td><td>⋯</td><td>13</td><td> 8</td><td>1</td><td> 4</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>allisar01</td><td>1871</td><td>1</td><td>CL1</td><td>NA</td><td>29</td><td>137</td><td>28</td><td>40</td><td> 4</td><td>⋯</td><td>19</td><td> 3</td><td>1</td><td> 2</td><td>5</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>1</td></tr>\n",
"\t<tr><td>allisdo01</td><td>1871</td><td>1</td><td>WS3</td><td>NA</td><td>27</td><td>133</td><td>28</td><td>44</td><td>10</td><td>⋯</td><td>27</td><td> 1</td><td>1</td><td> 0</td><td>2</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>ansonca01</td><td>1871</td><td>1</td><td>RC1</td><td>NA</td><td>25</td><td>120</td><td>29</td><td>39</td><td>11</td><td>⋯</td><td>16</td><td> 6</td><td>2</td><td> 2</td><td>1</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>armstbo01</td><td>1871</td><td>1</td><td>FW1</td><td>NA</td><td>12</td><td> 49</td><td> 9</td><td>11</td><td> 2</td><td>⋯</td><td> 5</td><td> 0</td><td>1</td><td> 0</td><td>1</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>barkeal01</td><td>1871</td><td>1</td><td>RC1</td><td>NA</td><td> 1</td><td> 4</td><td> 0</td><td> 1</td><td> 0</td><td>⋯</td><td> 2</td><td> 0</td><td>0</td><td> 1</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>barnero01</td><td>1871</td><td>1</td><td>BS1</td><td>NA</td><td>31</td><td>157</td><td>66</td><td>63</td><td>10</td><td>⋯</td><td>34</td><td>11</td><td>6</td><td>13</td><td>1</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>1</td></tr>\n",
"\t<tr><td>barrebi01</td><td>1871</td><td>1</td><td>FW1</td><td>NA</td><td> 1</td><td> 5</td><td> 1</td><td> 1</td><td> 1</td><td>⋯</td><td> 1</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>barrofr01</td><td>1871</td><td>1</td><td>BS1</td><td>NA</td><td>18</td><td> 86</td><td>13</td><td>13</td><td> 2</td><td>⋯</td><td>11</td><td> 1</td><td>0</td><td> 0</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>bassjo01 </td><td>1871</td><td>1</td><td>CL1</td><td>NA</td><td>22</td><td> 89</td><td>18</td><td>27</td><td> 1</td><td>⋯</td><td>18</td><td> 0</td><td>1</td><td> 3</td><td>4</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>battijo01</td><td>1871</td><td>1</td><td>CL1</td><td>NA</td><td> 1</td><td> 3</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 1</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>bealsto01</td><td>1871</td><td>1</td><td>WS3</td><td>NA</td><td>10</td><td> 36</td><td> 6</td><td> 7</td><td> 0</td><td>⋯</td><td> 1</td><td> 2</td><td>0</td><td> 2</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>2</td></tr>\n",
"\t<tr><td>beaveed01</td><td>1871</td><td>1</td><td>TRO</td><td>NA</td><td> 3</td><td> 15</td><td> 7</td><td> 6</td><td> 0</td><td>⋯</td><td> 5</td><td> 2</td><td>0</td><td> 0</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>bechtge01</td><td>1871</td><td>1</td><td>PH1</td><td>NA</td><td>20</td><td> 94</td><td>24</td><td>33</td><td> 9</td><td>⋯</td><td>21</td><td> 4</td><td>0</td><td> 2</td><td>2</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>1</td></tr>\n",
"\t<tr><td>bellast01</td><td>1871</td><td>1</td><td>TRO</td><td>NA</td><td>29</td><td>128</td><td>26</td><td>32</td><td> 3</td><td>⋯</td><td>23</td><td> 4</td><td>4</td><td> 9</td><td>2</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>2</td></tr>\n",
"\t<tr><td>berkena01</td><td>1871</td><td>1</td><td>PH1</td><td>NA</td><td> 1</td><td> 4</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>3</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>berryto01</td><td>1871</td><td>1</td><td>PH1</td><td>NA</td><td> 1</td><td> 4</td><td> 0</td><td> 1</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>berthha01</td><td>1871</td><td>1</td><td>WS3</td><td>NA</td><td>17</td><td> 73</td><td>17</td><td>17</td><td> 1</td><td>⋯</td><td> 8</td><td> 3</td><td>1</td><td> 4</td><td>2</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>biermch01</td><td>1871</td><td>1</td><td>FW1</td><td>NA</td><td> 1</td><td> 2</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 1</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>birdge01 </td><td>1871</td><td>1</td><td>RC1</td><td>NA</td><td>25</td><td>106</td><td>19</td><td>28</td><td> 2</td><td>⋯</td><td>13</td><td> 1</td><td>0</td><td> 3</td><td>2</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>3</td></tr>\n",
"\t<tr><td>birdsda01</td><td>1871</td><td>1</td><td>BS1</td><td>NA</td><td>29</td><td>152</td><td>51</td><td>46</td><td> 3</td><td>⋯</td><td>24</td><td> 6</td><td>0</td><td> 4</td><td>4</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>1</td></tr>\n",
"\t<tr><td>brainas01</td><td>1871</td><td>1</td><td>WS3</td><td>NA</td><td>30</td><td>134</td><td>24</td><td>30</td><td> 4</td><td>⋯</td><td>21</td><td> 4</td><td>0</td><td> 7</td><td>2</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>1</td></tr>\n",
"\t<tr><td>brannmi01</td><td>1871</td><td>1</td><td>CH1</td><td>NA</td><td> 3</td><td> 14</td><td> 2</td><td> 1</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>burrohe01</td><td>1871</td><td>1</td><td>WS3</td><td>NA</td><td>12</td><td> 63</td><td>11</td><td>15</td><td> 2</td><td>⋯</td><td>14</td><td> 0</td><td>0</td><td> 1</td><td>1</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>careyto01</td><td>1871</td><td>1</td><td>FW1</td><td>NA</td><td>19</td><td> 87</td><td>16</td><td>20</td><td> 2</td><td>⋯</td><td>10</td><td> 5</td><td>0</td><td> 2</td><td>1</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>carleji01</td><td>1871</td><td>1</td><td>CL1</td><td>NA</td><td>29</td><td>127</td><td>31</td><td>32</td><td> 8</td><td>⋯</td><td>18</td><td> 2</td><td>1</td><td> 8</td><td>3</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>3</td></tr>\n",
"\t<tr><td>conefr01 </td><td>1871</td><td>1</td><td>BS1</td><td>NA</td><td>19</td><td> 77</td><td>17</td><td>20</td><td> 3</td><td>⋯</td><td>16</td><td>12</td><td>1</td><td> 8</td><td>2</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>1</td></tr>\n",
"\t<tr><td>connone01</td><td>1871</td><td>1</td><td>TRO</td><td>NA</td><td> 7</td><td> 33</td><td> 6</td><td> 7</td><td> 0</td><td>⋯</td><td> 2</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>0</td></tr>\n",
"\t<tr><td>cravebi01</td><td>1871</td><td>1</td><td>TRO</td><td>NA</td><td>27</td><td>118</td><td>26</td><td>38</td><td> 8</td><td>⋯</td><td>26</td><td> 6</td><td>3</td><td> 3</td><td>0</td><td>NA</td><td>0</td><td>NA</td><td>0</td><td>3</td></tr>\n",
"\t<tr><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋱</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td><td>⋮</td></tr>\n",
"\t<tr><td>wittgni01</td><td>2018</td><td>1</td><td>MIA</td><td>NL</td><td> 32</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>wolteto01</td><td>2018</td><td>1</td><td>COL</td><td>NL</td><td> 74</td><td>182</td><td> 19</td><td> 31</td><td> 4</td><td>⋯</td><td> 27</td><td> 2</td><td>0</td><td>26</td><td> 33</td><td>2</td><td> 6</td><td>0</td><td>2</td><td> 6</td></tr>\n",
"\t<tr><td>wongko01 </td><td>2018</td><td>1</td><td>SLN</td><td>NL</td><td>127</td><td>353</td><td> 41</td><td> 88</td><td>18</td><td>⋯</td><td> 38</td><td> 6</td><td>5</td><td>31</td><td> 60</td><td>3</td><td>14</td><td>6</td><td>3</td><td> 6</td></tr>\n",
"\t<tr><td>woodal02 </td><td>2018</td><td>1</td><td>LAN</td><td>NL</td><td> 33</td><td> 44</td><td> 1</td><td> 2</td><td> 0</td><td>⋯</td><td> 0</td><td> 1</td><td>0</td><td> 0</td><td> 25</td><td>0</td><td> 0</td><td>6</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>woodbl01 </td><td>2018</td><td>1</td><td>LAA</td><td>AL</td><td> 13</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>woodhu01 </td><td>2018</td><td>1</td><td>TBA</td><td>AL</td><td> 31</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>woodrbr01</td><td>2018</td><td>1</td><td>MIL</td><td>NL</td><td> 19</td><td> 8</td><td> 2</td><td> 2</td><td> 0</td><td>⋯</td><td> 1</td><td> 0</td><td>0</td><td> 1</td><td> 1</td><td>0</td><td> 0</td><td>1</td><td>0</td><td> 1</td></tr>\n",
"\t<tr><td>workmbr01</td><td>2018</td><td>1</td><td>BOS</td><td>AL</td><td> 43</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>wrighda03</td><td>2018</td><td>1</td><td>NYN</td><td>NL</td><td> 2</td><td> 2</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 1</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>wrighky01</td><td>2018</td><td>1</td><td>ATL</td><td>NL</td><td> 4</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>wrighmi01</td><td>2018</td><td>1</td><td>BAL</td><td>AL</td><td> 48</td><td> 1</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>wrighst01</td><td>2018</td><td>1</td><td>BOS</td><td>AL</td><td> 20</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>wynnsau01</td><td>2018</td><td>1</td><td>BAL</td><td>AL</td><td> 42</td><td>110</td><td> 16</td><td> 28</td><td> 2</td><td>⋯</td><td> 11</td><td> 0</td><td>0</td><td> 5</td><td> 25</td><td>0</td><td> 0</td><td>3</td><td>0</td><td> 7</td></tr>\n",
"\t<tr><td>yacabji01</td><td>2018</td><td>1</td><td>BAL</td><td>AL</td><td> 12</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>yarbrry01</td><td>2018</td><td>1</td><td>TBA</td><td>AL</td><td> 38</td><td> 3</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 2</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>yateski01</td><td>2018</td><td>1</td><td>SDN</td><td>NL</td><td> 65</td><td> 2</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>yelicch01</td><td>2018</td><td>1</td><td>MIL</td><td>NL</td><td>147</td><td>574</td><td>118</td><td>187</td><td>34</td><td>⋯</td><td>110</td><td>22</td><td>4</td><td>68</td><td>135</td><td>2</td><td> 7</td><td>0</td><td>2</td><td>14</td></tr>\n",
"\t<tr><td>youngch04</td><td>2018</td><td>1</td><td>LAA</td><td>AL</td><td> 56</td><td>113</td><td> 17</td><td> 19</td><td> 2</td><td>⋯</td><td> 13</td><td> 2</td><td>0</td><td>11</td><td> 37</td><td>0</td><td> 2</td><td>1</td><td>1</td><td> 1</td></tr>\n",
