mms.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from sklearn.metrics import pairwise\n",
    "import seaborn as sns\n",
    "from scipy.spatial import distance"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [],
   "source": [
    "data = np.random.randint(low=0, high=6, size=(50, 1000))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[2 5 4 ... 5 3 2]\n",
      " [1 4 0 ... 5 2 4]\n",
      " [0 3 2 ... 1 1 1]\n",
      " ...\n",
      " [4 3 4 ... 0 3 3]\n",
      " [5 3 2 ... 3 0 3]\n",
      " [1 2 0 ... 1 4 5]]\n"
     ]
    }
   ],
   "source": [
    "print(data)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "outputs": [],
   "source": [
    "df = pd.DataFrame(data=data)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "outputs": [
    {
     "data": {
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<td>0</td>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n      <td>0</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>...</td>\n      <td>1</td>\n      <td>5</td>\n      <td>0</td>\n      <td>3</td>\n      <td>3</td>\n      <td>5</td>\n      <td>2</td>\n      <td>0</td>\n      <td>1</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>18</th>\n      <td>3</td>\n      <td>5</td>\n      <td>4</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>...</td>\n      <td>1</td>\n      <td>3</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>3</td>\n      <td>0</td>\n      <td>4</td>\n      <td>5</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>19</th>\n      <td>0</td>\n      <td>5</td>\n      <td>0</td>\n      <td>1</td>\n      <td>3</td>\n      <td>0</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>...</td>\n      <td>5</td>\n      <td>5</td>\n      <td>4</td>\n      <td>5</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>20</th>\n      <td>4</td>\n      <td>3</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n      <td>2</td>\n      <td>...</td>\n      <td>2</td>\n      <td>5</td>\n      <td>1</td>\n      <td>0</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>1</td>\n      <td>4</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>21</th>\n      <td>1</td>\n      <td>4</td>\n      <td>2</td>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n      <td>1</td>\n      <td>5</td>\n      <td>5</td>\n      <td>4</td>\n      <td>...</td>\n      <td>4</td>\n      <td>0</td>\n      <td>3</td>\n      <td>0</td>\n      <td>2</td>\n      <td>4</td>\n      <td>5</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>22</th>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>5</td>\n      <td>0</td>\n      <td>1</td>\n      <td>4</td>\n      <td>...</td>\n      <td>5</td>\n      <td>5</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>5</td>\n      <td>1</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>23</th>\n      <td>5</td>\n      <td>1</td>\n      <td>3</td>\n      <td>3</td>\n      <td>5</td>\n      <td>2</td>\n      <td>4</td>\n      <td>2</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>24</th>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>1</td>\n      <td>3</td>\n      <td>2</td>\n      <td>0</td>\n      <td>...</td>\n      <td>3</td>\n      <td>0</td>\n      <td>4</td>\n      <td>3</td>\n      <td>3</td>\n      <td>0</td>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>25</th>\n      <td>2</td>\n      <td>4</td>\n      <td>4</td>\n      <td>5</td>\n      <td>2</td>\n      <td>5</td>\n      <td>0</td>\n      <td>5</td>\n      <td>2</td>\n      <td>4</td>\n      <td>...</td>\n      <td>5</td>\n      <td>3</td>\n      <td>0</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>26</th>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>0</td>\n      <td>1</td>\n      <td>5</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n      <td>...</td>\n      <td>5</td>\n      <td>2</td>\n      <td>4</td>\n      <td>2</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>2</td>\n      <td>1</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>27</th>\n      <td>4</td>\n      <td>1</td>\n      <td>5</td>\n      <td>4</td>\n      <td>2</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n      <td>5</td>\n      <td>...</td>\n      <td>2</td>\n      <td>2</td>\n      <td>5</td>\n      <td>0</td>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n      <td>1</td>\n      <td>4</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>28</th>\n      <td>4</td>\n      <td>4</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>3</td>\n      <td>0</td>\n      <td>5</td>\n      <td>...