"\t<tr><td>younger03</td><td>2018</td><td>1</td><td>LAA</td><td>AL</td><td> 41</td><td>109</td><td> 12</td><td> 22</td><td> 4</td><td>⋯</td><td> 8</td><td> 5</td><td>1</td><td> 6</td><td> 28</td><td>0</td><td> 1</td><td>0</td><td>1</td><td> 4</td></tr>\n",
"\t<tr><td>zagunma01</td><td>2018</td><td>1</td><td>CHN</td><td>NL</td><td> 5</td><td> 5</td><td> 0</td><td> 2</td><td> 1</td><td>⋯</td><td> 1</td><td> 0</td><td>0</td><td> 1</td><td> 1</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>zagurmi01</td><td>2018</td><td>1</td><td>MIL</td><td>NL</td><td> 2</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>zamorda01</td><td>2018</td><td>1</td><td>NYN</td><td>NL</td><td> 16</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>zastrro01</td><td>2018</td><td>1</td><td>CHN</td><td>NL</td><td> 6</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>zieglbr01</td><td>2018</td><td>1</td><td>MIA</td><td>NL</td><td> 53</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>zieglbr01</td><td>2018</td><td>2</td><td>ARI</td><td>NL</td><td> 29</td><td> 0</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>zimmebr01</td><td>2018</td><td>1</td><td>CLE</td><td>AL</td><td> 34</td><td>106</td><td> 14</td><td> 24</td><td> 5</td><td>⋯</td><td> 9</td><td> 4</td><td>1</td><td> 7</td><td> 44</td><td>0</td><td> 1</td><td>0</td><td>0</td><td> 1</td></tr>\n",
"\t<tr><td>zimmejo02</td><td>2018</td><td>1</td><td>DET</td><td>AL</td><td> 25</td><td> 2</td><td> 0</td><td> 0</td><td> 0</td><td>⋯</td><td> 0</td><td> 0</td><td>0</td><td> 0</td><td> 2</td><td>0</td><td> 0</td><td>0</td><td>0</td><td> 0</td></tr>\n",
"\t<tr><td>zimmery01</td><td>2018</td><td>1</td><td>WAS</td><td>NL</td><td> 85</td><td>288</td><td> 33</td><td> 76</td><td>21</td><td>⋯</td><td> 51</td><td> 1</td><td>1</td><td>30</td><td> 55</td><td>1</td><td> 3</td><td>0</td><td>2</td><td>10</td></tr>\n",
"\t<tr><td>zobribe01</td><td>2018</td><td>1</td><td>CHN</td><td>NL</td><td>139</td><td>455</td><td> 67</td><td>139</td><td>28</td><td>⋯</td><td> 58</td><td> 3</td><td>4</td><td>55</td><td> 60</td><td>1</td><td> 2</td><td>1</td><td>7</td><td> 8</td></tr>\n",
"\t<tr><td>zuninmi01</td><td>2018</td><td>1</td><td>SEA</td><td>AL</td><td>113</td><td>373</td><td> 37</td><td> 75</td><td>18</td><td>⋯</td><td> 44</td><td> 0</td><td>0</td><td>24</td><td>150</td><td>0</td><td> 6</td><td>0</td><td>2</td><td> 7</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 105861 × 22\n",
"\\begin{tabular}{r|llllllllllllllllllllll}\n",
" playerID & yearID & stint & teamID & lgID & G & AB & R & H & X2B & X3B & HR & RBI & SB & CS & BB & SO & IBB & HBP & SH & SF & GIDP\\\\\n",
" <chr> & <int> & <int> & <fct> & <fct> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <int> & <dbl> & <int> & <dbl> & <int>\\\\\n",
"\\hline\n",
"\t abercda01 & 1871 & 1 & TRO & NA & 1 & 4 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t addybo01 & 1871 & 1 & RC1 & NA & 25 & 118 & 30 & 32 & 6 & 0 & 0 & 13 & 8 & 1 & 4 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t allisar01 & 1871 & 1 & CL1 & NA & 29 & 137 & 28 & 40 & 4 & 5 & 0 & 19 & 3 & 1 & 2 & 5 & NA & 0 & NA & 0 & 1\\\\\n",
"\t allisdo01 & 1871 & 1 & WS3 & NA & 27 & 133 & 28 & 44 & 10 & 2 & 2 & 27 & 1 & 1 & 0 & 2 & NA & 0 & NA & 0 & 0\\\\\n",
"\t ansonca01 & 1871 & 1 & RC1 & NA & 25 & 120 & 29 & 39 & 11 & 3 & 0 & 16 & 6 & 2 & 2 & 1 & NA & 0 & NA & 0 & 0\\\\\n",
"\t armstbo01 & 1871 & 1 & FW1 & NA & 12 & 49 & 9 & 11 & 2 & 1 & 0 & 5 & 0 & 1 & 0 & 1 & NA & 0 & NA & 0 & 0\\\\\n",
"\t barkeal01 & 1871 & 1 & RC1 & NA & 1 & 4 & 0 & 1 & 0 & 0 & 0 & 2 & 0 & 0 & 1 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t barnero01 & 1871 & 1 & BS1 & NA & 31 & 157 & 66 & 63 & 10 & 9 & 0 & 34 & 11 & 6 & 13 & 1 & NA & 0 & NA & 0 & 1\\\\\n",
"\t barrebi01 & 1871 & 1 & FW1 & NA & 1 & 5 & 1 & 1 & 1 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t barrofr01 & 1871 & 1 & BS1 & NA & 18 & 86 & 13 & 13 & 2 & 1 & 0 & 11 & 1 & 0 & 0 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t bassjo01 & 1871 & 1 & CL1 & NA & 22 & 89 & 18 & 27 & 1 & 10 & 3 & 18 & 0 & 1 & 3 & 4 & NA & 0 & NA & 0 & 0\\\\\n",
"\t battijo01 & 1871 & 1 & CL1 & NA & 1 & 3 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t bealsto01 & 1871 & 1 & WS3 & NA & 10 & 36 & 6 & 7 & 0 & 0 & 0 & 1 & 2 & 0 & 2 & 0 & NA & 0 & NA & 0 & 2\\\\\n",
"\t beaveed01 & 1871 & 1 & TRO & NA & 3 & 15 & 7 & 6 & 0 & 0 & 0 & 5 & 2 & 0 & 0 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t bechtge01 & 1871 & 1 & PH1 & NA & 20 & 94 & 24 & 33 & 9 & 1 & 1 & 21 & 4 & 0 & 2 & 2 & NA & 0 & NA & 0 & 1\\\\\n",
"\t bellast01 & 1871 & 1 & TRO & NA & 29 & 128 & 26 & 32 & 3 & 3 & 0 & 23 & 4 & 4 & 9 & 2 & NA & 0 & NA & 0 & 2\\\\\n",
"\t berkena01 & 1871 & 1 & PH1 & NA & 1 & 4 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 3 & NA & 0 & NA & 0 & 0\\\\\n",
"\t berryto01 & 1871 & 1 & PH1 & NA & 1 & 4 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t berthha01 & 1871 & 1 & WS3 & NA & 17 & 73 & 17 & 17 & 1 & 1 & 0 & 8 & 3 & 1 & 4 & 2 & NA & 0 & NA & 0 & 0\\\\\n",
"\t biermch01 & 1871 & 1 & FW1 & NA & 1 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t birdge01 & 1871 & 1 & RC1 & NA & 25 & 106 & 19 & 28 & 2 & 5 & 0 & 13 & 1 & 0 & 3 & 2 & NA & 0 & NA & 0 & 3\\\\\n",
"\t birdsda01 & 1871 & 1 & BS1 & NA & 29 & 152 & 51 & 46 & 3 & 3 & 0 & 24 & 6 & 0 & 4 & 4 & NA & 0 & NA & 0 & 1\\\\\n",
"\t brainas01 & 1871 & 1 & WS3 & NA & 30 & 134 & 24 & 30 & 4 & 0 & 0 & 21 & 4 & 0 & 7 & 2 & NA & 0 & NA & 0 & 1\\\\\n",
"\t brannmi01 & 1871 & 1 & CH1 & NA & 3 & 14 & 2 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t burrohe01 & 1871 & 1 & WS3 & NA & 12 & 63 & 11 & 15 & 2 & 3 & 1 & 14 & 0 & 0 & 1 & 1 & NA & 0 & NA & 0 & 0\\\\\n",
"\t careyto01 & 1871 & 1 & FW1 & NA & 19 & 87 & 16 & 20 & 2 & 0 & 0 & 10 & 5 & 0 & 2 & 1 & NA & 0 & NA & 0 & 0\\\\\n",
"\t carleji01 & 1871 & 1 & CL1 & NA & 29 & 127 & 31 & 32 & 8 & 1 & 0 & 18 & 2 & 1 & 8 & 3 & NA & 0 & NA & 0 & 3\\\\\n",
"\t conefr01 & 1871 & 1 & BS1 & NA & 19 & 77 & 17 & 20 & 3 & 1 & 0 & 16 & 12 & 1 & 8 & 2 & NA & 0 & NA & 0 & 1\\\\\n",
"\t connone01 & 1871 & 1 & TRO & NA & 7 & 33 & 6 & 7 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & NA & 0 & NA & 0 & 0\\\\\n",
"\t cravebi01 & 1871 & 1 & TRO & NA & 27 & 118 & 26 & 38 & 8 & 1 & 0 & 26 & 6 & 3 & 3 & 0 & NA & 0 & NA & 0 & 3\\\\\n",
"\t ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮ & ⋮\\\\\n",
"\t wittgni01 & 2018 & 1 & MIA & NL & 32 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t wolteto01 & 2018 & 1 & COL & NL & 74 & 182 & 19 & 31 & 4 & 4 & 3 & 27 & 2 & 0 & 26 & 33 & 2 & 6 & 0 & 2 & 6\\\\\n",
"\t wongko01 & 2018 & 1 & SLN & NL & 127 & 353 & 41 & 88 & 18 & 2 & 9 & 38 & 6 & 5 & 31 & 60 & 3 & 14 & 6 & 3 & 6\\\\\n",
"\t woodal02 & 2018 & 1 & LAN & NL & 33 & 44 & 1 & 2 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 25 & 0 & 0 & 6 & 0 & 0\\\\\n",
"\t woodbl01 & 2018 & 1 & LAA & AL & 13 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t woodhu01 & 2018 & 1 & TBA & AL & 31 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t woodrbr01 & 2018 & 1 & MIL & NL & 19 & 8 & 2 & 2 & 0 & 0 & 1 & 1 & 0 & 0 & 1 & 1 & 0 & 0 & 1 & 0 & 1\\\\\n",
"\t workmbr01 & 2018 & 1 & BOS & AL & 43 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t wrighda03 & 2018 & 1 & NYN & NL & 2 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 1 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t wrighky01 & 2018 & 1 & ATL & NL & 4 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t wrighmi01 & 2018 & 1 & BAL & AL & 48 & 1 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t wrighst01 & 2018 & 1 & BOS & AL & 20 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t wynnsau01 & 2018 & 1 & BAL & AL & 42 & 110 & 16 & 28 & 2 & 0 & 4 & 11 & 0 & 0 & 5 & 25 & 0 & 0 & 3 & 0 & 7\\\\\n",
"\t yacabji01 & 2018 & 1 & BAL & AL & 12 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t yarbrry01 & 2018 & 1 & TBA & AL & 38 & 3 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t yateski01 & 2018 & 1 & SDN & NL & 65 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t yelicch01 & 2018 & 1 & MIL & NL & 147 & 574 & 118 & 187 & 34 & 7 & 36 & 110 & 22 & 4 & 68 & 135 & 2 & 7 & 0 & 2 & 14\\\\\n",
"\t youngch04 & 2018 & 1 & LAA & AL & 56 & 113 & 17 & 19 & 2 & 1 & 6 & 13 & 2 & 0 & 11 & 37 & 0 & 2 & 1 & 1 & 1\\\\\n",
"\t younger03 & 2018 & 1 & LAA & AL & 41 & 109 & 12 & 22 & 4 & 2 & 1 & 8 & 5 & 1 & 6 & 28 & 0 & 1 & 0 & 1 & 4\\\\\n",
"\t zagunma01 & 2018 & 1 & CHN & NL & 5 & 5 & 0 & 2 & 1 & 0 & 0 & 1 & 0 & 0 & 1 & 1 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t zagurmi01 & 2018 & 1 & MIL & NL & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t zamorda01 & 2018 & 1 & NYN & NL & 16 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t zastrro01 & 2018 & 1 & CHN & NL & 6 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t zieglbr01 & 2018 & 1 & MIA & NL & 53 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t zieglbr01 & 2018 & 2 & ARI & NL & 29 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t zimmebr01 & 2018 & 1 & CLE & AL & 34 & 106 & 14 & 24 & 5 & 0 & 2 & 9 & 4 & 1 & 7 & 44 & 0 & 1 & 0 & 0 & 1\\\\\n",
"\t zimmejo02 & 2018 & 1 & DET & AL & 25 & 2 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 0 & 2 & 0 & 0 & 0 & 0 & 0\\\\\n",
"\t zimmery01 & 2018 & 1 & WAS & NL & 85 & 288 & 33 & 76 & 21 & 2 & 13 & 51 & 1 & 1 & 30 & 55 & 1 & 3 & 0 & 2 & 10\\\\\n",
"\t zobribe01 & 2018 & 1 & CHN & NL & 139 & 455 & 67 & 139 & 28 & 3 & 9 & 58 & 3 & 4 & 55 & 60 & 1 & 2 & 1 & 7 & 8\\\\\n",
"\t zuninmi01 & 2018 & 1 & SEA & AL & 113 & 373 & 37 & 75 & 18 & 0 & 20 & 44 & 0 & 0 & 24 & 150 & 0 & 6 & 0 & 2 & 7\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 105861 × 22\n",
"\n",
"| playerID &lt;chr&gt; | yearID &lt;int&gt; | stint &lt;int&gt; | teamID &lt;fct&gt; | lgID &lt;fct&gt; | G &lt;int&gt; | AB &lt;int&gt; | R &lt;int&gt; | H &lt;int&gt; | X2B &lt;int&gt; | ⋯ ⋯ | RBI &lt;int&gt; | SB &lt;int&gt; | CS &lt;int&gt; | BB &lt;int&gt; | SO &lt;int&gt; | IBB &lt;int&gt; | HBP &lt;dbl&gt; | SH &lt;int&gt; | SF &lt;dbl&gt; | GIDP &lt;int&gt; |\n",
"|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n",
"| abercda01 | 1871 | 1 | TRO | NA | 1 | 4 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| addybo01 | 1871 | 1 | RC1 | NA | 25 | 118 | 30 | 32 | 6 | ⋯ | 13 | 8 | 1 | 4 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| allisar01 | 1871 | 1 | CL1 | NA | 29 | 137 | 28 | 40 | 4 | ⋯ | 19 | 3 | 1 | 2 | 5 | NA | 0 | NA | 0 | 1 |\n",
"| allisdo01 | 1871 | 1 | WS3 | NA | 27 | 133 | 28 | 44 | 10 | ⋯ | 27 | 1 | 1 | 0 | 2 | NA | 0 | NA | 0 | 0 |\n",
"| ansonca01 | 1871 | 1 | RC1 | NA | 25 | 120 | 29 | 39 | 11 | ⋯ | 16 | 6 | 2 | 2 | 1 | NA | 0 | NA | 0 | 0 |\n",
"| armstbo01 | 1871 | 1 | FW1 | NA | 12 | 49 | 9 | 11 | 2 | ⋯ | 5 | 0 | 1 | 0 | 1 | NA | 0 | NA | 0 | 0 |\n",
"| barkeal01 | 1871 | 1 | RC1 | NA | 1 | 4 | 0 | 1 | 0 | ⋯ | 2 | 0 | 0 | 1 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| barnero01 | 1871 | 1 | BS1 | NA | 31 | 157 | 66 | 63 | 10 | ⋯ | 34 | 11 | 6 | 13 | 1 | NA | 0 | NA | 0 | 1 |\n",
"| barrebi01 | 1871 | 1 | FW1 | NA | 1 | 5 | 1 | 1 | 1 | ⋯ | 1 | 0 | 0 | 0 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| barrofr01 | 1871 | 1 | BS1 | NA | 18 | 86 | 13 | 13 | 2 | ⋯ | 11 | 1 | 0 | 0 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| bassjo01 | 1871 | 1 | CL1 | NA | 22 | 89 | 18 | 27 | 1 | ⋯ | 18 | 0 | 1 | 3 | 4 | NA | 0 | NA | 0 | 0 |\n",
"| battijo01 | 1871 | 1 | CL1 | NA | 1 | 3 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 1 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| bealsto01 | 1871 | 1 | WS3 | NA | 10 | 36 | 6 | 7 | 0 | ⋯ | 1 | 2 | 0 | 2 | 0 | NA | 0 | NA | 0 | 2 |\n",
"| beaveed01 | 1871 | 1 | TRO | NA | 3 | 15 | 7 | 6 | 0 | ⋯ | 5 | 2 | 0 | 0 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| bechtge01 | 1871 | 1 | PH1 | NA | 20 | 94 | 24 | 33 | 9 | ⋯ | 21 | 4 | 0 | 2 | 2 | NA | 0 | NA | 0 | 1 |\n",
"| bellast01 | 1871 | 1 | TRO | NA | 29 | 128 | 26 | 32 | 3 | ⋯ | 23 | 4 | 4 | 9 | 2 | NA | 0 | NA | 0 | 2 |\n",
"| berkena01 | 1871 | 1 | PH1 | NA | 1 | 4 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 3 | NA | 0 | NA | 0 | 0 |\n",
"| berryto01 | 1871 | 1 | PH1 | NA | 1 | 4 | 0 | 1 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| berthha01 | 1871 | 1 | WS3 | NA | 17 | 73 | 17 | 17 | 1 | ⋯ | 8 | 3 | 1 | 4 | 2 | NA | 0 | NA | 0 | 0 |\n",
"| biermch01 | 1871 | 1 | FW1 | NA | 1 | 2 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 1 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| birdge01 | 1871 | 1 | RC1 | NA | 25 | 106 | 19 | 28 | 2 | ⋯ | 13 | 1 | 0 | 3 | 2 | NA | 0 | NA | 0 | 3 |\n",
"| birdsda01 | 1871 | 1 | BS1 | NA | 29 | 152 | 51 | 46 | 3 | ⋯ | 24 | 6 | 0 | 4 | 4 | NA | 0 | NA | 0 | 1 |\n",
"| brainas01 | 1871 | 1 | WS3 | NA | 30 | 134 | 24 | 30 | 4 | ⋯ | 21 | 4 | 0 | 7 | 2 | NA | 0 | NA | 0 | 1 |\n",
"| brannmi01 | 1871 | 1 | CH1 | NA | 3 | 14 | 2 | 1 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| burrohe01 | 1871 | 1 | WS3 | NA | 12 | 63 | 11 | 15 | 2 | ⋯ | 14 | 0 | 0 | 1 | 1 | NA | 0 | NA | 0 | 0 |\n",
"| careyto01 | 1871 | 1 | FW1 | NA | 19 | 87 | 16 | 20 | 2 | ⋯ | 10 | 5 | 0 | 2 | 1 | NA | 0 | NA | 0 | 0 |\n",
"| carleji01 | 1871 | 1 | CL1 | NA | 29 | 127 | 31 | 32 | 8 | ⋯ | 18 | 2 | 1 | 8 | 3 | NA | 0 | NA | 0 | 3 |\n",
"| conefr01 | 1871 | 1 | BS1 | NA | 19 | 77 | 17 | 20 | 3 | ⋯ | 16 | 12 | 1 | 8 | 2 | NA | 0 | NA | 0 | 1 |\n",
"| connone01 | 1871 | 1 | TRO | NA | 7 | 33 | 6 | 7 | 0 | ⋯ | 2 | 0 | 0 | 0 | 0 | NA | 0 | NA | 0 | 0 |\n",
"| cravebi01 | 1871 | 1 | TRO | NA | 27 | 118 | 26 | 38 | 8 | ⋯ | 26 | 6 | 3 | 3 | 0 | NA | 0 | NA | 0 | 3 |\n",
"| ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋱ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ | ⋮ |\n",
"| wittgni01 | 2018 | 1 | MIA | NL | 32 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| wolteto01 | 2018 | 1 | COL | NL | 74 | 182 | 19 | 31 | 4 | ⋯ | 27 | 2 | 0 | 26 | 33 | 2 | 6 | 0 | 2 | 6 |\n",
"| wongko01 | 2018 | 1 | SLN | NL | 127 | 353 | 41 | 88 | 18 | ⋯ | 38 | 6 | 5 | 31 | 60 | 3 | 14 | 6 | 3 | 6 |\n",
"| woodal02 | 2018 | 1 | LAN | NL | 33 | 44 | 1 | 2 | 0 | ⋯ | 0 | 1 | 0 | 0 | 25 | 0 | 0 | 6 | 0 | 0 |\n",
"| woodbl01 | 2018 | 1 | LAA | AL | 13 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| woodhu01 | 2018 | 1 | TBA | AL | 31 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| woodrbr01 | 2018 | 1 | MIL | NL | 19 | 8 | 2 | 2 | 0 | ⋯ | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 1 |\n",
"| workmbr01 | 2018 | 1 | BOS | AL | 43 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| wrighda03 | 2018 | 1 | NYN | NL | 2 | 2 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| wrighky01 | 2018 | 1 | ATL | NL | 4 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| wrighmi01 | 2018 | 1 | BAL | AL | 48 | 1 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| wrighst01 | 2018 | 1 | BOS | AL | 20 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| wynnsau01 | 2018 | 1 | BAL | AL | 42 | 110 | 16 | 28 | 2 | ⋯ | 11 | 0 | 0 | 5 | 25 | 0 | 0 | 3 | 0 | 7 |\n",
"| yacabji01 | 2018 | 1 | BAL | AL | 12 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| yarbrry01 | 2018 | 1 | TBA | AL | 38 | 3 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 |\n",
"| yateski01 | 2018 | 1 | SDN | NL | 65 | 2 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| yelicch01 | 2018 | 1 | MIL | NL | 147 | 574 | 118 | 187 | 34 | ⋯ | 110 | 22 | 4 | 68 | 135 | 2 | 7 | 0 | 2 | 14 |\n",
"| youngch04 | 2018 | 1 | LAA | AL | 56 | 113 | 17 | 19 | 2 | ⋯ | 13 | 2 | 0 | 11 | 37 | 0 | 2 | 1 | 1 | 1 |\n",
"| younger03 | 2018 | 1 | LAA | AL | 41 | 109 | 12 | 22 | 4 | ⋯ | 8 | 5 | 1 | 6 | 28 | 0 | 1 | 0 | 1 | 4 |\n",
"| zagunma01 | 2018 | 1 | CHN | NL | 5 | 5 | 0 | 2 | 1 | ⋯ | 1 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 |\n",
"| zagurmi01 | 2018 | 1 | MIL | NL | 2 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| zamorda01 | 2018 | 1 | NYN | NL | 16 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| zastrro01 | 2018 | 1 | CHN | NL | 6 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| zieglbr01 | 2018 | 1 | MIA | NL | 53 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| zieglbr01 | 2018 | 2 | ARI | NL | 29 | 0 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |\n",
"| zimmebr01 | 2018 | 1 | CLE | AL | 34 | 106 | 14 | 24 | 5 | ⋯ | 9 | 4 | 1 | 7 | 44 | 0 | 1 | 0 | 0 | 1 |\n",
"| zimmejo02 | 2018 | 1 | DET | AL | 25 | 2 | 0 | 0 | 0 | ⋯ | 0 | 0 | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 |\n",
"| zimmery01 | 2018 | 1 | WAS | NL | 85 | 288 | 33 | 76 | 21 | ⋯ | 51 | 1 | 1 | 30 | 55 | 1 | 3 | 0 | 2 | 10 |\n",
"| zobribe01 | 2018 | 1 | CHN | NL | 139 | 455 | 67 | 139 | 28 | ⋯ | 58 | 3 | 4 | 55 | 60 | 1 | 2 | 1 | 7 | 8 |\n",
"| zuninmi01 | 2018 | 1 | SEA | AL | 113 | 373 | 37 | 75 | 18 | ⋯ | 44 | 0 | 0 | 24 | 150 | 0 | 6 | 0 | 2 | 7 |\n",
"\n"
],
"text/plain": [
" playerID yearID stint teamID lgID G AB R H X2B ⋯ RBI SB CS BB\n",
"1 abercda01 1871 1 TRO NA 1 4 0 0 0 ⋯ 0 0 0 0\n",
"2 addybo01 1871 1 RC1 NA 25 118 30 32 6 ⋯ 13 8 1 4\n",
"3 allisar01 1871 1 CL1 NA 29 137 28 40 4 ⋯ 19 3 1 2\n",
"4 allisdo01 1871 1 WS3 NA 27 133 28 44 10 ⋯ 27 1 1 0\n",
"5 ansonca01 1871 1 RC1 NA 25 120 29 39 11 ⋯ 16 6 2 2\n",
"6 armstbo01 1871 1 FW1 NA 12 49 9 11 2 ⋯ 5 0 1 0\n",
"7 barkeal01 1871 1 RC1 NA 1 4 0 1 0 ⋯ 2 0 0 1\n",
"8 barnero01 1871 1 BS1 NA 31 157 66 63 10 ⋯ 34 11 6 13\n",
"9 barrebi01 1871 1 FW1 NA 1 5 1 1 1 ⋯ 1 0 0 0\n",
"10 barrofr01 1871 1 BS1 NA 18 86 13 13 2 ⋯ 11 1 0 0\n",
"11 bassjo01 1871 1 CL1 NA 22 89 18 27 1 ⋯ 18 0 1 3\n",
"12 battijo01 1871 1 CL1 NA 1 3 0 0 0 ⋯ 0 0 0 1\n",
"13 bealsto01 1871 1 WS3 NA 10 36 6 7 0 ⋯ 1 2 0 2\n",
"14 beaveed01 1871 1 TRO NA 3 15 7 6 0 ⋯ 5 2 0 0\n",
"15 bechtge01 1871 1 PH1 NA 20 94 24 33 9 ⋯ 21 4 0 2\n",
"16 bellast01 1871 1 TRO NA 29 128 26 32 3 ⋯ 23 4 4 9\n",
"17 berkena01 1871 1 PH1 NA 1 4 0 0 0 ⋯ 0 0 0 0\n",
"18 berryto01 1871 1 PH1 NA 1 4 0 1 0 ⋯ 0 0 0 0\n",
"19 berthha01 1871 1 WS3 NA 17 73 17 17 1 ⋯ 8 3 1 4\n",
"20 biermch01 1871 1 FW1 NA 1 2 0 0 0 ⋯ 0 0 0 1\n",
"21 birdge01 1871 1 RC1 NA 25 106 19 28 2 ⋯ 13 1 0 3\n",
"22 birdsda01 1871 1 BS1 NA 29 152 51 46 3 ⋯ 24 6 0 4\n",
"23 brainas01 1871 1 WS3 NA 30 134 24 30 4 ⋯ 21 4 0 7\n",
"24 brannmi01 1871 1 CH1 NA 3 14 2 1 0 ⋯ 0 0 0 0\n",
"25 burrohe01 1871 1 WS3 NA 12 63 11 15 2 ⋯ 14 0 0 1\n",
"26 careyto01 1871 1 FW1 NA 19 87 16 20 2 ⋯ 10 5 0 2\n",
"27 carleji01 1871 1 CL1 NA 29 127 31 32 8 ⋯ 18 2 1 8\n",
"28 conefr01 1871 1 BS1 NA 19 77 17 20 3 ⋯ 16 12 1 8\n",
"29 connone01 1871 1 TRO NA 7 33 6 7 0 ⋯ 2 0 0 0\n",
"30 cravebi01 1871 1 TRO NA 27 118 26 38 8 ⋯ 26 6 3 3\n",
"⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋱ ⋮ ⋮ ⋮ ⋮ \n",
"105832 wittgni01 2018 1 MIA NL 32 0 0 0 0 ⋯ 0 0 0 0\n",
"105833 wolteto01 2018 1 COL NL 74 182 19 31 4 ⋯ 27 2 0 26\n",
"105834 wongko01 2018 1 SLN NL 127 353 41 88 18 ⋯ 38 6 5 31\n",
"105835 woodal02 2018 1 LAN NL 33 44 1 2 0 ⋯ 0 1 0 0\n",
"105836 woodbl01 2018 1 LAA AL 13 0 0 0 0 ⋯ 0 0 0 0\n",
"105837 woodhu01 2018 1 TBA AL 31 0 0 0 0 ⋯ 0 0 0 0\n",
"105838 woodrbr01 2018 1 MIL NL 19 8 2 2 0 ⋯ 1 0 0 1\n",
"105839 workmbr01 2018 1 BOS AL 43 0 0 0 0 ⋯ 0 0 0 0\n",
"105840 wrighda03 2018 1 NYN NL 2 2 0 0 0 ⋯ 0 0 0 1\n",
"105841 wrighky01 2018 1 ATL NL 4 0 0 0 0 ⋯ 0 0 0 0\n",
"105842 wrighmi01 2018 1 BAL AL 48 1 0 0 0 ⋯ 0 0 0 0\n",
"105843 wrighst01 2018 1 BOS AL 20 0 0 0 0 ⋯ 0 0 0 0\n",
"105844 wynnsau01 2018 1 BAL AL 42 110 16 28 2 ⋯ 11 0 0 5\n",
"105845 yacabji01 2018 1 BAL AL 12 0 0 0 0 ⋯ 0 0 0 0\n",
"105846 yarbrry01 2018 1 TBA AL 38 3 0 0 0 ⋯ 0 0 0 0\n",
"105847 yateski01 2018 1 SDN NL 65 2 0 0 0 ⋯ 0 0 0 0\n",
"105848 yelicch01 2018 1 MIL NL 147 574 118 187 34 ⋯ 110 22 4 68\n",
"105849 youngch04 2018 1 LAA AL 56 113 17 19 2 ⋯ 13 2 0 11\n",
"105850 younger03 2018 1 LAA AL 41 109 12 22 4 ⋯ 8 5 1 6\n",
"105851 zagunma01 2018 1 CHN NL 5 5 0 2 1 ⋯ 1 0 0 1\n",
"105852 zagurmi01 2018 1 MIL NL 2 0 0 0 0 ⋯ 0 0 0 0\n",
"105853 zamorda01 2018 1 NYN NL 16 0 0 0 0 ⋯ 0 0 0 0\n",
"105854 zastrro01 2018 1 CHN NL 6 0 0 0 0 ⋯ 0 0 0 0\n",