</td>\n      <td>0</td>\n      <td>3</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>4</td>\n      <td>3</td>\n      <td>0</td>\n      <td>5</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>29</th>\n      <td>1</td>\n      <td>5</td>\n      <td>5</td>\n      <td>3</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>1</td>\n      <td>...</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n      <td>5</td>\n      <td>0</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>0</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>30</th>\n      <td>4</td>\n      <td>0</td>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n      <td>5</td>\n      <td>3</td>\n      <td>5</td>\n      <td>0</td>\n      <td>5</td>\n      <td>...</td>\n      <td>2</td>\n      <td>2</td>\n      <td>4</td>\n      <td>5</td>\n      <td>5</td>\n      <td>3</td>\n      <td>2</td>\n      <td>3</td>\n      <td>3</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>31</th>\n      <td>2</td>\n      <td>5</td>\n      <td>5</td>\n      <td>3</td>\n      <td>1</td>\n      <td>3</td>\n      <td>4</td>\n      <td>0</td>\n      <td>3</td>\n      <td>1</td>\n      <td>...</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n      <td>5</td>\n      <td>1</td>\n      <td>1</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>32</th>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>0</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>...</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>3</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n    </tr>\n    <tr>\n      <th>33</th>\n      <td>2</td>\n      <td>5</td>\n      <td>5</td>\n      <td>2</td>\n      <td>5</td>\n      <td>1</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>...</td>\n      <td>2</td>\n      <td>2</td>\n      <td>0</td>\n      <td>5</td>\n      <td>5</td>\n      <td>1</td>\n      <td>5</td>\n      <td>3</td>\n      <td>0</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>34</th>\n      <td>5</td>\n      <td>3</td>\n      <td>3</td>\n      <td>0</td>\n      <td>5</td>\n      <td>1</td>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>0</td>\n      <td>...</td>\n      <td>4</td>\n      <td>5</td>\n      <td>3</td>\n      <td>1</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n    </tr>\n    <tr>\n      <th>35</th>\n      <td>0</td>\n      <td>2</td>\n      <td>4</td>\n      <td>2</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>...</td>\n      <td>4</td>\n      <td>0</td>\n      <td>3</td>\n      <td>0</td>\n      <td>4</td>\n      <td>4</td>\n      <td>0</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>36</th>\n      <td>0</td>\n      <td>2</td>\n      <td>3</td>\n      <td>2</td>\n      <td>3</td>\n      <td>5</td>\n      <td>1</td>\n      <td>1</td>\n      <td>3</td>\n      <td>5</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>3</td>\n      <td>3</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>37</th>\n      <td>0</td>\n      <td>3</td>\n      <td>4</td>\n      <td>4</td>\n      <td>1</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>5</td>\n      <td>4</td>\n      <td>...</td>\n      <td>3</td>\n      <td>1</td>\n      <td>0</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>3</td>\n      <td>3</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>38</th>\n      <td>1</td>\n      <td>5</td>\n      <td>4</td>\n      <td>2</td>\n      <td>2</td>\n      <td>1</td>\n      <td>3</td>\n      <td>1</td>\n      <td>0</td>\n      <td>3</td>\n      <td>...</td>\n      <td>1</td>\n      <td>2</td>\n      <td>0</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>3</td>\n      <td>2</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>39</th>\n      <td>0</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>3</td>\n      <td>...</td>\n      <td>5</td>\n      <td>1</td>\n      <td>3</td>\n      <td>1</td>\n      <td>4</td>\n      <td>5</td>\n      <td>3</td>\n      <td>3</td>\n      <td>4</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>40</th>\n      <td>2</td>\n      <td>0</td>\n      <td>0</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>2</td>\n      <td>2</td>\n      <td>...</td>\n      <td>5</td>\n      <td>5</td>\n      <td>4</td>\n      <td>5</td>\n      <td>1</td>\n      <td>2</td>\n      <td>3</td>\n      <td>5</td>\n      <td>3</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>41</th>\n      <td>4</td>\n      <td>0</td>\n      <td>5</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>0</td>\n      <td>5</td>\n      <td>3</td>\n      <td>5</td>\n      <td>...