"105855 zieglbr01 2018 1 MIA NL 53 0 0 0 0 ⋯ 0 0 0 0\n",
"105856 zieglbr01 2018 2 ARI NL 29 0 0 0 0 ⋯ 0 0 0 0\n",
"105857 zimmebr01 2018 1 CLE AL 34 106 14 24 5 ⋯ 9 4 1 7\n",
"105858 zimmejo02 2018 1 DET AL 25 2 0 0 0 ⋯ 0 0 0 0\n",
"105859 zimmery01 2018 1 WAS NL 85 288 33 76 21 ⋯ 51 1 1 30\n",
"105860 zobribe01 2018 1 CHN NL 139 455 67 139 28 ⋯ 58 3 4 55\n",
"105861 zuninmi01 2018 1 SEA AL 113 373 37 75 18 ⋯ 44 0 0 24\n",
" SO IBB HBP SH SF GIDP\n",
"1 0 NA 0 NA 0 0 \n",
"2 0 NA 0 NA 0 0 \n",
"3 5 NA 0 NA 0 1 \n",
"4 2 NA 0 NA 0 0 \n",
"5 1 NA 0 NA 0 0 \n",
"6 1 NA 0 NA 0 0 \n",
"7 0 NA 0 NA 0 0 \n",
"8 1 NA 0 NA 0 1 \n",
"9 0 NA 0 NA 0 0 \n",
"10 0 NA 0 NA 0 0 \n",
"11 4 NA 0 NA 0 0 \n",
"12 0 NA 0 NA 0 0 \n",
"13 0 NA 0 NA 0 2 \n",
"14 0 NA 0 NA 0 0 \n",
"15 2 NA 0 NA 0 1 \n",
"16 2 NA 0 NA 0 2 \n",
"17 3 NA 0 NA 0 0 \n",
"18 0 NA 0 NA 0 0 \n",
"19 2 NA 0 NA 0 0 \n",
"20 0 NA 0 NA 0 0 \n",
"21 2 NA 0 NA 0 3 \n",
"22 4 NA 0 NA 0 1 \n",
"23 2 NA 0 NA 0 1 \n",
"24 0 NA 0 NA 0 0 \n",
"25 1 NA 0 NA 0 0 \n",
"26 1 NA 0 NA 0 0 \n",
"27 3 NA 0 NA 0 3 \n",
"28 2 NA 0 NA 0 1 \n",
"29 0 NA 0 NA 0 0 \n",
"30 0 NA 0 NA 0 3 \n",
"⋮ ⋮ ⋮ ⋮ ⋮ ⋮ ⋮ \n",
"105832 0 0 0 0 0 0 \n",
"105833 33 2 6 0 2 6 \n",
"105834 60 3 14 6 3 6 \n",
"105835 25 0 0 6 0 0 \n",
"105836 0 0 0 0 0 0 \n",
"105837 0 0 0 0 0 0 \n",
"105838 1 0 0 1 0 1 \n",
"105839 0 0 0 0 0 0 \n",
"105840 0 0 0 0 0 0 \n",
"105841 0 0 0 0 0 0 \n",
"105842 0 0 0 0 0 0 \n",
"105843 0 0 0 0 0 0 \n",
"105844 25 0 0 3 0 7 \n",
"105845 0 0 0 0 0 0 \n",
"105846 2 0 0 0 0 0 \n",
"105847 0 0 0 0 0 0 \n",
"105848 135 2 7 0 2 14 \n",
"105849 37 0 2 1 1 1 \n",
"105850 28 0 1 0 1 4 \n",
"105851 1 0 0 0 0 0 \n",
"105852 0 0 0 0 0 0 \n",
"105853 0 0 0 0 0 0 \n",
"105854 0 0 0 0 0 0 \n",
"105855 0 0 0 0 0 0 \n",
"105856 0 0 0 0 0 0 \n",
"105857 44 0 1 0 0 1 \n",
"105858 2 0 0 0 0 0 \n",
"105859 55 1 3 0 2 10 \n",
"105860 60 1 2 1 7 8 \n",
"105861 150 0 6 0 2 7 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"batting"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"get_stats <- function(player.id) {\n",
" batting %>%\n",
" filter(playerID == player.id) %>%\n",
" inner_join(Master, by = \"playerID\") %>%\n",
" mutate(birthyear = ifelse(birthMonth >= 7, birthYear + 1, birthYear),\n",
" Age = yearID - birthyear,\n",
" SLG = (H - X2B - X3B - HR + 2 * X2B + 3 * X3B + 4 * HR) / AB,\n",
" OBP = (H + BB + HBP) / (AB + BB + HBP +SF),\n",
" OPS = SLG + OBP) %>%\n",
" select(Age, SLG, OBP, OPS)\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<pre class=language-r><code>function (player.id) \n",
"{\n",
"<span style=white-space:pre-wrap> batting %&gt;% filter(playerID == player.id) %&gt;% inner_join(Master, </span>\n",
"<span style=white-space:pre-wrap> by = \"playerID\") %&gt;% mutate(birthyear = ifelse(birthMonth &gt;= </span>\n",
"<span style=white-space:pre-wrap> 7, birthYear + 1, birthYear), Age = yearID - birthyear, </span>\n",
"<span style=white-space:pre-wrap> SLG = (H - X2B - X3B - HR + 2 * X2B + 3 * X3B + 4 * HR)/AB, </span>\n",
"<span style=white-space:pre-wrap> OBP = (H + BB + HBP)/(AB + BB + HBP + SF), OPS = SLG + </span>\n",
"<span style=white-space:pre-wrap> OBP) %&gt;% select(Age, SLG, OBP, OPS)</span>\n",
"}</code></pre>"
],
"text/latex": [
"\\begin{minted}{r}\n",
"function (player.id) \n",
"\\{\n",
" batting \\%>\\% filter(playerID == player.id) \\%>\\% inner\\_join(Master, \n",
" by = \"playerID\") \\%>\\% mutate(birthyear = ifelse(birthMonth >= \n",
" 7, birthYear + 1, birthYear), Age = yearID - birthyear, \n",
" SLG = (H - X2B - X3B - HR + 2 * X2B + 3 * X3B + 4 * HR)/AB, \n",
" OBP = (H + BB + HBP)/(AB + BB + HBP + SF), OPS = SLG + \n",
" OBP) \\%>\\% select(Age, SLG, OBP, OPS)\n",
"\\}\n",
"\\end{minted}"
],
"text/markdown": [
"```r\n",
"function (player.id) \n",
"{\n",
" batting %>% filter(playerID == player.id) %>% inner_join(Master, \n",
" by = \"playerID\") %>% mutate(birthyear = ifelse(birthMonth >= \n",
" 7, birthYear + 1, birthYear), Age = yearID - birthyear, \n",
" SLG = (H - X2B - X3B - HR + 2 * X2B + 3 * X3B + 4 * HR)/AB, \n",
" OBP = (H + BB + HBP)/(AB + BB + HBP + SF), OPS = SLG + \n",
" OBP) %>% select(Age, SLG, OBP, OPS)\n",
"}\n",
"```"
],
"text/plain": [
"function(player.id) {\n",
" batting %>%\n",
" filter(playerID == player.id) %>%\n",
" inner_join(Master, by = \"playerID\") %>%\n",
" mutate(birthyear = ifelse(birthMonth >= 7, birthYear + 1, birthYear),\n",
" Age = yearID - birthyear,\n",
" SLG = (H - X2B - X3B - HR + 2 * X2B + 3 * X3B + 4 * HR) / AB,\n",
" OBP = (H + BB + HBP) / (AB + BB + HBP +SF),\n",
" OPS = SLG + OBP) %>%\n",
" select(Age, SLG, OBP, OPS)\n",
"}"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"get_stats"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"Mantle <- get_stats(mantle_id)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<table>\n",
"<caption>A data.frame: 18 × 4</caption>\n",
"<thead>\n",
"\t<tr><th scope=col>Age</th><th scope=col>SLG</th><th scope=col>OBP</th><th scope=col>OPS</th></tr>\n",
"\t<tr><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th><th scope=col>&lt;dbl&gt;</th></tr>\n",
"</thead>\n",
"<tbody>\n",
"\t<tr><td>19</td><td>0.4428152</td><td>0.3489583</td><td>0.7917736</td></tr>\n",
"\t<tr><td>20</td><td>0.5300546</td><td>0.3942308</td><td>0.9242854</td></tr>\n",
"\t<tr><td>21</td><td>0.4967462</td><td>0.3981481</td><td>0.8948944</td></tr>\n",
"\t<tr><td>22</td><td>0.5248619</td><td>0.4083205</td><td>0.9331824</td></tr>\n",
"\t<tr><td>23</td><td>0.6112186</td><td>0.4308176</td><td>1.0420362</td></tr>\n",
"\t<tr><td>24</td><td>0.7054409</td><td>0.4639017</td><td>1.1693426</td></tr>\n",
"\t<tr><td>25</td><td>0.6645570</td><td>0.5120385</td><td>1.1765955</td></tr>\n",
"\t<tr><td>26</td><td>0.5915222</td><td>0.4432515</td><td>1.0347737</td></tr>\n",
"\t<tr><td>27</td><td>0.5138632</td><td>0.3902821</td><td>0.9041453</td></tr>\n",
"\t<tr><td>28</td><td>0.5578748</td><td>0.3990683</td><td>0.9569431</td></tr>\n",
"\t<tr><td>29</td><td>0.6867704</td><td>0.4480620</td><td>1.1348324</td></tr>\n",
"\t<tr><td>30</td><td>0.6047745</td><td>0.4860558</td><td>1.0908303</td></tr>\n",
"\t<tr><td>31</td><td>0.6220930</td><td>0.4413146</td><td>1.0634076</td></tr>\n",
"\t<tr><td>32</td><td>0.5913978</td><td>0.4232804</td><td>1.0146783</td></tr>\n",
"\t<tr><td>33</td><td>0.4515235</td><td>0.3793103</td><td>0.8308339</td></tr>\n",
"\t<tr><td>34</td><td>0.5375375</td><td>0.3893130</td><td>0.9268505</td></tr>\n",
"\t<tr><td>35</td><td>0.4340909</td><td>0.3905967</td><td>0.8246877</td></tr>\n",
"\t<tr><td>36</td><td>0.3977011</td><td>0.3846154</td><td>0.7823165</td></tr>\n",
"</tbody>\n",
"</table>\n"
],
"text/latex": [
"A data.frame: 18 × 4\n",
"\\begin{tabular}{r|llll}\n",
" Age & SLG & OBP & OPS\\\\\n",
" <dbl> & <dbl> & <dbl> & <dbl>\\\\\n",
"\\hline\n",
"\t 19 & 0.4428152 & 0.3489583 & 0.7917736\\\\\n",
"\t 20 & 0.5300546 & 0.3942308 & 0.9242854\\\\\n",
"\t 21 & 0.4967462 & 0.3981481 & 0.8948944\\\\\n",
"\t 22 & 0.5248619 & 0.4083205 & 0.9331824\\\\\n",
"\t 23 & 0.6112186 & 0.4308176 & 1.0420362\\\\\n",
"\t 24 & 0.7054409 & 0.4639017 & 1.1693426\\\\\n",
"\t 25 & 0.6645570 & 0.5120385 & 1.1765955\\\\\n",
"\t 26 & 0.5915222 & 0.4432515 & 1.0347737\\\\\n",
"\t 27 & 0.5138632 & 0.3902821 & 0.9041453\\\\\n",
"\t 28 & 0.5578748 & 0.3990683 & 0.9569431\\\\\n",
"\t 29 & 0.6867704 & 0.4480620 & 1.1348324\\\\\n",
"\t 30 & 0.6047745 & 0.4860558 & 1.0908303\\\\\n",
"\t 31 & 0.6220930 & 0.4413146 & 1.0634076\\\\\n",
"\t 32 & 0.5913978 & 0.4232804 & 1.0146783\\\\\n",
"\t 33 & 0.4515235 & 0.3793103 & 0.8308339\\\\\n",
"\t 34 & 0.5375375 & 0.3893130 & 0.9268505\\\\\n",
"\t 35 & 0.4340909 & 0.3905967 & 0.8246877\\\\\n",
"\t 36 & 0.3977011 & 0.3846154 & 0.7823165\\\\\n",
"\\end{tabular}\n"
],
"text/markdown": [
"\n",
"A data.frame: 18 × 4\n",
"\n",
"| Age &lt;dbl&gt; | SLG &lt;dbl&gt; | OBP &lt;dbl&gt; | OPS &lt;dbl&gt; |\n",
"|---|---|---|---|\n",
"| 19 | 0.4428152 | 0.3489583 | 0.7917736 |\n",
"| 20 | 0.5300546 | 0.3942308 | 0.9242854 |\n",
"| 21 | 0.4967462 | 0.3981481 | 0.8948944 |\n",
"| 22 | 0.5248619 | 0.4083205 | 0.9331824 |\n",
"| 23 | 0.6112186 | 0.4308176 | 1.0420362 |\n",
"| 24 | 0.7054409 | 0.4639017 | 1.1693426 |\n",
"| 25 | 0.6645570 | 0.5120385 | 1.1765955 |\n",
"| 26 | 0.5915222 | 0.4432515 | 1.0347737 |\n",
"| 27 | 0.5138632 | 0.3902821 | 0.9041453 |\n",
"| 28 | 0.5578748 | 0.3990683 | 0.9569431 |\n",
"| 29 | 0.6867704 | 0.4480620 | 1.1348324 |\n",
"| 30 | 0.6047745 | 0.4860558 | 1.0908303 |\n",
"| 31 | 0.6220930 | 0.4413146 | 1.0634076 |\n",
"| 32 | 0.5913978 | 0.4232804 | 1.0146783 |\n",
"| 33 | 0.4515235 | 0.3793103 | 0.8308339 |\n",
"| 34 | 0.5375375 | 0.3893130 | 0.9268505 |\n",
"| 35 | 0.4340909 | 0.3905967 | 0.8246877 |\n",
"| 36 | 0.3977011 | 0.3846154 | 0.7823165 |\n",
"\n"
],
"text/plain": [
" Age SLG OBP OPS \n",
"1 19 0.4428152 0.3489583 0.7917736\n",
"2 20 0.5300546 0.3942308 0.9242854\n",
"3 21 0.4967462 0.3981481 0.8948944\n",
"4 22 0.5248619 0.4083205 0.9331824\n",
"5 23 0.6112186 0.4308176 1.0420362\n",
"6 24 0.7054409 0.4639017 1.1693426\n",
"7 25 0.6645570 0.5120385 1.1765955\n",
"8 26 0.5915222 0.4432515 1.0347737\n",
"9 27 0.5138632 0.3902821 0.9041453\n",
"10 28 0.5578748 0.3990683 0.9569431\n",
"11 29 0.6867704 0.4480620 1.1348324\n",
"12 30 0.6047745 0.4860558 1.0908303\n",
"13 31 0.6220930 0.4413146 1.0634076\n",
"14 32 0.5913978 0.4232804 1.0146783\n",
"15 33 0.4515235 0.3793103 0.8308339\n",
"16 34 0.5375375 0.3893130 0.9268505\n",
"17 35 0.4340909 0.3905967 0.8246877\n",
"18 36 0.3977011 0.3846154 0.7823165"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Mantle"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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gQIECBAgEBLCQhILVUugyVAgAABAgQI\nECBAoJ4CAlI9dW2bAAECBAgQIECAAIGWEhCQWqpcBkuAAAECBAgQIECAQD0FOuu58Sxuu6ur\nK4vDytyY2tv/nJ3Td2aZK0+kunR2dqpN9koTbW1tpVF53GSvOOkx45iWvbqkEY38zUk1GnkM\nZXOkxRxVqoljWvZq39HRURpU+q4+tdWn1uNLoQJSOgBPmzatNkG9SgLpjxWz7P0ypLqMfGVv\ndMUeUTr4pi+Pm+z9HqS/AekfCbXJXm1G/rmbOnVqDA8PZ2+ABR+RY1o2fwFGAlJ3d3fp2JbN\nUWZrVIODgzUNqFABaWhoKFasWFETTNE7pX8k0h+qvr6+WLp0adE5Mjf/GTNmRH9/f6xevTpz\nYyv6gObNm1d6NtzjJnu/CemfiHRcW7ZsWfYGV/ARzZw5s/SkT/obPTAwUHCN7E0/Hdcc07JX\nl56enkjHtVWrVsXKlSuzN8AMjiiFyunTp1cdmfcgVSXSgQABAgQIECBAgACBoggISEWptHkS\nIECAAAECBAgQIFBVQECqSqQDAQIECBAgQIAAAQJFERCQilJp8yRAgAABAgQIECBAoKqAgFSV\nSAcCBAgQIECAAAECBIoiICAVpdLmSYAAAQIECBAgQIBAVQEBqSqRDgQIECBAgAABAgQIFEVA\nQCpKpc2TAAECBAgQIECAAIGqAgJSVSIdCBAgQIAAAQIECBAoioCAVJRKmycBAgQIECBAgAAB\nAlUFBKSqRDoQIECAAAECBAgQIFAUAQGpKJU2TwIECBAgQIAAAQIEqgoISFWJdCBAgAABAgQI\nECBAoCgCAlJRKm2eBAgQIECAAAECBAhUFRCQqhLpQIAAAQIECBAgQIBAUQQEpKJU2jwJECBA\ngAABAgQIEKgqICBVJdKBAAECBAgQIECAAIGiCAhIRam0eRIgQIAAAQIECBAgUFVAQKpKpAMB\nAgQIECBAgAABAkUREJCKUmnzJECAAAECBAgQIECgqoCAVJVIBwIECBAgQIAAAQIEiiLQWZSJ\nmicBAgQIECiawFNPPRW33357DA4Oxp577hkLFiwoGoH5EiBAYL0FBKT1JrMCAQIECBDIvsB/\n/Md/xCmnnBJdXV2lwfb29saHP/zh+MQnPpH9wRshAQIEmijgJXZNxLdrAgQIECBQD4Fbb701\nTj755NKZo9WrV0f6Gh4ejvPOOy++973v1WOXtkmAAIHcCAhIuSmliRAgQIAAgT8LXHjhhaVA\ntLZHeqndN77xjbWb3SZAgACBNQQEpDUw/EiAAAECBPIg8Lvf/a7iNJ5++umK97mDAAECBCIE\nJL8FBAgQIEAgZwLbb799dHR0lJ3VtttuW7ZdIwECBAj8WUBA8ptAgAABAgRyJvChD32o7Iza\n29vjn/7pn8rep5EAAQIE/iwgIPlNIECAAAECORPYYYcd4pJLLomNN944UihKX9OnT49zzjkn\n9thjj5zN1nQIECCwYQVc5nvDetoaAQIECBDIhMDrX//6uO+++2LhwoUxNDQUKTR1d3dnYmwG\nQYAAgSwLCEhZro6xESBAgACBSQh0dnbGTjvtNIktWJUAAQLFE/ASu+LV3IwJECBAgAABAgQI\nEKggICBVgNFMgAABAgQIECBAgEDxBASk4tXcjAkQIECAAAECBAgQqCAgIFWA0UyAAAECBAgQ\nIECAQPEEBKTi1dyMCRAgQIAAAQIECBCoICAgVYDRTIAAAQIECBAgQIBA8QQEpOLV3IwJECBA\ngAABAgQIEKggICBVgNFMgAABAgQIECBAgEDxBASk4tXcjAkQIECAAAECBAgQqCAgIFWA0UyA\nAAECBAgQIECAQPEEBKTi1dyMCRAgQIAAAQIECBCoICAgVYDRTIAAAQIECBAgQIBA8QQEpOLV\n3IwJECBAgAABAgQIEKggICBVgNFMgAABAgQIECBAgEDxBASk4tXcjAkQIECAAAECBAgQqCAg\nIFWA0UyAAAECBAgQIECAQPEEBKTi1dyMCRAgQIAAAQIECBCoICAgVYDRTIAAAQIECBAgQIBA\n8QQEpOLV3IwJECBAgAABAgQIEKggICBVgNFMgAABAgQIECBAgEDxBASk4tXcjAkQIECAAAEC\nBAgQqCAgIFWA0UyAAAECBAgQIECAQPEEBKTi1dyMCRAgQIAAAQIECBCoICAgVYDRTIAAAQIE\nCBAgQIBA8QQEpOLV3IwJECBAgAABAgQIEKggICBVgNFMgAABAgQIECBAgEDxBASk4tXcjAkQ\nIECAAAECBAgQqCAgIFWA0UyAAAECBAgQIECAQPEEBKTi1dyMCRAgQIAAAQIECBCoICAgVYDR\nTIAAAQIECBAgQIBA8QQEpOLV3IwJECBAgAABAgQIEKggICBVgNFMgAABAgQIECBAgEDxBASk\n4tXcjAkQIECAAAECBAgQqCAgIFWA0UyAAAECBAgQIECAQPEEBKTi1dyMCRAgQIAAAQIECBCo\nICAgVYDRTIAAAQIECBAgQIBA8QQEpOLV3IwJECBAgAABAgQIEKggICBVgNFMgAABAgQIECBA\ngEDxBASk4tXcjAkQIECAAAECBAgQqCAgIFWA0UyAAAECBAgQIECAQPEEBKTi1dyMCRAgQIAA\nAQIECBCoICAgVYDRTIAAAQIECBAgQIBA8QQEpOLV3IwJECBAgAABAgQIEKggICBVgNFMgAAB\nAgQIECBAgEDxBASk4tXcjAkQIECAAAECBAgQqCAgIFWA0UyAAAECBAgQIECAQPEEBKTi1dyM\nCRAgQIAAAQIECBCoICAgVYDRTIAAAQIECBAgQIBA8QQEpOLV3IwJECBAgAABAgQIEKggICBV\ngNFMgAABAgQIECBAgEDxBASk4tXcjAkQIECAAAECBAgQqCAgIFWA0UyAAAECBAgQIECAQPEE\nMhOQBgcH45JLLonly5fXXIXbbrstfvGLX9TcX0cCBAgQIECAAAECBAisSyAzAem8886L888/\nP5577rl1jXf0vvvuuy8+9alPxcKFC0fb/ECAAAECBAgQIECAAIHJCHROZuUNse6iRYvizDPP\njHvvvbemzQ0MDMSll15a+mpra6tpHZ0IECBAgAABAgQIECBQi0DTzyCdfvrpMTw8HGeccUYt\n443rrrsurr322vjc5z4XW2+9dU3r6ESAAAECBAgQIECAAIFaBJp+BunjH/94zJ8/Px5//PFa\nxht77rlnHHDAAdHZ2RnpZXmVlj/84Q+x9957j7n7hBNOiOOOO25MmxvrFujp6YnNNtts3Z3c\nS4DAOAGPm3EkmWmYOnVqZsZiIGMFNtlkk7ENbmVGwDEtM6UYN5CZM2dG+rJUF+jv76/e6U89\nmh6QUjhan2Xu3Lk1dU8BaqeddhrTNx14a4UZs2JBb3R3d5fO7qWXNVqyJdDR0VGqzdDQULYG\nZjTR1dVVUnCsyd4vQ3pZdnt7e6SLAlmyJZCOaekr/b1JryqxZEsgHdcc07JVkzSadDxL/++m\nY5r/B2qrTzrGpP9vqy1ND0jVBjjR+zfeeOO46qqrxqyerpC3ZMmSMW1ulBdID7oUXnt7e2Pp\n0qXlO2ltmsCMGTNKf6xWr17dtDHYcXmBefPmlf5oOdaU92lma/qjmM4eLVu2rJnDsO8yAunZ\n72nTppX+3nhSrgxQk5vScc0xrclFKLP79CqfOXPmxPPPPx8rV64s00PT2gLpiZiNNtpo7eZx\nt5v+HqRxI9JAgAABAgQIECBAgACBJgkISE2Ct1sCBAgQIECAAAECBLInkPmAlD4M9vrrr8+e\nnBERIECAAAECBAgQIJA7gcwHpBtvvDGuvvrq3MGbEAECBAgQIECAAAEC2RPIzEUaFixYELff\nfvs4oc9+9rPj2kYavvnNb4786DsBAgQIECBAgAABAgQmLZD5M0iTnqENECBAgAABAgQIECBA\noEYBAalGKN0IECBAgAABAgQIEMi/gICU/xqbIQECBAgQIECAAAECNQoISDVC6UaAAAECBAgQ\nIECAQP4FBKT819gMCRAgQIAAAQIECBCoUSAzV7Grcby6ESBAgAABAjkSWLJkSenjPFasWBHb\nbLNNvPa1r422trYczdBUCBBoNQEBqdUqZrwECBAgQCAnAumzDo855pjRQDQ4OBjbb799XHHF\nFTFr1qyczNI0CBBoNQEvsWu1ihkvAQIECBDIgcCiRYvife97X/T29sbq1atLX/39/fHQQw/F\nRz/60RzM0BQIEGhVAQGpVStn3AQIECBAoIUFfvCDH4yeOVpzGikkXXfddbFy5co1m/1MgACB\nhgkISA2jtiMCBAgQIEBgROCZZ56J9JK6csvQ0FA8++yz5e7SRoAAgboLCEh1J7YDAgQIECBA\nYG2B7bbbLtrby/8bMm3atNhss83WXsVtAgQINESg/JGpIbu2EwIECBAgQKCoAm9961tj8803\nj87OsdeLSrf/+Z//OTo6OopKY94ECDRZQEBqcgHsngABAgQIFFGgu7s7vv/978duu+02Ov0p\nU6bESSedFMcee+xomx8IECDQaIGxT9s0eu/2R4AAAQIECBRWIL2M7uqrrx69it2MGTOcOSrs\nb4OJE8iOgICUnVoYCQECBAgQKKTApptuGul9R4sXL46BgYFCGpg0AQLZEfASu+zUwkgIECBA\ngAABAgQIEGiygIDU5ALYPQECBAgQIECAAAEC2REQkLJTCyMhQIAAAQIECBAgQKDJAgJSkwtg\n9wQIECBAgAABAgQIZEdAQMpOLYyEAAECBAgQIECAAIEmCwhITS6A3RMgQIAAAQIECBAgkB0B\nASk7tTASAgQIECBAgAABAgSaLCAgNbkAdk+AAAECBAgQIECAQHYEBKTs1MJICBAgQIAAAQIE\nCBBosoCA1OQC2D0BAgQIECBAgAABAtkREJCyUwsjIUCAAAECBAgQIECgyQICUpMLYPcECBAg\nQIAAAQIECGRHQEDKTi2MhAABAgQIECBAgACBJgsISE0ugN0TIECAAAECBAgQIJAdAQEpO7Uw\nEgIECBAgQIAAAQIEmiwgIDW5AHZPgAABAgQIECBAgEB2BASk7NTCSAgQIECAAAECBAgQaLKA\ngNTkAtg9AQIECBAgQIAAAQLZERCQslMLIyFAgAABAgQIECBAoMkCAlKTC2D3BAgQIECAAAEC\nBAhkR0BAyk4tjIQAAQIECBAgQIAAgSYLCEhNLoDdEyBAgAABAgQIECCQHQEBKTu1MBICBAgQ\nIECAAAECBJosICA1uQB2T4AAAQIECBAgQIBAdgQEpOzUwkgIECBAgAABAgQIEGiygIDU5ALY\nPQECBAgQIECAAAEC2REQkLJTCyMhQIAAAQIECBAgQKDJAgJSkwtg9wQIECBAgAABAgQIZEdA\nQMpOLYyEAAECBAgQIECAAIEmCwhITS6A3RMgQIAAAQIECBAgkB0BASk7tTASAgQIECBAgAAB\nAgSaLCAgNbkAdk+AAAECBAgQIECAQHYEBKTs1MJICBAgQIAAAQIECBBosoCA1OQC2D0BAgQI\nECBAgAABAtkREJCyUwsjIUCAAAECBAgQIECgyQICUpMLYPcECBAgQIAAAQIECGRHQEDKTi2M\nhAABAgQIECBAgACBJgsISE0ugN0TIECAAAECBAgQIJAdAQEpO7UwEgIECBAgQIAAAQIEmizQ\n2eT92z0BAgQIECBAIPMCjzzySDz22GOx5ZZbxnbbbZf58RogAQITFxCQJm5nTQIECBAgQCDn\nAsuXL49jjz02brnllpgyZUr09fXFLrvsEhdddFHMmzcv57M3PQLFFPASu2LW3awJECBAgACB\nGgSOO+64+O///u9Sz97e3hgeHo5f/vKXceSRR5Z+rmETuhAg0GICAlKLFcxwCRAgQIAAgcYI\npJfU3XzzzdHf3z9mhwMDA/HQQw/FPffcM6bdDQIE8iEgIOWjjmZBgAABAgQIbGCBRx99NLq7\nu8tuNbWnAGUhQCB/AgJS/mpqRgQIECBAgMAGENh6663HnT0a2Ww6q7TVVluN3PSdAIEcCQhI\nOSqmqRAgQIAAAQIbTmDbbbeN3XbbLTo7x17TqqOjIxYsWBCvfvWrN9zObIkAgcwICEiZKYWB\nECBAgAABAlkTuOCCC2LHHXeM9vb2mDp1aiksbbPNNvHtb3+71Ja18RoPAQKTFxj7lMjkt2cL\nBAgQIECAAIHcCMydOzeuu+66uPfeeyO9Jyl9DtLuu+8uHOWmwiZCYLyAgDTeRAsBAgQIECBA\nYIzAK1/5ykhfFgIE8i/gJXb5r7EZEiBAgAABAgQIECBQo4CAVCOUbgQIECBAgAABAgQI5F9A\nQMp/jc2QAAECBAgQIECAAIEaBQSkGqF0I0CAAAECBAgQIEAg/wICUv5rbIYECBAgQIAAAQIE\nCNQoICDVCKUbAQIECBAgQIAAAQL5FxCQ8l9jMyRAgAABAgQIECBAoEYBAalGKN0IECBAgAAB\nAgQIEMi/gICU/xqbIQECBAgQIECAAAECNQoISDVC6UaAAAECBAgQIECAQP4FBKT819gMCRAg\nQIAAAQIECBCoUUBAqhFKNwIECBAgQIAAAQIE8i8gIOW/xmZIgAABAgQIECBAgECNAgJSjVC6\nESBAgAABAgQIECCQfwEBKf81NkMCBAgQIECAAAECBGoUEJBqhNKNAAECBAgQIECAAIH8CwhI\n+a+xGRIgQIAAAQIECBAgUKOAgFQjlG4ECBAgQIAAAQIECORfoG34T0v+p/nnGT7//PMxZcqU\nokx30vPs7OyMoaGh0tekN2YDG1Sgvb090kO3QA/fDepXz411dHSUNj84OFjP3dj2BATa2toi\nfaXjmiVbAumYlr4GBgayNTCjKQmk45pjWvZ+GdLxbKQ2/h+orT7pGNPT01O1c2fVHjnqkB7c\nixcvztGM6jeV9Idq/vz50dvbG0uXLq3fjmx5QgIzZsyI/v7+WL169YTWt1L9BObNm1f6R8+x\npn7GE91yd3d3TJ06NZYtWzbRTVivTgIzZ86MadOmxbPPPisk1cl4MptNxzXHtMkI1mfd9I/+\nnDlz4rnnnouVK1fWZyc522oKlLUEJC+xy1nhTYcAAQIECBAgQIAAgYkLCEgTt7MmAQIECBAg\nQIAAAQI5ExCQclZQ0yFAgAABAgQIECBAYOICAtLE7axJgAABAgQIECBAgEDOBASknBXUdAgQ\nIECAAAECBAgQmLiAgDRxO2sSIECAAAECBAgQIJAzAQEpZwU1HQIECBAgQIAAAQIEJi4gIE3c\nzpoECBAgQIAAAQIECORMQEDKWUFNhwABAgQIECBAgACBiQsISBO3syaBXAh897vfjb322ite\n+MIXxl//9V/HpZdemot5mQQBAgQIECBAYCICAtJE1KxDICcC55xzTvzjP/5jPPLII9HX1xdP\nPPFEfPKTn4xTTjklJzM0DQIECBAgQIDA+gkISOvnpTeB3AgsXbo0vvCFL8Tg4OCYOQ0MDMTX\nvva1ePLJJ8e0u0GAAAECBAgQKIKAgFSEKpsjgTIC9913X7S3lz8ETJkyJe65554ya2kiQIAA\nAQIECORboPx/R/mes9kRIPAngZ6enhgaGiprkdrT/RYCBAgQIECAQNEEBKSiVdx8CfxF4JWv\nfGVMnz69rEdHR0fsscceZe/TSIAAAQIECBDIs4CAlOfqmhuBdQh0d3fHV7/61ejq6ip9pa6d\nnZ2RwtFXvvKVmDFjxjrWdhcBAgQIECBAIJ8CnfmcllkRIFCLwD777BM333xzXHzxxfGb3/wm\nttlmmzj66KPjpS99aS2r60OAAAECBAgQyJ2AgJS7kpoQgfUT+Ku/+qv47Gc/u34r6U2AAAEC\nBAgQyKmAl9jltLCmRYAAAQIECBAgQIDA+gsISOtvZg0CBAgQIECAAAECBHIqICDltLCmRYAA\nAQIECBAgQIDA+gsISOtvZg0CBAgQIECAAAECBHIqICDltLCmRYAAgbUF+vv748tf/nLstttu\n8ZKXvCQOOeSQuOuuu9bu5jYBAgQIECi0gIBU6PKbPAECRRJ473vfG2eddVY8+eST8dxzz8Xd\nd98db3vb20qXei+Sg7kSIECAAIF1CQhI69JxHwECBHIicOutt0b6SmeRRpbh4eEYGhqKk046\naaTJdwIECBAgUHgBAanwvwIACBAogsDPfvazaGtrKzvVdEZp8eLFZe/TSIAAAQIEiiYgIBWt\n4uZLgEAhBaZMmRLt7ZUP+V1dXYV0MWkCBAgQILC2QOW/lmv3dJsAAQIEWlZgv/32i76+vnHj\nT6Fp5513jtmzZ4+7TwMBAgQIECiigIBUxKqbMwEChRPYcccd4yMf+UjpLNLIS+3SWaNp06bF\n2WefXTgPEyZAgAABApUEOivdoZ0AAQIE8iXwsY99LHbfffe4/PLLS+852nXXXeOYY46JTTfd\nNF8TNRsCBAgQIDAJAQFpEnhWJUCAQKsJvO51r4v0ZSFAgAABAgTKC3iJXXkXrQQIECBAgAAB\nAgQIFFBAQCpg0U2ZAAECBAgQIECAAIHyAgJSeRetBAgQIECAAAECBAgUUEBAKmDRTZkAAQIE\nCBAgQIAAgfICAlJ5F60ECBAgQIAAAQIECBRQQEAqYNFNmQABAgQIECBAgACB8gICUnkXrQQI\nECBAgAABAgQIFFBAQCpg0U2ZAAECBAgQIECAAIHyAgJSeRetBAgQIECAAAECBAgUUEBAKmDR\nTZkAAQIECBAgQIAAgfICAlJ5F60ECBAgQIAAAQIECBRQQEAqYNFNmQABAgQIECBAgACB8gIC\nUnkXrQQIECBAgAABAgQIFFBAQCpg0U2ZAAECBAgQIECAAIHyAgJSeRetBAgQIECAAAECBAgU\nUEBAKmDRTZkAAQIECBAgQIAAgfICAlJ5F60ECBAgQIAAAQIECBRQQEAqYNFNmQABAgQIECBA\ngACB8gICUnkXrQQIECBAgAABAgQIFFBAQCpg0U2ZAAECBAgQIECAAIHyAgJSeRetBAgQIECA\nAAECBAgUUEBAKmDRTZkAAQIECBAgQIAAgfICAlJ5F60ECBAgQIAAAQIECBRQQEAqYNFNmQAB\nAgQIECBAgACB8gICUnkXrQQIECBAgAABAgQIFFBAQCpg0U2ZAAECBAgQIECAAIHyAgJSeRet\nBAgQIECAAAECBAgUUEBAKmDRTZkAAQIECBDIl8BvfvObOOaYY2LnnXeOvfbaK84+++zo6+vL\n1yTNhkCDBDobtB+7IUCAAAECBAgQqIPAgw8+GG9961tjYGAgBgcHY/HixfGlL30pbr/99rjy\nyiujvd3z4XVgt8kcC3jE5Li4pkaAAAECBAjkX+ATn/hE6WxRCkcjS39/f9x9991x7bXXjjT5\nToBAjQICUo1QuhEgQIAAAQIEsiaQzhr9/Oc/j+Hh4XFDS/fddttt49o1ECCwbgEBad0+7iVA\ngAABAgQIZFYgvXyura2t7PhSe0dHR9n7NBIgUFlAQKps4x4CBAgQIECAQKYFUkDae++9ywah\nFJD222+/TI/f4AhkUUBAymJVjIkAAQIECBAgUKPA6aefHjNmzIiurq7RNTo7O0sXbnjDG94w\n2uYHAgRqE3AVu9qc9CJAgAABAgQIZFJgwYIFccstt8RXv/rVuOOOO2LWrFlx6KGHxjve8Y5M\njtegCGRdQEDKeoWMjwABAgQIECBQRWDTTTeNT3/601V6uZsAgVoEvMSuFiV9CBAgQIAAAQIE\nCBAohICAVIgymyQBAgQIECBAgAABArUICEi1KOlDgAABAgQIECBAgEAhBASkQpTZJAkQIECA\nAAECBAgQqEVAQKpFSR8CBAgQIECAAAECBAohICAVoswmSYAAAQIECBAgQIBALQICUi1K+hAg\nQIAAAQIECBAgUAgBAakQZTZJAgQIECBAgAABAgRqERCQalHShwABAgQIECBAgACBQggISIUo\ns0kSIECAAAECBAgQIFCLgIBUi5I+BAgQIECAAAECBAgUQkBAKkSZTZIAAQIECBAgQIAAgVoE\nBKRalPQhQIAAAQIECBAgQKAQAgJSIcpskgQIECBAgAABAgQI1CIgINWipA8BAgQIECBAgAAB\nAoUQEJAKUWaTJECAAAECBAgQIECgFoHMBKTBwcG45JJLYvny5VXHvWLFivjhD38YV111VTzx\nxBNV++tAgAABAgQIECBAgACBWgQyE5DOO++8OP/88+O5555b57gfffTROPjgg+O73/1uPPDA\nA/He97437rzzznWu404CBAgQIECAAAECBAjUItBZS6d69lm0aFGceeaZce+999a0m89//vNx\n0EEHxQknnBBtbW2ls05nnXVWXH755aXbNW1EJwIECBAgQIAAAQIECJQRaPoZpNNPPz2Gh4fj\njDPOKDO8sU1LliyJhx56qHQGKYWjtLz1rW+Np556KhYuXDi2s1sECBAgQIAAAQIECBBYT4Gm\nn0H6+Mc/HvPnz4/HH3+86tB///vfl/psscUWo33nzp0b3d3d8Yc//CFe9rKXjban9yml8LXm\nss8++8Ree+21ZpOfKwiMBNCurq6YNWtWhV6amyWQ6pK+pkyZ0qwh2G8Fgfb29tLZbI+bCkBN\nbE616ezsdExrYg0q7Todz9Iyffr00pOmlfppb45Aeuw4pjXHfl177ejoKN09derU0v8E6+rr\nvj8LDA0N1UTR9ICUwlGty9NPP136h3DtfwpnzJgRzz777JjNrFy5svQ+pTUbt9xyy3jjG9+4\nZpOfqwikfybSl4UAgfUT2GijjdZvBb0bJuCY1jDq9d5R+kfPkk0Bx7Rs1iWNKp0oSF+W6gJ9\nfX3VO/2pR0v955ueYRoYGBg3sXQFvLUfuOnM0rXXXjumb/rlWbx48Zg2N8oLpGeLkmFvb29N\nVxYsvxWt9RJIv+/psVDrA71e47Dd8QJz5syJ9PhJLwm2ZEtg5KxrtYsBZWvUxRhNOnOUwtEf\n//jHSH/TLdkSSMe1tZ+IztYIizmadMJg5syZpQucrVq1qpgI6znr9AqpTTbZpOpaLRWQ0oTS\ngTOdHVozEKVLg2+++eZjJpueIdx2223HtKV+zz///Jg2N8oLpH/w0pJORZYLpeXX0toogfS+\nPbVplPbE9uNxMzG3eq6VjmvpsaM29VSe2LZHXvaS/sarz8QM672WutRbeP23P3I23OOmdruR\nlyVWW6PpF2moNsA1799qq61KL/d68MEHR5vTRRvSgXXN9yWN3ukHAgQIECBAgAABAgQIrIdA\n5gPSbbfdFtdff31pSukNguk9RBdddFHpdOLq1atLn520//77x7x589Zj2roSIECAAAECBAgQ\nIEBgvEDmA9KNN94YV1999ejIjz322NIb0Q488MA45JBDSmeUjj/++NH7/UCAAAECBAgQIECA\nAIGJCrT96fXYwxNduZnrpfcTpdcRTps2reZheA9SzVSlN5mnKwymN/0tXbq09hX1bIhAunJj\nf39/pLOolmwJpLPZ6b0u6UOwLdkSSBfqSRcCWLZsWbYGZjSlN5qnv+fpQkre65K9X4h0XHOR\nq+zVpaenJ9IFNNIxLb0/31JdIGWHTTfdtGrHlrpIw5qzSVftsBAgQIAAAQIECBAgQGBDCmT+\nJXYbcrK2RYAAAQIECBAgQIAAgXUJCEjr0nEfAQIECBAgQIAAAQKFEhCQClVukyVAgAABAgQI\nECBAYF0CAtK6dNxHgAABAgQIECBAgEChBASkQpXbZAkQIECAAAECBAgQWJeAgLQuHfcRIECA\nAAECBAgQIFAoAQGpUOU2WQIECBAgQIAAAQIE1iUgIK1Lx30ECBAgQIAAAQIECBRKQEAqVLlN\nlgABAgQIECBAgACBdQkISOvScR8BAgQIECBAgAABAoUS2CABafny5fHLX/4yhoeHC4VnsgQI\nECBAgAABAgQI5Eug5oD0wAMPxEknnRSf+9znRgUGBwfj7/7u72KTTTaJnXfeObbccsu4+OKL\nR+/3AwECBAgQIECAAAECBFpJoLOWwf7mN7+JvffeO5YuXRpHH3306Cqf+MQn4oorrijd98Y3\nvjG+//3vxzHHHBNbb711vOENbxjt5wcCBAgQIECAAAECBAi0gkBNAemwww6Ljo6OuOSSS+KI\nI44ozeupp56KL37xi7HddtvFj3/84+jp6YkTTjihdCbpYx/7WNxzzz2tMH9jJECAAAECBAgQ\nIECAwKhA1ZfYpbNGv/jFL+LQQw8tnT3q7PxzprrmmmtiaGioFIpSOErLjBkzIoWpX/3qV9Hb\n2zu6Ez8QIECAAAECBAgQIECgFQSqBqR08YW0vOlNbxozn5tvvrl0e7/99hvT/pKXvCT6+voi\nvSzPQoAAAQIECBAgQIAAgVYSqBqQ+vv7S/NJF2IYWdLV6n7yk5/EC17wgth2221Hmkvff/e7\n35W+b7XVVmPa3SBAgAABAgQIECBAgEDWBaoGpHR1urSMnElKP991112xePHiSBdmWHu54447\nIoWj2bNnr32X2wQIECBAgAABAgQIEMi0QNWLNKQzR7vsskucdtppMW/evHj5y18eH/3oR0uT\nOuqoo8ZM7lvf+lb86Ec/Kl36e8wdbhAgQIAAAQIECBAgQKAFBKoGpDSHq666Kl71qleVLsAw\nMqd0ie/Xvva1pZvpogwf+chH4rbbbosXvehFce655450850AAQIECBAgQIAAAQItI1BTQEqh\n57777it9ztHDDz8c++67b/zt3/7t6CSffvrp0pXu0hXsPv3pT8fGG288ep8fCBAgQIAAAQIE\nCBAg0CoCNQWkNJkFCxbEiSeeWHZe6UxSek9SV1dX2fs1EiBAgAABAgQIECBAoBUEag5I65rM\nyOcgrauP+wgQIECAAAECBAgQIJB1gZoDUrq098KFC+Oee+6JTTfdNPbYY4+YNWtW1udnfAQI\nECBAgAABAgQIEKhZoKaAtGLFijj88MPj2muvHd1wuqLdBRdcEAceeOBomx8IECBAgAABAgQI\nECDQygJVPwcpTe5f//VfS+Fo7733jjPPPDMOPfTQWLp0abzrXe+KJUuWtPL8jZ0AAQIECBAg\nQIAAAQKjAjWdQfr2t78du+22W9x0003R2fnnVa655prS2aMrrrgiPvjBD45u0A8ECBAgQIAA\nAQIECBBoVYGqZ5DSy+ueeeaZeMtb3jIajtJkDzjggNJV6x599NFWnbtxEyBAgAABAgQIECBA\nYIxA1YC0bNmy0gqzZ88eu2J7e6T3IT355JNj2t0gQIAAAQIECBAgQIBAqwpUDUiDg4OluXV0\ndIybY2obGBgY166BAAECBAgQIECAAAECrShQNSC14qSMmQABAgQIECBAgAABAhMRqOkiDWnD\nixYtiocffnjMPtLZo/QepbXbU6eXvOQlY/q6QYAAAQIECBAgQIAAgawL1ByQTj311Ehfay9P\nP/10bLfddms3R/pgWQsBAgQIECBAgAABAgRaSaBqQJoxY4bLeLdSRY2VAAECBAgQIECAAIEJ\nC1QNSBtvvHGce+65E96BFQkQIECAAAECBAgQINAqAlUDUrmJrF69Ou6999548MEHIwWo7bff\nPnbYYYdyXbURIECAAAECBAgQIECgZQTWKyBdd9118elPfzruv//+6O/vHzPJl7/85fH1r389\nXvOa14xpd4MAAQIECBAgQIAAAQKtIlBzQPrWt74V73nPe2KjjTaKffbZJ175ylfGtttuW/qg\n2Iceeii+//3vx3777Rf/9V//Fa973etaZf7GSYAAAQIECBAgQIAAgVGBmgLSN7/5zXj3u98d\nO+64Y1xzzTXxghe8YHQDIz+kS32nPgcccEBcf/318Td/8zcjd/lOgAABAgQIECBAgACBlhCo\n+kGxQ0ND8alPfSpe+tKXxk9/+tOy4SjNNH3u0fe+971IV707+eSTW2LyBkmAAAECBAgQIECA\nAIE1BaoGpF/96lfx+OOPx6GHHhozZ85cc91xP2+22WZxzDHHxC233BLLly8fd78GAgQIECBA\ngAABAgQIZFmgakB67LHHSuN/4xvfWNM8XvGKV5T6pVBlIUCAAAECBAgQIECAQCsJVA1Im2yy\nSWk+vb29Nc1r5MxRupiDhQABAgQIECBAgAABAq0kUDUg7bTTTtHW1lZ6/1EtE0vvU5o6dWrF\n9yrVsg19CBAgQIAAAQIECBAg0AyBqgEpXXRhr732in/7t3+LkZfbVRrorbfeGumKd0ceeWR0\ndXVV6qadAAECBAgQIECAAAECmRSoGpDSqC+88MLS4PfYY49In4e09jIwMBBnn312HHzwwbH9\n9tu7it3aQG4TIECAAAECBAgQINASAjUFpPSBsN/5zndieHg4jjrqqJg+fXq8/OUvL33mUfrA\n2NmzZ8eJJ55Y+pyk22+/PbbYYouWmLxBEiBAgAABAgQIECBAYE2Bmj4oNq1w4IEHxv/8z//E\naaedFjfddFOkD4Z94IEHYv78+fGmN70p9txzzzjuuONK7z9acwd+JkCAAAECBAgQIECAQKsI\n1ByQ0oTS5yCdccYZo3N79tlnY86cOaO3/UCAAAECBAgQIECAAIFWFqjpJXaVJigcVZLRToAA\nAQIECBAgQIBAKwpMKiC14oSNmQABAgQIECBAgAABApUEBKRKMtoJECBAgAABAgQIECicgIBU\nuJKbMAECBAgQIECAAAEClQQEpEoy2gkQIECAAAECBAgQKJyAgFS4kpswAQIECBAgQIAAAQKV\nBASkSjLaCRAgQIAAAQIECBAonICAVLiSmzABAgQIECBAgAABApUEBKRKMtoJECBAgAABAgQI\nECicgIBUuJKbMAECBAgQIECAAAEClQQEpEoy2gkQIECAAAECBAgQKJyAgFS4kpswAQIECBAg\nQIAAAQKVBASkSjLaCRAgQIAAAQIECBAonICAVLiSmzABAgQIECBAgAABApUEBKRKMtoJECBA\ngAABAgQIECicgIBUuJKbMAECBAgQIECAAAEClQQ6K92hnQABAgQIEKgssGjRorj//vtj5syZ\nseuuu0ZXV1flzu4hQIAAgZYREJBaplQGSoAAAQJZEBgeHo7PfOYzcf7550d3d3cMDg7GrFmz\n4oILLojdd989C0M0BgIECBCYhICX2E0Cz6oECBAgUDyB8847Ly6++OJIQam3tzcGBgZiyZIl\ncfjhh0c6q2QhQIAAgdYWEJBau35GT4AAAQINFjj33HOjv79/3F7TmaTLL798XLsGAgQIEGgt\nAQGptepltAQIECDQRIHVq1fH0qVLy46gr68vHn300bL3aSRAgACB1hEQkFqnVkZKgAABAk0W\n6OnpKb3fqNww0vuRXvjCF5a7SxsBAgQItJCAgNRCxTJUAgQIEGi+wLHHHlv2inVtbW1x2GGH\nNX+ARkCAAAECkxIQkCbFZ2UCBAgQKJrA8ccfX7ogQwpE6YxSurz37Nmz47LLLovNN9+8aBzm\nS4AAgdwJuMx37kpqQgQIECBQT4H29vY4/fTT48Mf/nDcd999MWPGjHj1q19dCkv13K9tEyBA\ngEBjBASkxjjbCwECBAjkTGCrrbaK9GUhQIAAgXwJeIldvuppNgQIECBAgAABAgQITEJAQJoE\nnlUJECBAgAABAgQIEMiXgICUr3qaDQECBAgQIECAAAECkxAQkCaBZ1UCBAgQIECAAAECBPIl\nICDlq55mQ4AAAQIECBAgQIDAJAQEpEngWZUAAQIECBAgQIAAgXwJFOoy3+lD/aZNm5avCtZp\nNskqLZ2dnczqZDyZzaYPpkyfxdLR0TGZzVi3DgIjjx3HmjrgTnKT6fHimDZJxDqtno5paZk6\ndWoMDQ3VaS82O1GB9PfGMW2ievVbLx3P0jJlypQY+dtTv73lY8vDw8M1TaRQASmJ1ApTk15B\nOjHLbqHVRm2yK5DdkXncZK82IzVJ30d+zt4oiz0idclu/T1uaq9Nrb/HhQpICWXlypW1Kxa4\nZ3q2aObMmTEwMMAsg78H6Znw/v7+WL16dQZHV+whpWdZ0zN5jjXZ+z3o7u5Wm+yVpTSi9Ex4\nehY8HdPS3x1LtgTScc0xLVs1SaPp6emJjTbaKPr6+tSnxvLU+sob70GqEVQ3AgQIECBAgAAB\nAgTyLyAg5b/GZkiAAAECBAgQIECAQI0CAlKNULoRIECAAAECBAgQIJB/AQEp/zU2QwIECBAg\nQIAAAQIEahQQkGqE0o0AAQIECBAgQIAAgfwLCEj5r7EZEiBAgAABAgQIECBQo4CAVCOUbgQI\nECBAgAABAgQI5F9AQMp/jc2QAAECBAgQIECAAIEaBQSkGqF0I0CAAAECBAgQIEAg/wICUv5r\nbIYECBAgQIAAAQIECNQoICDVCKUbAQIECBAgQIAAAQL5FxCQ8l9jMyRAgAABAgQIECBAoEYB\nAalGKN0IECBAgAABAgQIEMi/gICU/xqbIQECBAgQIECAAAECNQoISDVC6UaAAAECBAgQIECA\nQP4FBKT819gMCRAgQIAAAQIECBCoUUBAqhFKNwIECBAgQIAAAQIE8i8gIOW/xmZIgAABAgQI\nECBAgECNAgJSjVC6ESBAgAABAgQIECCQfwEBKf81NkMCBAgQIECAAAECBGoUEJBqhNKNAAEC\nBAgQIECAAIH8CwhI+a+xGRIgQIAAAQIECBAgUKOAgFQjlG4ECBAgQIAAAQIECORfQEDKf43N\nkAABAgQIECBAgACBGgU6a+ynGwECExD42c9+FldeeWUsXrw4dt1113jXu94VG2+88QS2ZBUC\nBAgQIECAAIFGCAhIjVC2j0IKnHXWWXHmmWdGW1tbDA0NxU9/+tM4//zz45prroltttmmkCYm\nTYAAAQIECBDIuoCX2GW9QsbXkgILFy4shaPh4eFSOEqT6Ovri2XLlsWJJ57YknMyaAIECBAg\nQIBAEQQEpCJU2RwbLvCjH/0ouru7x+03nUm6++67Y8WKFePu00CAAAECBAgQINB8AQGp+TUw\nghwKrFq1KgYHByvObPXq1RXvcwcBAgQIECBAgEDzBASk5tnbc44FXv3qV1ec3RZbbBHz5s2r\neL87CBAgQIAAAQIEmicgIDXP3p5zLPD6178+Ukjq6uoaM8v29vY4/fTTx7S5QYAAAQIECBAg\nkB0BASk7tTCSHAmkK9d961vfig984AMxd+7c0vuRdtppp7j88stj3333zdFMTYUAAQIECBAg\nkC8Bl/nOVz3NJkMCU6ZMiX/5l38pfWVoWIZCgAABAgQIECCwDgFnkNaB4y4CBAgQIECAAAEC\nBIolICAVq95mS4AAAQIECBAgQIDAOgS8xG4dOO4iQIAAAQIECBAolsDAwEDcc889sWTJkthh\nhx1im222KRaA2YaA5JeAAAECBAgQIECAwJ8EHnjggTj66KPjmWeeic7OzkifW3jIIYfEl7/8\n5bIfAA8tnwICUj7ralYECBAgQIAAAQLrIbBixYp45zvfGcuWLYvh4eFIZ5LScu2118acOXPi\ntNNOW4+t6drKAt6D1MrVM3YCBAgQIECAAIENIvCDH/wgVq1aVQpHa26wv7+/9NEd6WySpRgC\nAlIx6myWBAgQIECAAAEC6xD43e9+F0NDQ2V7pJCUXnZnKYaAl9gVo87rNcv0psQLL7wwfv7z\nn8fs2bPjoIMOigMOOGC9tqEzAQIECBAgQKCVBLbeeutoby9/7qCrqyvmzZvXStMx1kkICEiT\nwMvjqunZkze/+c3x3HPPRV9fX2mK6bW3RxxxRJxxxhl5nLI5ESBAgAABAgTi4IMPLr3PKP3/\nk96DNLKkcJQu3JA+AN5SDIHyMbkYczfLMgInnXRS6c2JI+EodRkcHIzLLrss7rjjjjJraCJA\ngAABAgQItL7A9OnT47vf/W5svvnmpSvY9fT0lCZ14IEHxv/7f/+v9SdoBjULOINUM1X+O6ar\ntdx+++1lX3/b1tYWP/rRj2KPPfbIP4QZEiBAgAABAoUUSJ97dOedd8a9995b+hykl73sZfGC\nF7ygkBZFnrSAVOTqrzX3dKao0psTU3tvb+9aa7hJgAABAgQIEMiXQPr8o9133z1fkzKb9RLw\nErv14sp35/Ta2vRMSbklHSz23HPPcndpI0CAAAECBAgQIJAbAQEpN6XcMBP5/Oc/X3rd7ZpX\ncUlvTtxll13iLW95y4bZia0QIECAAAECBAgQyKiAgJTRwjRrWK961avimmuuib322itmzZoV\nW265ZXzwgx+Myy+/vOKlL5s1VvslQIAAAQIECBAgsKEFvAdpQ4vmYHs77bRTXHnllTF//vzS\nJ0ovXbo0B7MyBQIECBAgQIAAAQLVBZxBqm6kBwECBAgQIECAAAECBREQkApSaNMkQIAAAQIE\nCBAgQKC6gIBU3UgPAgQIECBAgAABAgQKIiAgFaTQpkmAAAECBAgQIECAQHUBAam6kR4ECBAg\nQIAAAQIECBREQEAqSKFNkwABAgQIECBAgACB6gICUnUjPQgQIECAAAECBAgQKIiAgFSQQpsm\nAQIECBAgQIAAAQLVBQSk6kZ6ECBAgAABAgQIECBQEAEBqSCFNk0CBAgQIECAAAECBKoLCEjV\njfQgQIAAAQIECBAgQKAgAgJSQQptmgQIECBAgAABAgQIVBcQkKob6UGAAAECBAgQIECAQEEE\nBKSCFPoalScAADNESURBVNo0CRAgQIAAAQIECBCoLiAgVTfSgwABAgQIECBAgACBgggISAUp\ntGkSIECAAAECBAgQIFBdQECqbqQHAQIECBAgQIAAAQIFERCQClJo0yRAgAABAgQIECBAoLqA\ngFTdSA8CBAgQIECAAAECBAoiICAVpNCmSYAAAQIECBAgQIBAdQEBqbqRHgQIECBAgAABAgQI\nFERAQCpIoU2TAAECBAgQIECAAIHqAgJSdSM9CBAgQIAAAQIECBAoiICAVJBCmyYBAgQIECBA\ngAABAtUFBKTqRnoQIECAAAECBAgQIFAQAQGpIIU2TQIECBAgQIAAAQIEqgsISNWN9CBAgAAB\nAgQIECBAoCACnQWZp2kSIECAQIsILFmyJK644op49NFHY6uttop3vvOdsfnmm7fI6A2TAAEC\nBFpdQEBq9QoaPwECBHIkcP/998c73vGO6O/vj97e3uju7o4vf/nLcemll8Zee+2Vo5maCgEC\nBAhkVcBL7LJaGeMiQIBAwQQGBwfjPe95Tzz//POlcJSm39fXV/r5fe97X6xcubJgIqZLgAAB\nAs0QEJCaoW6fBAgQIDBOIJ09Wrx4cQwPD4+7b/Xq1XHHHXeMa9dAgAABAgQ2tICAtKFFbY8A\nAQIEJiSwfPny6OjoKLtue3t7pPstBAgQIECg3gICUr2FbZ8AAQIEahLYcccdY2BgoGzf9H6k\nnXfeuex9GgkQIECAwIYUyERAeuKJJ+Lyyy+PH//4x/Hcc89Vnd/DDz8cl112Wfzwhz+MZ599\ntmp/HQgQIEAg+wKbbLJJfOADH4iurq4xg02304UbXvSiF41pd4MAAQIECNRDoOkBKV2Z6Kij\njoqFCxfGlVdeGccdd9w6Q8/VV18d6c26t9xySylQHXroofHggw/Ww8Y2CRAgQKDBAv/6r/8a\nH/vYx2LWrFmlPU+bNi0+9KEPxRe/+MUGj8TuCBAgQKCoAk29zHc6c3TRRRfF2WefHa94xStK\nL6049thjS59/kb6vvTzzzDNx7rnnxt///d/H+9///tLdV111VXzyk58snVFKf0gtBAgQINC6\nAm1tbfHBD36w9JWuZue43rq1NHICBAi0qkBTzyDdddddscUWW5TCUQLs7OyM/fffP2644Yay\nng899FDpszEOPPDA0fv33Xff0hmne++9d7TNDwQIECDQ+gLCUevX0AwIECDQigJNPYP09NNP\