</td>\n      <td>2</td>\n      <td>3</td>\n      <td>2</td>\n      <td>0</td>\n      <td>4</td>\n      <td>0</td>\n      <td>1</td>\n      <td>4</td>\n      <td>2</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>42</th>\n      <td>3</td>\n      <td>3</td>\n      <td>5</td>\n      <td>1</td>\n      <td>2</td>\n      <td>2</td>\n      <td>5</td>\n      <td>2</td>\n      <td>1</td>\n      <td>2</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>1</td>\n      <td>0</td>\n      <td>5</td>\n      <td>1</td>\n      <td>0</td>\n      <td>4</td>\n    </tr>\n    <tr>\n      <th>43</th>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>4</td>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>...</td>\n      <td>2</td>\n      <td>1</td>\n      <td>4</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>2</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>44</th>\n      <td>3</td>\n      <td>3</td>\n      <td>1</td>\n      <td>2</td>\n      <td>4</td>\n      <td>4</td>\n      <td>4</td>\n      <td>3</td>\n      <td>1</td>\n      <td>1</td>\n      <td>...</td>\n      <td>5</td>\n      <td>1</td>\n      <td>5</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>4</td>\n      <td>3</td>\n      <td>1</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>45</th>\n      <td>2</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>4</td>\n      <td>0</td>\n      <td>3</td>\n      <td>2</td>\n      <td>5</td>\n      <td>1</td>\n      <td>...</td>\n      <td>1</td>\n      <td>4</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>3</td>\n      <td>5</td>\n    </tr>\n    <tr>\n      <th>46</th>\n      <td>1</td>\n      <td>2</td>\n      <td>1</td>\n      <td>0</td>\n      <td>3</td>\n      <td>0</td>\n      <td>1</td>\n      <td>5</td>\n      <td>4</td>\n      <td>0</td>\n      <td>...</td>\n      <td>5</td>\n      <td>1</td>\n      <td>3</td>\n      <td>0</td>\n      <td>5</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n      <td>1</td>\n      <td>2</td>\n    </tr>\n    <tr>\n      <th>47</th>\n      <td>4</td>\n      <td>3</td>\n      <td>4</td>\n      <td>3</td>\n      <td>4</td>\n      <td>1</td>\n      <td>3</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n      <td>...</td>\n      <td>1</td>\n      <td>4</td>\n      <td>0</td>\n      <td>2</td>\n      <td>1</td>\n      <td>1</td>\n      <td>0</td>\n      <td>0</td>\n      <td>3</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>48</th>\n      <td>5</td>\n      <td>3</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>1</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>2</td>\n      <td>...</td>\n      <td>5</td>\n      <td>4</td>\n      <td>2</td>\n      <td>4</td>\n      <td>1</td>\n      <td>1</td>\n      <td>2</td>\n      <td>3</td>\n      <td>0</td>\n      <td>3</td>\n    </tr>\n    <tr>\n      <th>49</th>\n      <td>1</td>\n      <td>2</td>\n      <td>0</td>\n      <td>2</td>\n      <td>0</td>\n      <td>3</td>\n      <td>5</td>\n      <td>0</td>\n      <td>1</td>\n      <td>1</td>\n      <td>...</td>\n      <td>2</td>\n      <td>2</td>\n      <td>3</td>\n      <td>4</td>\n      <td>5</td>\n      <td>4</td>\n      <td>2</td>\n      <td>1</td>\n      <td>4</td>\n      <td>5</td>\n    </tr>\n  </tbody>\n</table>\n<p>50 rows × 1000 columns</p>\n</div>"
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "outputs": [],
   "source": [
    "sim = pairwise.cosine_similarity(df)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cosine similarity between row 1 and row 0 is 0.6936463066285999\n",
      "cosine similarity between row 2 and row 0 is 0.6755202878582166\n",
      "cosine similarity between row 2 and row 1 is 0.6822867740453196\n",
      "cosine similarity between row 3 and row 0 is 0.6848527491097506\n",
      "cosine similarity between row 3 and row 1 is 0.6902323737872296\n",
      "cosine similarity between row 3 and row 2 is 0.6780926658117028\n",
      "cosine similarity between row 4 and row 0 is 0.6814302278152795\n",
      "cosine similarity between row 4 and row 1 is 0.6889167525232867\n",
      "cosine similarity between row 4 and row 2 is 0.6790306316246786\n",
      "cosine similarity between row 4 and row 3 is 0.6943451188807976\n",
      "cosine similarity between row 5 and row 0 is 0.6543980831366638\n",
      "cosine similarity between row 5 and row 1 is 0.660835501223758\n",
      "cosine similarity between row 5 and row 2 is 0.6741113983727295\n",
      "cosine similarity between row 5 and row 3 is 0.6704209180333824\n",
      "cosine similarity between row 5 and row 4 is 0.6879061364120791\n",
      "cosine similarity between row 6 and row 0 is 0.6666678938254708\n",
      "cosine similarity between row 6 and row 1 is 0.6643693189661543\n",
      "cosine similarity between row 6 and row 2 is 0.6862025988989627\n",
      "cosine similarity between row 6 and row 3 is 0.6804057498465833\n",
      "cosine similarity between row 6 and row 4 is 0.6852613945969009\n",
      "cosine similarity between row 6 and row 5 is 0.686070187194276\n",
      "cosine similarity between row 7 and row 0 is 0.6954374470864136\n",
      "cosine similarity between row 7 and row 1 is 0.7113845848698219\n",
      "cosine similarity between row 7 and row 2 is 0.6826075736250063\n",
      "cosine similarity between row 7 and row 3 is 0.6823323897370269\n",
      "cosine similarity between row 7 and row 4 is 0.7137723197777166\n",
      "cosine similarity between row 7 and row 5 is 0.6813386457656795\n",
      "cosine similarity between row 7 and row 6 is 0.7009547246324702\n",
      "cosine similarity between row 8 and row 0 is 0.6678604778455247\n",
      "cosine similarity between row 8 and row 1 is 0.6885933183365237\n",
      "cosine similarity between row 8 and row 2 is 0.6946581923086533\n",
      "cosine similarity between row 8 and row 3 is 0.6931618011682277\n",
      "cosine similarity between row 8 and row 4 is 0.6970887190202822\n",
      "cosine similarity between row 8 and row 5 is 0.6778189039846929\n",
      "cosine similarity between row 8 and row 6 is 0.6756334149418196\n",
      "cosine similarity between row 8 and row 7 is 0.6969713913397145\n",
      "cosine similarity between row 9 and row 0 is 0.6879251054743957\n",
      "cosine similarity between row 9 and row 1 is 0.6736334303104656\n",
      "cosine similarity between row 9 and row 2 is 0.6945689890453087\n",
      "cosine similarity between row 9 and row 3 is 0.701885126061978\n",
      "cosine similarity between row 9 and row 4 is 0.6999424866266666\n",
      "cosine similarity between row 9 and row 5 is 0.6858406453855607\n",
      "cosine similarity between row 9 and row 6 is 0.6919501729321128\n",
      "cosine similarity between row 9 and row 7 is 0.7045751145939951\n",
      "cosine similarity between row 9 and row 8 is 0.669931832438933\n",
      "cosine similarity between row 10 and row 0 is 0.6818543831636017\n",
      "cosine similarity between row 10 and row 1 is 0.684897510293231\n",
      "cosine similarity between row 10 and row 2 is 0.6835264588392301\n",
      "cosine similarity between row 10 and row 3 is 0.6854487149809545\n",
      "cosine similarity between row 10 and row 4 is 0.6950939076476609\n",
      "cosine similarity between row 10 and row 5 is 0.6882684569289826\n",
      "cosine similarity between row 10 and row 6 is 0.6877777908091277\n",
      "cosine similarity between row 10 and row 7 is 0.7056420913948388\n",
      "cosine similarity between row 10 and row 8 is 0.688320876574033\n",
      "cosine similarity between row 10 and row 9 is 0.6703316593276963\n",
      "cosine similarity between row 11 and row 0 is 0.6828397293657507\n",
      "cosine similarity between row 11 and row 1 is 0.7103989199176357\n",
      "cosine similarity between row 11 and row 2 is 0.701398742388372\n",
      "cosine similarity between row 11 and row 3 is 0.6810737214966084\n",
      "cosine similarity between row 11 and row 4 is 0.6994362277256121\n",
      "cosine similarity between row 11 and row 5 is 0.6972998967375312\n",
      "cosine similarity between row 11 and row 6 is 0.6904876512504025\n",
      "cosine similarity between row 11 and row 7 is 0.7118178317210021\n",
      "cosine similarity between row 11 and row 8 is 0.6927845791849545\n",
      "cosine similarity between row 11 and row 9 is 0.6852109243253096\n",
      "cosine similarity between row 11 and row 10 is 0.7078805840779356\n",
      "cosine similarity between row 12 and row 0 is 0.6956196775761894\n",
      "cosine similarity between row 12 and row 1 is 0.6693765407360048\n",
      "cosine similarity between row 12 and row 2 is 0.7037151086276712\n",
      "cosine similarity between row 12 and row 3 is 0.6609988130969813\n",
      "cosine similarity between row 12 and row 4 is 0.6807100862022708\n",
      "cosine similarity between row 12 and row 5 is 0.6917373245866804\n",
      "cosine similarity between row 12 and row 6 is 0.6808747648210659\n",
      "cosine similarity between row 12 and row 7 is 0.6958345253608368\n",
      "cosine similarity between row 12 and row 8 is 0.6768716829476906\n",
      "cosine similarity between row 12 and row 9 is 0.6715725241497575\n",
      "cosine similarity between row 12 and row 10 is 0.6845776916471362\n",
      "cosine similarity between row 12 and row 11 is 0.683151453357709\n",
      "cosine similarity between row 13 and row 0 is 0.6748393808099495\n",
      "cosine similarity between row 13 and row 1 is 0.6714700696532561\n",
      "cosine similarity between row 13 and row 2 is 0.6768339719063327\n",
      "cosine similarity between row 13 and row 3 is 0.6769711394104992\n",
      "cosine similarity between row 13 and row 4 is 0.6733380277979667\n",
      "cosine similarity between row 13 and row 5 is 0.670842888996948\n",
      "cosine similarity between row 13 and row 6 is 0.6798341160167592\n",
      "cosine similarity between row 13 and row 7 is 0.7002622826444469\n",
      "cosine similarity between row 13 and row 8 is 0.6894710404166886\n",
      "cosine similarity between row 13 and row 9 is 0.6927268346248702\n",
      "cosine similarity between row 13 and row 10 is 0.6862556344143853\n",
      "cosine similarity between row 13 and row 11 is 0.6866002082412374\n",
      "cosine similarity between row 13 and row 12 is 0.6915137389167122\n",
      "cosine similarity between row 14 and row 0 is 0.6699832903491341\n",
      "cosine similarity between row 14 and row 1 is 0.6854995704767828\n",
      "cosine similarity between row 14 and row 2 is 0.6689619544792169\n",
      "cosine similarity between row 14 and row 3 is 0.6829558186431124\n",
      "cosine similarity between row 14 and row 4 is 0.6956053827913605\n",
      "cosine similarity between row 14 and row 5 is 0.6758451366179373\n",
      "cosine similarity between row 14 and row 6 is 0.6706793931173609\n",
      "cosine similarity between row 14 and row 7 is 0.6914798261335979\n",
      "cosine similarity between row 14 and row 8 is 0.6831900697673539\n",
      "cosine similarity between row 14 and row 9 is 0.6916323075277027\n",
      "cosine similarity between row 14 and row 10 is 0.6761874197034757\n",
      "cosine similarity between row 14 and row 11 is 0.666568151341543\n",
      "cosine similarity between row 14 and row 12 is 0.6730392683319177\n",
      "cosine similarity between row 14 and row 13 is 0.6682713496488519\n",
      "cosine similarity between row 15 and row 0 is 0.6659102941523558\n",
      "cosine similarity between row 15 and row 1 is 0.6854213753183565\n",
      "cosine similarity between row 15 and row 2 is 0.6716016876730977\n",
      "cosine similarity between row 15 and row 3 is 0.6683535288177439\n",
      "cosine similarity between row 15 and row 4 is 0.6641336848404514\n",
      "cosine similarity between row 15 and row 5 is 0.663113900586808\n",
      "cosine similarity between row 15 and row 6 is 0.6678745055938545\n",
      "cosine similarity between row 15 and row 7 is 0.6906766332354677\n",
      "cosine similarity between row 15 and row 8 is 0.6760525193386213\n",
      "cosine similarity between row 15 and row 9 is 0.6685172471981368\n",
      "cosine similarity between row 15 and row 10 is 0.6653194255489236\n",
      "cosine similarity between row 15 and row 11 is 0.6994598259676307\n",
      "cosine similarity between row 15 and row 12 is 0.7023314040804806\n",
      "cosine similarity between row 15 and row 13 is 0.6526951315382203\n",
      "cosine similarity between row 15 and row 14 is 0.6561015315050024\n",
      "cosine similarity between row 16 and row 0 is 0.6752813201274734\n",
      "cosine similarity between row 16 and row 1 is 0.6875404701580091\n",
      "cosine similarity between row 16 and row 2 is 0.6784399566064075\n",
      "cosine similarity between row 16 and row 3 is 0.6681846430889931\n",
      "cosine similarity between row 16 and row 4 is 0.6875273609010755\n",
      "cosine similarity between row 16 and row 5 is 0.6684158335407866\n",
      "cosine similarity between row 16 and row 6 is 0.6715982911856001\n",
      "cosine similarity between row 16 and row 7 is 0.6817179947381186\n",
      "cosine similarity between row 16 and row 8 is 0.6789954235208013\n",
      "cosine similarity between row 16 and row 9 is 0.6783015817042416\n",
      "cosine similarity between row 16 and row 10 is 0.6875913407616812\n",
      "cosine similarity between row 16 and row 11 is 0.6759605933500101\n",
      "cosine similarity between row 16 and row 12 is 0.6807334451616656\n",
      "cosine similarity between row 16 and row 13 is 0.6639880331341498\n",
      "cosine similarity between row 16 and row 14 is 0.6888002015671174\n",
      "cosine similarity between row 16 and row 15 is 0.6715387431626447\n",
      "cosine similarity between row 17 and row 0 is 0.6786144860154674\n",
      "cosine similarity between row 17 and row 1 is 0.6713984663849232\n",
      "cosine similarity between row 17 and row 2 is 0.6923277294667898\n",
      "cosine similarity between row 17 and row 3 is 0.6868088785189481\n",