nx5ZbbjnGLQWmdKZoaGgo0lWL1l7Ss4trXuUofZhg6vvkk0+O6Zraf/WrX41pSy/ZGHnZxpg7\n3BgnMGKfvq/9foBxnTU0XCDVJT0O1Kbh9FV3mI5RaVGbqlQN75CehHNMazh7TTsc+ZuTajTy\nGKppRZ0aJuCY1jDqmnc08v+w/wdqJqv5+NLUgPT73/8+Zs6cOWZWM2bMKAWeZcuWxZw5c8bc\nt/3225f+6UgXdEgvwUgH0e9973ulPmt/gOAf//jHOPzww8esf8IJJ5TWG9PoxjoFpkyZEunL\nQoDA+gmkCw5YsinQ09OTzYEZ1bi/+0iyI+CYlp1arD2S6dOnR/qyVBdIHz5ey9LUgJSejVj7\nkq4jtzfaaKNx408Pzo985CNx1llnxU033VR6Bn2bbbaJBQsWxNSpU8f0Ty/NSJ/Ivuayww47\n1HSVvDXXKerPKXwmw1SP9AGNlmwJdHd3l55IGHm8ZGt0xR5NOnalx096/4wlWwLpWdZ0hiJd\nMtySLYH0RFz6nyA92ZleFWLJlkA6rq39RHS2RljM0aTjWXrCJx3T0iunLNUF0geRp/+hqi1N\nDUgp8Dz22GNjxpg+CDCdOap01uLggw+OXXbZpfTyua233jpe9rKXxSGHHBJz584ds52UpD/+\n8Y+PaUvbXrFixZg2N8oLpJc7pICUHnDMyhs1szWdaU21EV6bWYXy+05/rNLjx+OmvE8zW9Mf\nxfRkmto0swrl952eVEgBKT2x4Imf8kbNbE3HNY+bZlag/L5TXdJX+l9AgC1vtHZreqIs/Q9V\nbRn/Jp9qa2zA+9PZn1//+tdjDobpkt1rvy9pZJfpF+Diiy8unUZ8y1veEjvttFP89re/jfRy\nvPSzhQABAgQIECBAgAABApMRaGpASlegS0v60Nd0Sv2RRx6J6667rvS5SCOTuu222+L6668v\n3UwpOV2t7sILLyydTkwfEptebnfEEUfEZpttNrKK7wQIECBAgAABAgQIEJiQQFNfYpdeRnfK\nKafEySefXApJ6aUPb3vb22KPPfYYncyNN94YTz31VLz5zW8utaUPDDznnHMiXeo7nY7fe++9\nSx8cO7qCHwonkF5Pml6eYSFAgAABAgQIECAwWYG2P/1zOTzZjWyI9RctWhTz5s0re2nvcttf\nunRp6aV26Q1qtS7pPUjeOF2bVnoPxfz582PVqlWRrLO2PP7446UPCE5nGNOv8Gte85o47bTT\n4sUvfnHWhlqX8XgPUl1YN8hGR45j6ZhmyZbAyHuQ0suyLdkSSFe0Te97Xbx48ZiX3WdrlMUd\nTTqupdpYsiWQXlmV3refjmneg1RbbdJ7kDbddNOqnZv6Ers1R5f+GR/5HIQ12yv9PHv27NLV\niCrdrz2/Aukfz/SBwrfeemvpD+ng4GDccccdpbOMKThZCBAgQIAAAQIECExUIDMBaaITsF7x\nBL7yla+UnilJwWhkSe9hS9e2P/PMM0eafCdAgAABAgQIECCw3gIC0nqTWaHZAulsUbnr/adL\nw955553NHp79EyBAgAABAgQItLCAgNTCxSvq0Nd1/fr0GnYLAQIECBAgQIAAgYkKCEgTlbNe\n0wQOPfTQsu8/S1c1fMc73tG0cdkxAQIECBAgQIBA6wsISK1fw8LN4Mgjj4zXve51pZA0cnnv\nFI522223OOaYYwrnYcIECBAgQIAAAQIbTqD2a2RvuH3aEoFJCaSrHV588cWlDxC+4YYbSh8y\nnALTQQcdtF5XQpzUIKxMgAABAgQIECCQSwEBKZdlzf+k0pmjAw44oPSV/9maIQECBAgQIECA\nQKMEvMSuUdL2Q4AAAQIECBAgQIBA5gUEpMyXyAAJECBAgAABAgQIEGiUgIDUKGn7IUCAAAEC\nBAgQIEAg8wICUuZLZIAECBAgQIAAAQIECDRKQEBqlLT9ECBAgAABAgQIECCQeQEBKfMlMkAC\nBAgQIECAAAECBBolICA1Stp+CBAgQIAAAQIECBDIvICAlPkSGSABAgQIECBAgAABAo0SEJAa\nJW0/BAgQIECAAAECBAhkXkBAynyJDJAAAQIECBAgQIAAgUYJCEiNkrYfAgQIECBAgAABAgQy\nLyAgZb5EBkiAAAECBAgQIECAQKMEBKRGSdsPAQIECBAgQIAAAQKZFxCQMl8iAyRAgAABAgQI\nECBAoFECAlKjpO2HAAECBAgQIECAAIHMCwhImS+RARIgQIAAAQIECBAg0CgBAalR0vZDgAAB\nAgQIECBAgEDmBQSkzJfIAAkQIECAAAECBAgQaJSAgNQoafshQIAAAQIECBAgQCDzAgJS5ktk\ngAQIECBAgAABAgQINEpAQGqUtP0QIECAAAECBAgQIJB5AQEp8yUyQAIECBAgQIAAAQIEGiUg\nIDVK2n4IECBAgAABAgQIEMi8gICU+RIZIAECBAgQIECAAAECjRIQkBolbT8ECBAgQIAAAQIE\nCGReQEDKfIkMkAABAgQIECBAgACBRgkISI2Sth8CBAgQIECAAAECBDIvICBlvkQGSIAAAQIE\nCBAgQIBAowQEpEZJ2w8BAgQIECBAgAABApkXEJAyXyIDJECAAAECBAgQIECgUQICUqOk7YcA\nAQIECBAgQIAAgcwLCEiZL5EBEiBAgAABAgQIECDQKAEBqVHS9kOAAAECBAgQIECAQOYFBKTM\nl8gACRAgQIAAAQIECBBolICA1Chp+yFAgAABAgQIECBAIPMCAlLmS2SABAgQIECAAAECBAg0\nSkBAapS0/RAgQIAAAQIECBAgkHkBASnzJTJAAgQIECBAgAABAgQaJSAgNUrafggQIECAAAEC\nBAgQyLyAgJT5EhkgAQIECBAgQIAAAQKNEhCQGiVtPwQIECBAgAABAgQIZF5AQMp8iQyQAAEC\nBAgQIECAAIFGCQhIjZK2HwIECBAgQIAAAQIEMi8gIGW+RAZIgAABAgQIECBAgECjBASkRknb\nDwECBAgQIECAAAECmRcQkDJfIgMkQIAAAQIECBAgQKBRAgJSo6TthwABAgQIECBAgACBzAsI\nSJkvkQESIECAAAECBAgQINAoAQGpUdL2Q4AAAQIECBAgQIBA5gUEpMyXyAAJECBAgAABAgQI\nEGiUgIDUKGn7IUCAAAECBAgQIEAg8wICUuZLZIAECBAgQIAAAQIECDRKQEBqlLT9ECBAgAAB\nAgQIECCQeQEBKfMlMkACBAgQIECAAAECBBolICA1Stp+CBAgQIAAAQIECBDIvICAlPkSGSAB\nAgQIECBAgAABAo0SEJAaJW0/BAgQIECAAAECBAhkXkBAynyJDJAAAQIECBAgQIAAgUYJCEiN\nkrYfAgQIECBAgAABAgQyLyAgZb5EBkiAAAECBAgQIECAQKMEBKRGSdsPAQIECBAgQIAAAQKZ\nFxCQMl8iAyRAgAABAgQIECBAoFECAlKjpO2HAAECBAgQIECAAIHMCwhImS+RARIgQIAAAQIE\nCBAg0CgBAalR0vZDgAABAgQIECBAgEDmBQSkzJfIAAkQIECAAAECBAgQaJSAgNQoafshQIAA\nAQIECBAgQCDzAgJS5ktkgAQIECBAgAABAgQINEpAQGqUtP0QIECAAAECBAgQIJB5AQEp8yUy\nQAIECBAgQIAAAQIEGiUgIDVK2n4IECBAgAABAgQIEMi8gICU+RIZIAECBAgQIECAAAECjRIQ\nkBolbT8ECBAgQIAAAQIECGReQEDKfIkMkAABAgQIECBAgACBRgl0NmpHWdlPe7tMWEstRpza\n2tpi5Oda1tOnMQIjdVGbxnhPZC9qMxG1+q6TajLy2Knvnmx9fQVSXdKSauSxs7569e/vcVN/\n44nsweNm/dVGzKqt2Tb8p6Vap7zc//zzz0dXV1deplP3eXR3d8fQ0FAMDAzUfV92sH4CHR0d\nkR66qT6WbAmMHGP6+/uzNTCjGQ1Hg4ODNDImkI5p6Ss9bgr0b0nGqlB5OOm45phW2adZ96Qn\nEzo7O0v/p/l/oLYqpOP/1KlTq3Yu1BmkhLJ8+fKqKDr8+Vm8+fPnR29vbyxduhRJxgRmzJhR\n+mO1evXqjI3McObNm1d6BnzJkiUwMiaQnvRJfxiXLVuWsZEZzsyZM2PatGmlvzeelMve70M6\nrjmmZa8uPT09MWfOnEgnAFauXJm9AWZwROmJmFoCktebZbB4hkSAAAECBAgQIECAQHMEBKTm\nuNsrAQIECBAgQIAAAQIZFBCQMlgUQyJAgAABAgQIECBAoDkCAlJz3O2VAAECBAgQIECAAIEM\nCghIGSyKIREgQIAAAQIECBAg0BwBAak57vZKgAABAgQIECBAgEAGBQSkDBbFkAgQIECAAAEC\nBAgQaI6AgNQcd3slQIAAAQIECBAgQCCDAgJSBotiSAQIECBAgAABAgQINEdAQGqOu70SIECA\nAAECBAgQIJBBAQEpg0UxJAIECBAgQIAAAQIEmiMgIDXH3V4JECBAgAABAgQIEMiggICUwaIY\nEgECBAgQIECAAAECzREQkJrjbq8ECBAgQIAAAQIECGRQQEDKYFEMiQABAgQIECBAgACB5ggI\nSM1xt1cCBAgQIECAAAECBDIoICBlsCiGRIAAAQIECBAgQIBAcwQEpOa42ysBAgQIECBAgAAB\nAhkUEJAyWBRDIkCAAAECBAgQIECgOQICUnPc7ZUAAQIECBAgQIAAgQwKCEgZLIohESBAgAAB\nAgQIECDQHAEBqTnu9kqAAAECBAgQIECAQAYFBKQMFsWQCBAgQIAAAQIECBBojoCA1Bx3eyVA\ngAABAgQIECBAIIMCAlIGi2JIBAgQIECAAAECBAg0R0BAao67vRIgQIAAAQIECBAgkEEBASmD\nRTEkAgQIECBAgAABAgSaIyAgNcfdXgkQIECAAAECBAgQyKCAgJTBohgSAQIECBAgQCCvAitW\nrIilS5fmdXrmlQMBASkHRTQFAgQIECBAgEDWBR566KHYf//9Y7vttosddtghXvva18Zdd92V\n9WEbXwEFBKQCFt2UCRAgQIAAAQKNFPi///u/OPDAA+OBBx4Y3e1vf/vbOPTQQ+PBBx8cbfMD\ngSwICEhZqIIxECBAgAABAgRyLHDeeedFX19fDA0NjZlluv2FL3xhTJsbBJotICA1uwL2T4AA\nAQIECBDIucDdd98dAwMD42aZAtL9998/rl0DgWYKCEjN1LdvAgQIECBAgEABBObOnVtxlrNm\nzap4nzsINENAQGqGun0SIECAAAECBAokcPjhh0dHR8e4GXd1dcWRRx45rl0DgWYKCEjN1Ldv\nAgQIECBAgEABBA4++OBSEGpvb48Uijo7O0uBad99941/+Id/KICAKbaSQGcrDdZYCRAgQIAA\nAQIEWlPg9NNPj7e//e3xk5/8JAYHB2PvvfcuXeq7NWdj1HkWEJDyXF1zI0CAAAECBAhkSGC3\n3XaL9GUhkGUBL7HLcnWMjQABAgQIECBAgACBhgo4g9RQbjsjQIAAAQIECBAgMHmB4eHhWLp0\naaTvlg0r4AzShvW0NQIECBAgQIAAAQJ1E0iB6JxzzokXvvCFMWfOnNhyyy3jlFNOif7+/rrt\ns2gbdgapaBU3XwIECBAgQIAAgZYVOPXUU+P8888fDUSrVq0q3X7qqafiq1/9asvOK0sDdwYp\nS9UwFgIECBAgQIAAAQIVBJYsWRJf//rXR8PRSLd09ugHP/hBPPzwwyNNvk9CQECaBJ5VCRAg\nQIAAAQIECDRKYOHChWU/cDftv6enJ+6///5GDSXX+xGQcl1ekyNAgAABAgQIEMiLwKxZs0qf\nIVVuPumzpdL9lskLCEiTN7QFAgQIECBAgAABAnUX2HHHHWOLLbaItra2cftKZ5D22muvce0a\n1l9AQFp/M2sQIECAAAECBAgQaLhAe3t7XHjhhTFjxoyYMmVKKSil7+nrggsuiI022qjhY8rj\nDl3FLo9VNScCBAgQIECAAIFcCqSzSHfeeWf853/+Zzz55JMxb968OPjgg2P+/Pm5nG8zJiUg\nNUPdPgkQIECAAAECBAhMUGD27Nlx7LHHlj4HadmyZbFy5coJbslq5QS8xK6cijYCBAgQIECA\nAAECBAopICAVsuwmTYAAAQIECBAgQIBAOQEBqZyKNgIECBAgQIAAAQIECikgIBWy7CZNgAAB\nAgQIECBAgEA5AQGpnIo2AgQIECBAgAABAgQKKSAgFbLsJk2AAAECBAgQIECAQDkBAamcijYC\nBAgQIECAAAECBAopICAVsuwmTYAAAQIECBAgQIBAOQEBqZyKNgIECBAgQIAAAQIECikgIBWy\n7CZNgAABAgQIECBAgEA5AQGpnIo2AgQIECBAgAABAgQKKSAgFbLsJk2AAAECBAgQIECAQDkB\nAamcijYCBAgQIECAAAECBAopICAVsuwmTYAAAQIECBAgQIBAOQEBqZyKNgIECBAgQIAAAQIE\nCikgIBWy7CZNgAABAgQIECBAgEA5AQGpnIo2AgQIECBAgAABAgQKKSAgFbLsJk2AAAECBAgQ\nIECAQDkBAamcijYCBAgQIECAAAECBAopICAVsuwmTYAAAQIECBAgQIBAOQEBqZyKNgIECBAg\nQIAAAQIECikgIBWy7CZNgAABAgQIECBAgEA5AQGpnIo2AgQIECBAgAABAgQKKSAgFbLsJk2A\nAAECBAgQIECAQDkBAamcijYCBAgQIECAAAECBAopICAVsuwmTYAAAQIECBAgQIBAOQEBqZyK\nNgIECBAgQIAAAQIECikgIBWy7CZNgAABAgQIECBAgEA5AQGpnIo2AgQIECBAgAABAgQKKSAg\nFbLsJk2AAAECBAgQIECAQDkBAamcijYCBAgQIECAAAECBAopICAVsuwmTYAAAQIECBAgQIBA\nOQEBqZyKNgIECBAgQIAAAQIECikgIBWy7CZNgAABAgQIECBAgEA5gc5yjY1ue+KJJ+KOO+6I\njTfeOPbYY4+YPn36OoewevXquP3222NgYCD22Wef2GijjdbZ350ECBAgQIAAAQIECBCoRaDp\nZ5AuvfTSOOqoo2LhwoVx5ZVXxnHHHRfPPvtsxbHffPPNcdBBB8V1110Xt9xySxxyyCFxzTXX\nVOzvDgIECBAgQIAAAQIECNQq0NSAlM4cXXTRRXH22WfHZz/72fja174WU6ZMiSuuuKLi+L/x\njW/EvvvuG2eddVacccYZ8ba3vS3OPffcGB4erriOOwgQIECAAAECBAgQIFCLQFMD0l133RVb\nbLFFvOIVryiNtbOzM/bff/+44YYbKo69r68vNt1009H7t9566+jv7y+93G600Q8ECBAgQIAA\nAQIECBCYgEBT34P09NNPx5Zbbjlm2CkwPfPMMzE0NBTt7ePz22GHHRaXXXZZ6f1KPT098c1v\nfrN0Fqmrq2vMdpYsWRJHHnnkmLb0Ur60vqV2gXRGb968ebWvoGdDBNJjI501nTFjRkP2Zye1\nC3R0dJQ6e9zUbtaonm1tbZG+uru7G7VL+6lRYOTv/Zw5c2pcQ7dGCqTjmmNaI8Vr21c6nqUl\nvXd/2rRpta1U8F7ppEotS1MD0u9///uYOXPmmHGmf/hSOFq2bFmUO1Dut99+cdNNN8WXvvSl\n0h+6zTffPN75zneO2Ua6kbaRQtKay6pVq8qGrjX7+HmsQHrwjfzhGnuPW80UGDkojnxv5ljs\nu7yAx015l2a3OqY1uwLl9z9yLPO4Ke+ThVa1yUIVyo8hPX5GHkPle2gdEaj197ipASmd9UlX\noltzGbld7sp06b53v/vdseuuu8app54a6RmN9B6mo48+Or7zne/ErFmzRjeVnum4++67R2+n\nH5YvXx6LFi0a0+ZGeYH0CzR//vxIVwxcunRp+U5amyaQnkhIz4Kk+liyJZCOPenx41iTrbqk\n0aQzR1OnTi09AZe90RV7ROnJ0vQMeHpic+T/gGKLZGv26bi2ePHibA3KaCK9kiqdTFixYkWs\nXLmSSA0CKTus+VadSquMfw1bpZ51aN9kk01KRV1z0ynEpGKnl3atvdx3333xxz/+Md7//vfH\n3LlzY/bs2aWf0z+Kd95559rd3SZAgAABAgQIECBAgMB6CTQ1IG2zzTbx61//esyzRQ8++OC4\n9yWNzKi3t7f045qvsxw5rfj888+PdPOdAAECBAgQIECAAAECExJoakBKl+tOS7roQnrP0COP\nPFL6fKN0MYWR5bbbbovrr7++dHOnnXYqXZzh3//93yO9nyi9Tyld9jst6QNmLQQIECBAgAAB\nAgQIEJiMQFPfg5ReRnfKKafEySefXApJ6bXh6XON1gw7N954Yzz11FPx5je/uXTFrtNPPz0+\n97nPlW6ns0fpZXrp9mabbTYZB+sSIECAAAECBAgQIEAg2v50qeBMfMJqekPzyJuba6nLs/+/\nvTuBsrn+/zj+lrHvS1mShlAhTEnoCNUpOpSl0GLJltLinDaKhNRpQRyFbHWiOCnbqY5j61hL\nITnZiZGiscs2Y/Tv9fn97v3dGaP/zDTX3O/3+/ycM+693/u93/v5PD7n63vfn+175Iilpqa6\nACkz+2sfzW9iKF7mtEKLNKinjkUaMmd2KfdikYZLqZ217wr9P8YiDVlzuxR7s0jDpVDO3neE\nFmnQQgAs0pA9w2h+ikUaoqmb/WOHFmnQiCoWacicY2YXacjVHqTIomjFtKykjJYAz8rn2RcB\nBBBAAAEEEEAAAQQQSC+Qq3OQ0meG1wgggAACCCCAAAIIIIBAbgoQIOWmPt+NAAIIIIAAAggg\ngAACMSVAgJRL1ZGcnJxL38zXIoAAAggggAACCCCAwMUECJAuJhOF7VoP44MPPrDatWtbfHy8\n1axZ07RkuZY4JyGAAAIIIIAAAggggEDuC8TMIg25TxH9HAwfPtwFSKEVerQ63IgRI2zfvn32\n5ptvRj8DfAMCCCCAAAIIIIAAAgj8owA9SP/Ik3NvaunS8ePHX7B8aUpKik2bNs0SExNz7ss4\nEgIIIIAAAggggAACCGRLgAApW2xZ/9DGjRstLi7jDjvdMHf9+vVZPyifQAABBBBAAAEEEEAA\ngRwVIEDKUc6LH6xo0aLuxrYZ7aE5SLrxJwkBBBBAAAEEEEAAAQRyV4AA6RL5JyQk2MVubqs7\nITds2PAS5YSvQQABBBBAAAEEEEAAgYsJECBdTCaHt+fLl88mT55shQoVsvz587uj61F/Wtmu\ncOHCOfyNHA4BBBBAAAEEEEAAAQSyKpDxpJisHoX9MyVw880326pVq+zTTz+1nTt3uqW+O3bs\naJUqVcrU59kJAQQQQAABBBBAAAEEoitAgBRd3wuOXq5cOevXr98F29mAAAIIIIAAAggggAAC\nuS/AELvcrwNygAACCCCAAAIIIIAAAjEiQIAUIxVBNhBAAAEEEEAAAQQQQCD3BQiQcr8OyAEC\nCCCAAAIIIIAAAgjEiAABUoxUBNlAAAEEEEAAAQQQQACB3BcgQMr9OiAHCCCAAAIIIIAAAggg\nECMCBEgxUhFkAwEEEEAAAQQQQAABBHJfgAAp9+uAHCCAAAIIIIAAAggggECMCBAgxUhFkA0E\nEEAAAQQQQAABBPwmcPLkSUtJSfFUsQiQPFVdZBYBBBBAAAEEEEAAgdgXWLx4sTVs2NCqV69u\nVatWtUcffdSSkpJiP+N/55AAyRPVRCYRQAABBBBAAAEEEPCGwNKlS61r166WmJjoMpyammoK\nmFq1amWnT5+O+UIQIMV8FZFBBBBAAAEEEEAAAQS8IzB48GA7f/58mgyfO3fODhw4YDNnzkyz\nPRZfECDFYq2QJwQQQAABBBBAAAEEPCigQGjHjh0Z5jw5OdnWrVuX4XuxtJEAKZZqg7wggAAC\nCCCAAAIIIOBhgbi4OCtQoECGJdB7pUqVyvC9WNpIgBRLtUFeEEAAAQQQQAABBBDwuECbNm0s\nX758F5RCc5H0XqwnAqRYryHyhwACCCCAAAIIIICAhwSGDBli1apVs/z581uePHlcsKTH/v37\nW0JCQsyXJC7mc0gGEUAAAQQQQAABBBBAwDMCxYsXtwULFtjcuXNt7dq1ptf33HOP1alTxxNl\nIEDyRDWRSQQQQAABBBBAAAEEvCOg+Ubt27d3f97J9X9yyhA7r9UY+UUAAQQQQAABBBBAAIGo\nCRAgRY2WAyOAAAIIIIAAAggggIDXBAiQvFZj5BcBBBBAAAEEEEAAAQSiJkCAFDVaDowAAggg\ngAACCCCAAAJeEyBA8lqNkV8EEEAAAQQQQAABBBCImgABUtRoOTACCCCAAAIIIIAAAgh4TYAA\nyWs1Rn4RQAABBBBAAAEEEEAgagIESFGj5cAIIIAAAggggAACCCDgNQECJK/VGPlFAAEEEEAA\nAQQQQACBqAkQIEWNlgMjgAACCCCAAAIIIICA1wQIkLxWY+QXAQQQQAABBBBAAAEEoiZAgBQ1\nWg6MAAIIIIAAAggggAACXhMgQPJajZFfBBBAAAEEEEAAAQQQiJoAAVLUaDkwAggggAACCCCA\nAAIIeE2AAMlrNUZ+EUAAAQQQQAABBBBAIGoCBEhRo+XACCCAAAIIIIAAAggg4DUBAiSv1Rj5\nRQABBBBAAAEEEEAAgagJECBFjZYDI4AAAggggAACCCCAgNcECJC8VmPkFwEEEEAAAQQQQAAB\nBKImQIAUNVoOjAACCCCAAAIIIIAAAl4TIEDyWo2RXwQQQAABBBBAAAEEEIiaAAFS1Gg5MAII\nIIAAAggggAACCHhNgADJazVGfhFAAAEEEEAAAQQQQCBqAgRIUaPlwAgggAACCCCAAAIIIOA1\nAQIkr9UY+UUAAQQQQAABBBBAAIGoCRAgRY2WAyOAAAIIIIAAAggggIDXBAiQvFZj5BcBBBBA\nAAEEEEAAAQSiJkCAFDVaDowAAggggAACCCCAAAJeEyBA8lqNkV8EEEAAAQQQQAABBBCImgAB\nUtRoOTACCCCAAAIIIIAAAgh4TSDPX38nr2Wa/EZfICkpyTp27GjNmjWzV155JfpfyDcg4BOB\nLl262PHjx23OnDk+KRHFQCD6AqNGjbL58+fbxIkT7Zprron+F/INCPhA4JtvvrGhQ4da3759\nrX379j4oUewUIS52skJOYkkgNTXV9u3bZ4cOHYqlbJEXBGJeYP/+/Xbs2LGYzycZRCCWBI4c\nOeKuOSkpKbGULfKCQEwLnDp1yp03J06ciOl8ejFzDLHzYq2RZwQQQAABBBBAAAEEEIiKAAFS\nVFg5KAIIIIAAAggggAACCHhRgCF2Xqy1S5DnAgUK2O233261a9e+BN/GVyDgH4FGjRqZhj2Q\nEEAg8wLXXXedu+YUK1Ys8x9iTwQCLlCuXDl33lSuXDngEjlffBZpyHlTjogAAggggAACCCCA\nAAIeFWCInUcrjmwjgAACCCCAAAIIIIBAzgsQIOW8KUdEAAEEEEAAAQQQQAABjwowB8mjFZeT\n2T5//rxt3LjRfvzxR9N41ubNm5vmIEWmxMREW7VqlZUuXdoaN25sRYsWjXyb5wgEUuC3336z\n5cuXW968ed15UbFixbCDll1dvXp1+HXoic6vfPnyhV7yiEDgBI4ePWrLli0z3YaxQYMGVqFC\nhTQGOndWrlxperzllluM+RVpeHgRUIFz587Z999/b7t27bIbbrjB6tSpk0ZC58zJkyfTbLv+\n+uvtqquuSrONF5kTYA5S5px8u9fBgwetZ8+eLiCqW7eu+0Gn4GfChAlWvHhxV+6PP/7YJk2a\nZE2bNjX9IDx79qyNGTPGSpUq5VsXCobA/ycwaNAg++6776xJkyb2yy+/2J49e+y1114zLdKg\ntGLFChs4cKCVLVs2zaGmTp1qTERPQ8KLAAksWbLEXn/9dRcYnT592jZt2mTDhw+3+vXrOwWd\nSz169LCqVavalVde6QIlnVcNGzYMkBJFRSCtgBoVdBNyXU90bqhhrnXr1vbkk0+6HXXvyrvu\nustdW+Li/tf30bt3b7c97dF4lRmB/ylmZm/28Z3ArFmzTK3e77//viubLljt2rWzmTNnWq9e\nvUw9R/pBN3r0aKtXr56pBaNPnz7ufT2SEAiiwNatW10L+GeffWZXXHGFIxgyZIhrOAgFSNu3\nb7datWrZe++9F0QiyozABQK6Cez48eNdo1ynTp3c+2+88YZNnDgxHCDp9b333mvPPPOM5cmT\nxz766CMbNWqUzZgxw72+4KBsQCAAAmqoVk+rGq+Vvv32W3v++eftgQcecCN/9u7da8nJyTZ5\n8mQrU6ZMAESiX0TmIEXfOKa/oXDhwq5VIpTJQoUKmZZbVU+R0po1a1wApeBISS0TLVq0sIUL\nF7rX/INAEAWOHDniWrlDwZEMEhISbP/+/W7YkF4rQLr22mv1lIQAAn8LqJVbLd4KgEJJIxEO\nHz7sXh46dMg2b95s9913XzgYatWqlbseqaeJhEBQBTSC54UXXggXPzSCR9ciJV1v1LtEcBQm\n+tdP6EH614TePoC6bCOTLlTr16+3vn37us2///67G+YQuY96nDQ0T3OXLruMGDvShufBENBw\nn/RDfhYvXmwa761WbyVdsDSXr3///rZlyxb3nn4catgQCYEgChQsWNBuu+02V3QFQ2qAmz17\ntmts0EY1MChFzuXTD778+fPbH3/84Xpk3Q78g0DABELzjTTFQfPF1bOqbTVq1HASO3bscMPr\nRo4c6YalKoDS77vQ+RYwrhwpLr9uc4TRHwdR9+yrr75qV199tbVp08YVShes0FykUCk1f0LB\n0bFjx0KbeEQg0AIakrphwwY3LEgQmlyuc0cNCWot1zw/NTao4eHPP/8MtBWFR0ACQ4cOtbfe\nesu1emsen5LOETUqpF8kSNecUEu525F/EAiowLx580zzX3/++Wfr2LFjuJF627ZtridWAZOG\n3qkh7uWXX85woaCA0mW52PQgZZnMnx84fvy4DRgwwPSo8d6hVbb0qHlHkSn0WsPzSAgEXWDK\nlCk2ffp0N9E8NKROC51ofpJWfVTrt1LNmjWta9eupp4mDSEiIRBkAc1r1cRzzT/q3Lmzff75\n5+66E7q+RNpoaB7Xm0gRngdVQHOO2rZt6xZp0CJAL730kpv2oMZtNVyHht5phIN6ldR4F5oX\nG1Sz7JabHqTsyvnoc2rlfuKJJ1wgNHbs2DSrbmlMq1rDI5OCKJ2E6Vv5IvfhOQJ+F9DF6O23\n33YXoHfeecduvfXWcJE1zK58+fLh4EhvaOWhyy+/3LWSh3fkCQIBFihZsqRplS0FQFoSX9cb\nPT916lQaFV1z0i8FnmYHXiAQIAHNBdftIrRE/tKlS13JS5QoEQ6OQhQKjNQrS8qeAAFS9tx8\n86kDBw644Ejr5Gvpbp1kkalKlSpu/kRkq566dplHEanE8yAKDBs2zP2oGzdunFugIdJg9+7d\nrrdIKwuFki5USUlJnDshEB4DJ6Dzon379uFFgARw5swZFxTpnkiVKlVyCwHpGhNKWrRBjRGR\n85JC7/GIQFAE+vXr50YlRJZXw7V13ii9+OKLplWJI5OGfXPeRIpk7TkBUta8fLf3iBEj3MVJ\n3baaSK4TSn+6F4XSnXfe6R41hEgXKd2g7KuvvnJDItwb/INAAAW+/vprW7RokXXr1s31sIbO\nGz2qBTw+Pt40IV1LGmvuhIIjLaWvntc77rgjgGIUGQFz54VuRq7zQnNY1UCn80INcxoSpEfd\ny0W3ltCPPwVPugefVk5V7ysJgaAKaISCfoft3LnT3Yty7ty5bh5Sy5YtHYlWUdVS4FocSAs5\naMiqftN16NAhqGT/utzcKPZfE3r3AFrKW5P8Mkq6e7mGDSlpVTvd40XDHrQMuOZPdO/ePaOP\nsQ2BQAjoRpaaFJtRWrBggZsvoYuTJqKHlszXEDuNE69cuXJGH2MbAoEQ0A84nQc6L9TopkWB\nNI9Ct5dQUoOCrjdqbNAwbt3AXJPN0y8WFAgsConAfwUU9OiGyhpSp3mtGmb32GOPuftWahfd\nw1KjGnQDWb2vc+fpp592jQsgZk+AACl7boH8lFr71IrH0t6BrH4KnU0BzfHTYifph69m83B8\nDAFfCGjZbv3I00ImGSXNO8qbN68VKVIko7fZhkAgBdSzqnNDPbE6P9KnkydPulENej90y4n0\n+/A6cwIESJlzYi8EEEAAAQQQQAABBBAIgABzkAJQyRQRAQQQQAABBBBAAAEEMidAgJQ5J/ZC\nAAEEEEAAAQQQQACBAAgQIAWgkikiAggggAACCCCAAAIIZE6AAClzTuyFAAIIIIAAAggggAAC\nARAgQApAJVNEBBBAAAEEEEAAAQQQyJwAAVLmnNgLAQQQQCAGBY4ePWp79uxxNxaNweyRJQQQ\nQAABDwoQIHmw0sgyAggggMB/BHSz6/j4eHv88cchQQABBBBAIEcEuA9SjjByEAQQQACBSy2Q\nmJhoVapUsZo1a9r27dvt119/tbJly17qbPB9CCCAAAI+E6AHyWcVSnEQQACBoAh8+OGH7m7x\n48aNs7Nnz9rUqVODUnTKiQACCCAQRQF6kKKIy6ERQAABBKIj8Ndff1nVqlWtYsWKtnLlSqtT\np46dOnXK9STlyZPngi9NSkqyL7/80hYtWmQVKlSwhx9+2A4fPuw+O2jQoPD+586dc4HWmjVr\n3PESEhKsV69eVqJEifA+PEEAAQQQ8LcAPUj+rl9KhwACCPhSYMmSJbZ792578MEHXfkeeeQR\n27lzpy1cuPCC8io4ql+/vj311FNuMYfVq1db48aNbcCAATZ8+PDw/tqvUaNG1rt3b1u2bJkL\nkPR+3bp1bdOmTeH9eIIAAggg4G8BAiR/1y+lQwABBHwpMGXKFMufP384QOrcubPlzZvXNNwu\nferUqZOdOHHC1q5da3PmzLEVK1bYu+++a+olikz9+/e3H374wb744gvbunWrzZ492zZs2GDJ\nycnWp0+fyF15jgACCCDgYwECJB9XLkVDAAEE/Cigpb0VxLRu3drKlCnjiqhhc3fffbfNnz/f\nLdYQKvfBgwdNvU3qPapRo0Zos+slqlevXvi1jqk5TOpBatu2bXh75cqV7aGHHrLly5fbTz/9\nFN7OEwQQQAAB/wrE+bdolAwBBBBAwI8Cn3zyiZ05c8aKFy9ukydPDhexdOnSlpqaahMnTrQh\nQ4a47evWrXOPkcFQ6AM33nijbd682b3UKnia13T8+HHr0KFDaBf3qNXxlLZt2+bmOrkX/IMA\nAggg4FsBAiTfVi0FQwABBPwpoOF1SurxyWjlukmTJpkWXoiLizPNK1LScLz0qVChQuFN6mlS\n0rbLLks7uEK9SPorVqxYeH+eIIAAAgj4V4AAyb91S8kQQAAB3wlomJvmEmlO0OjRoy8o37PP\nPmtjx461efPmWbt27axatWpun127dl2wb+Q2rYinpGF406dPT7OveqU0v4mEAAIIIBAMgbTN\nZMEoM6VEAAEEEPCoQGhIXZcuXVyvkHqGIv969uzpShZarEHD6OLj423ChAmWkpISLvWWLVvS\nrHinAKl8+fJuYQYNs4tMWhK8ZMmStmfPnsjNPEcAAQQQ8KkA90HyacVSLAQQQMBvAlpNTvc9\nKlWqlLvf0cXKd9NNN9n69evdSnTVq1e3WbNmmVay0/Zu3bqZFmQYNWqUW/Jb845Onz7tDjVt\n2jTTanjNmze3wYMHW+HChW3GjBk2cuRIN2Rv6NChF/tKtiOAAAII+EiAHiQfVSZFQQABBPws\nMHfuXDt06JDpnkf/lHr06OEWXFCvkdL999/vbhJbsGBBd+8jLfIwbNgwa9GihRUpUiR8KB13\n5syZLrBq1qyZNWjQwMaMGWPdu3e3gQMHhvfjCQIIIICAvwXoQfJ3/VI6BBBAINACmj+0d+9e\nt8hC+sUXmjZtagcOHDANt0uf9u/f74IxDc+LDKLS78drBBBAAAH/CdCD5L86pUQIIIAAAv8V\nUFBUu3Zta9myZRoT3SxW9zZq0qRJmu2hF5qPVKtWLYKjEAiPCCCAQIAE6EEKUGVTVAQQQCCI\nAs8995yNGDHC6tevb+o10j2Pli5dalqYQTeR1f2TSAgggAACCIQECJBCEjwigAACCPhS4Pz5\n87Zs2TJbsGCBC4wqVapkjRo1sq5du1rZsmV9WWYKhQACCCCQfQECpOzb8UkEEEAAAQQQQAAB\nBBDwmQBzkHxWoRQHAQQQQAABBBBAAAEEsi9AgJR9Oz6JAAIIIIAAAggggAACPhMgQPJZhVIc\nBBBAAAEEEEAAAQQQyL4AAVL27fgkAggggAACCCCAAAII+EyAAMlnFUpxEEAAAQQQQAABBBBA\nIPsCBEjZt+OTCCCAAAIIIIAAAggg4DMBAiSfVSjFQQABBBBAAAEEEEAAgewLECBl345PIoAA\nAggggAACCCCAgM8E/g9Oh8w9+ft3gwAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ggplot(Mantle, aes(Age, OPS)) + geom_point()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [],
"source": [
"fit_model <- function(d) {\n",
" fit <- lm(OPS ~ I(Age - 30) + I((Age - 30) ^2), data = d)\n",
" b <- coef(fit)\n",
" Age.max <- 30 -b[2] / b[3] / 2\n",
" Max <- b[1] - b[2] ^ 2 / b[3] / 4\n",
" Max2 <- b\n",
" list(fit = fit, Age.max = Age.max, Max = Max)\n",
"}"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"NULL"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"F2 <- fit_model(Mantle)\n",
"F2$Max2"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<dl class=dl-horizontal>\n",
"\t<dt>(Intercept)</dt>\n",
"\t\t<dd>1.04313418918112</dd>\n",
"\t<dt>I(Age - 30)</dt>\n",
"\t\t<dd>-0.0228830237903891</dd>\n",
"\t<dt>I((Age - 30)^2)</dt>\n",
"\t\t<dd>-0.00386891486821035</dd>\n",
"</dl>\n"
],
"text/latex": [
"\\begin{description*}\n",
"\\item[(Intercept)] 1.04313418918112\n",
"\\item[I(Age - 30)] -0.0228830237903891\n",
"\\item[I((Age - 30)\\textbackslash{}textasciicircum\\{\\}2)] -0.00386891486821035\n",
"\\end{description*}\n"
],
"text/markdown": [
"(Intercept)\n",
": 1.04313418918112I(Age - 30)\n",
": -0.0228830237903891I((Age - 30)^2)\n",
": -0.00386891486821035\n",
"\n"
],
"text/plain": [
" (Intercept) I(Age - 30) I((Age - 30)^2) \n",
" 1.043134189 -0.022883024 -0.003868915 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"coef(F2$fit)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<dl class=dl-horizontal>\n",
"\t<dt>I(Age - 30)</dt>\n",
"\t\t<dd>27.0427077656307</dd>\n",
"\t<dt>(Intercept)</dt>\n",
"\t\t<dd>1.07697008345822</dd>\n",
"</dl>\n"
],
"text/latex": [
"\\begin{description*}\n",
"\\item[I(Age - 30)] 27.0427077656307\n",
"\\item[(Intercept)] 1.07697008345822\n",
"\\end{description*}\n"
],
"text/markdown": [
"I(Age - 30)\n",
": 27.0427077656307(Intercept)\n",
": 1.07697008345822\n",
"\n"
],
"text/plain": [
"I(Age - 30) (Intercept) \n",
" 27.04271 1.07697 "
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"c(F2$Age.max, F2$Max)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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ughe9KoUaPkb3/7m89y7cvzf/AC2qRRnyXT4JPkLIHevXvbV/X0+UqSswT05Fsv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H1BbQH6f7XV8Nr8vLy5NvfetblxtH6hA1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\neohP3AAAAABJRU5ErkJggg==",
"text/plain": [
"plot without title"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"ggplot(Mantle, aes(Age, OPS)) + geom_point() +\n",
" geom_smooth(method = \"lm\", se = FALSE, size = 1.5, formula = y ~ poly(x, 2, raw = TRUE)) +\n",
" geom_vline(xintercept = F2$Age.max, linetype = \"dashed\", color = \"darkgrey\") +\n",
" geom_hline(yintercept = F2$Max, linetype = \"dashed\", color = \"darkgrey\") +\n",
" annotate(geom = \"text\", x = c(29, 20), y = c(0.72, 1.1), label = c(\"Peak Age\", \"Max\"), size = 5)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "R",
"language": "R",
"name": "ir"
},
"language_info": {
"codemirror_mode": "r",
"file_extension": ".r",
"mimetype": "text/x-r-source",
"name": "R",
"pygments_lexer": "r",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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