      "cosine similarity between row 17 and row 4 is 0.6724240298591369\n",
      "cosine similarity between row 17 and row 5 is 0.6794577083349351\n",
      "cosine similarity between row 17 and row 6 is 0.6823984850504679\n",
      "cosine similarity between row 17 and row 7 is 0.6821514144618718\n",
      "cosine similarity between row 17 and row 8 is 0.6702089270315708\n",
      "cosine similarity between row 17 and row 9 is 0.7068008872116464\n",
      "cosine similarity between row 17 and row 10 is 0.6928859695357362\n",
      "cosine similarity between row 17 and row 11 is 0.6881248905118074\n",
      "cosine similarity between row 17 and row 12 is 0.7165906062285179\n",
      "cosine similarity between row 17 and row 13 is 0.6692904967899121\n",
      "cosine similarity between row 17 and row 14 is 0.6734806488411733\n",
      "cosine similarity between row 17 and row 15 is 0.6948057623805866\n",
      "cosine similarity between row 17 and row 16 is 0.6809193540775834\n",
      "cosine similarity between row 18 and row 0 is 0.6912390414551653\n",
      "cosine similarity between row 18 and row 1 is 0.6863403836502754\n",
      "cosine similarity between row 18 and row 2 is 0.6717216734774852\n",
      "cosine similarity between row 18 and row 3 is 0.6770612241994414\n",
      "cosine similarity between row 18 and row 4 is 0.6829698878647993\n",
      "cosine similarity between row 18 and row 5 is 0.6738654801037648\n",
      "cosine similarity between row 18 and row 6 is 0.680139733662769\n",
      "cosine similarity between row 18 and row 7 is 0.6836537770232244\n",
      "cosine similarity between row 18 and row 8 is 0.6783457707475394\n",
      "cosine similarity between row 18 and row 9 is 0.677975475174576\n",
      "cosine similarity between row 18 and row 10 is 0.6905565166442184\n",
      "cosine similarity between row 18 and row 11 is 0.6784236943714059\n",
      "cosine similarity between row 18 and row 12 is 0.6737155745929886\n",
      "cosine similarity between row 18 and row 13 is 0.6660725956968645\n",
      "cosine similarity between row 18 and row 14 is 0.6645863292098692\n",
      "cosine similarity between row 18 and row 15 is 0.655278178337452\n",
      "cosine similarity between row 18 and row 16 is 0.6856731620903453\n",
      "cosine similarity between row 18 and row 17 is 0.6647305872897127\n",
      "cosine similarity between row 19 and row 0 is 0.6733002579539846\n",
      "cosine similarity between row 19 and row 1 is 0.6874808797511698\n",
      "cosine similarity between row 19 and row 2 is 0.6949235726043618\n",
      "cosine similarity between row 19 and row 3 is 0.6831718317689711\n",
      "cosine similarity between row 19 and row 4 is 0.7027053834616843\n",
      "cosine similarity between row 19 and row 5 is 0.7038481003811246\n",
      "cosine similarity between row 19 and row 6 is 0.7060678167488673\n",
      "cosine similarity between row 19 and row 7 is 0.7097769449784591\n",
      "cosine similarity between row 19 and row 8 is 0.7067391127072453\n",
      "cosine similarity between row 19 and row 9 is 0.7177403653542398\n",
      "cosine similarity between row 19 and row 10 is 0.697142077764459\n",
      "cosine similarity between row 19 and row 11 is 0.6909158904929513\n",
      "cosine similarity between row 19 and row 12 is 0.706069363218688\n",
      "cosine similarity between row 19 and row 13 is 0.686466141470319\n",
      "cosine similarity between row 19 and row 14 is 0.6767285862049294\n",
      "cosine similarity between row 19 and row 15 is 0.6681237916242181\n",
      "cosine similarity between row 19 and row 16 is 0.6956424554097146\n",
      "cosine similarity between row 19 and row 17 is 0.712852860354865\n",
      "cosine similarity between row 19 and row 18 is 0.6846992829156073\n",
      "cosine similarity between row 20 and row 0 is 0.6633300804044492\n",
      "cosine similarity between row 20 and row 1 is 0.6749150111936834\n",
      "cosine similarity between row 20 and row 2 is 0.6816177102948098\n",
      "cosine similarity between row 20 and row 3 is 0.6702210271244264\n",
      "cosine similarity between row 20 and row 4 is 0.6822083309268501\n",
      "cosine similarity between row 20 and row 5 is 0.6749916929527567\n",
      "cosine similarity between row 20 and row 6 is 0.6784449748771012\n",
      "cosine similarity between row 20 and row 7 is 0.7024260722051905\n",
      "cosine similarity between row 20 and row 8 is 0.6943003184708243\n",
      "cosine similarity between row 20 and row 9 is 0.6683284845210671\n",
      "cosine similarity between row 20 and row 10 is 0.6688894569133663\n",
      "cosine similarity between row 20 and row 11 is 0.7028846076856524\n",
      "cosine similarity between row 20 and row 12 is 0.677449740246285\n",
      "cosine similarity between row 20 and row 13 is 0.6765777136939879\n",
      "cosine similarity between row 20 and row 14 is 0.6556294170494176\n",
      "cosine similarity between row 20 and row 15 is 0.6732612017283919\n",
      "cosine similarity between row 20 and row 16 is 0.6701377671922919\n",
      "cosine similarity between row 20 and row 17 is 0.6670206695105\n",
      "cosine similarity between row 20 and row 18 is 0.671503073339373\n",
      "cosine similarity between row 20 and row 19 is 0.6617162390436337\n",
      "cosine similarity between row 21 and row 0 is 0.6789575614669455\n",
      "cosine similarity between row 21 and row 1 is 0.6889167258242098\n",
      "cosine similarity between row 21 and row 2 is 0.6932715155590158\n",
      "cosine similarity between row 21 and row 3 is 0.6868591589393465\n",
      "cosine similarity between row 21 and row 4 is 0.6827829901305588\n",
      "cosine similarity between row 21 and row 5 is 0.6779915503453745\n",
      "cosine similarity between row 21 and row 6 is 0.6931877346505695\n",
      "cosine similarity between row 21 and row 7 is 0.7041621058790298\n",
      "cosine similarity between row 21 and row 8 is 0.6985446881267369\n",
      "cosine similarity between row 21 and row 9 is 0.6794447876144032\n",
      "cosine similarity between row 21 and row 10 is 0.6923061662781065\n",
      "cosine similarity between row 21 and row 11 is 0.7088981872749734\n",
      "cosine similarity between row 21 and row 12 is 0.7070138877267643\n",
      "cosine similarity between row 21 and row 13 is 0.6929070541383886\n",
      "cosine similarity between row 21 and row 14 is 0.6867776725542364\n",
      "cosine similarity between row 21 and row 15 is 0.6715961731717102\n",
      "cosine similarity between row 21 and row 16 is 0.6956971873002102\n",
      "cosine similarity between row 21 and row 17 is 0.6965902732297804\n",
      "cosine similarity between row 21 and row 18 is 0.6799983017753524\n",
      "cosine similarity between row 21 and row 19 is 0.6990379613553528\n",
      "cosine similarity between row 21 and row 20 is 0.6788907670857504\n",
      "cosine similarity between row 22 and row 0 is 0.676645248340844\n",
      "cosine similarity between row 22 and row 1 is 0.6820900877264068\n",
      "cosine similarity between row 22 and row 2 is 0.6790258524172224\n",
      "cosine similarity between row 22 and row 3 is 0.6942522562811679\n",
      "cosine similarity between row 22 and row 4 is 0.6993321481705245\n",
      "cosine similarity between row 22 and row 5 is 0.6861945044699065\n",
      "cosine similarity between row 22 and row 6 is 0.6793841070958611\n",
      "cosine similarity between row 22 and row 7 is 0.6986716120601328\n",
      "cosine similarity between row 22 and row 8 is 0.6956937068928741\n",
      "cosine similarity between row 22 and row 9 is 0.6786533495457072\n",
      "cosine similarity between row 22 and row 10 is 0.698427070251518\n",
      "cosine similarity between row 22 and row 11 is 0.7046406428760408\n",
      "cosine similarity between row 22 and row 12 is 0.6857773842643589\n",
      "cosine similarity between row 22 and row 13 is 0.6692968837721673\n",
      "cosine similarity between row 22 and row 14 is 0.6720559560644344\n",
      "cosine similarity between row 22 and row 15 is 0.6663209614167577\n",
      "cosine similarity between row 22 and row 16 is 0.6857104899284137\n",
      "cosine similarity between row 22 and row 17 is 0.7030690177262063\n",
      "cosine similarity between row 22 and row 18 is 0.6666449218040218\n",
      "cosine similarity between row 22 and row 19 is 0.7057115033331444\n",
      "cosine similarity between row 22 and row 20 is 0.6802712163229284\n",
      "cosine similarity between row 22 and row 21 is 0.6895145199798846\n",
      "cosine similarity between row 23 and row 0 is 0.6709479916992711\n",
      "cosine similarity between row 23 and row 1 is 0.6867738213783587\n",
      "cosine similarity between row 23 and row 2 is 0.6718087626886154\n",
      "cosine similarity between row 23 and row 3 is 0.6841767380371844\n",
      "cosine similarity between row 23 and row 4 is 0.6966360507997074\n",
      "cosine similarity between row 23 and row 5 is 0.679530955186144\n",
      "cosine similarity between row 23 and row 6 is 0.681591093943291\n",
      "cosine similarity between row 23 and row 7 is 0.7082381611528188\n",
      "cosine similarity between row 23 and row 8 is 0.6729899191774085\n",
      "cosine similarity between row 23 and row 9 is 0.6994412936873105\n",
      "cosine similarity between row 23 and row 10 is 0.6789810477633059\n",
      "cosine similarity between row 23 and row 11 is 0.6950936936068478\n",
      "cosine similarity between row 23 and row 12 is 0.6722116083963144\n",
      "cosine similarity between row 23 and row 13 is 0.6733209219839714\n",
      "cosine similarity between row 23 and row 14 is 0.6730614492881634\n",
      "cosine similarity between row 23 and row 15 is 0.6676220350900457\n",
      "cosine similarity between row 23 and row 16 is 0.6783004257130563\n",
      "cosine similarity between row 23 and row 17 is 0.6827953633256583\n",
      "cosine similarity between row 23 and row 18 is 0.680981879008886\n",
      "cosine similarity between row 23 and row 19 is 0.6864834197334417\n",
      "cosine similarity between row 23 and row 20 is 0.6620954277411243\n",
      "cosine similarity between row 23 and row 21 is 0.6754187773536438\n",
      "cosine similarity between row 23 and row 22 is 0.6799221985338091\n",
      "cosine similarity between row 24 and row 0 is 0.6627005028220477\n",
      "cosine similarity between row 24 and row 1 is 0.6705744859273391\n",
      "cosine similarity between row 24 and row 2 is 0.6874211629152728\n",
      "cosine similarity between row 24 and row 3 is 0.6692750903063919\n",
      "cosine similarity between row 24 and row 4 is 0.679842047967171\n",
      "cosine similarity between row 24 and row 5 is 0.6748705175885601\n",
      "cosine similarity between row 24 and row 6 is 0.6748377546579728\n",
      "cosine similarity between row 24 and row 7 is 0.7003879289582813\n",
      "cosine similarity between row 24 and row 8 is 0.6882750050496023\n",
      "cosine similarity between row 24 and row 9 is 0.6748061487155915\n",
      "cosine similarity between row 24 and row 10 is 0.6527029244738242\n",
      "cosine similarity between row 24 and row 11 is 0.6956123799812328\n",
      "cosine similarity between row 24 and row 12 is 0.6707901391508075\n",
      "cosine similarity between row 24 and row 13 is 0.6618851966434558\n",
      "cosine similarity between row 24 and row 14 is 0.6567784183317275\n",
      "cosine similarity between row 24 and row 15 is 0.6443187834378066\n",
      "cosine similarity between row 24 and row 16 is 0.6709466610717479\n",
      "cosine similarity between row 24 and row 17 is 0.6693663869051307\n",
      "cosine similarity between row 24 and row 18 is 0.6467814452289978\n",
      "cosine similarity between row 24 and row 19 is 0.66946786594984\n",
      "cosine similarity between row 24 and row 20 is 0.6615560455859293\n",
      "cosine similarity between row 24 and row 21 is 0.6679410390576395\n",
      "cosine similarity between row 24 and row 22 is 0.672259767541266\n",
      "cosine similarity between row 24 and row 23 is 0.6760904426992753\n",
      "cosine similarity between row 25 and row 0 is 0.6738579185038163\n",
      "cosine similarity between row 25 and row 1 is 0.6984958585624087\n",
      "cosine similarity between row 25 and row 2 is 0.6813934922298456\n",
      "cosine similarity between row 25 and row 3 is 0.66197102600012\n",
      "cosine similarity between row 25 and row 4 is 0.7033349332649945\n",
      "cosine similarity between row 25 and row 5 is 0.6830024147534146\n",
      "cosine similarity between row 25 and row 6 is 0.6583470168886393\n",
      "cosine similarity between row 25 and row 7 is 0.7060067368632402\n",
      "cosine similarity between row 25 and row 8 is 0.6939663200791113\n",
      "cosine similarity between row 25 and row 9 is 0.6841499870517498\n",
      "cosine similarity between row 25 and row 10 is 0.6954921793028003\n",
      "cosine similarity between row 25 and row 11 is 0.6887871999398597\n",
      "cosine similarity between row 25 and row 12 is 0.6825238360981222\n",
      "cosine similarity between row 25 and row 13 is 0.6895508563835145\n",
      "cosine similarity between row 25 and row 14 is 0.6841393084109031\n",
      "cosine similarity between row 25 and row 15 is 0.6574415502660333\n",
      "cosine similarity between row 25 and row 16 is 0.6791745257364378\n",
      "cosine similarity between row 25 and row 17 is 0.6772807955514384\n",
      "cosine similarity between row 25 and row 18 is 0.6890333360478138\n",
      "cosine similarity between row 25 and row 19 is 0.6824805618074837\n",
      "cosine similarity between row 25 and row 20 is 0.679786673942983\n",
      "cosine similarity between row 25 and row 21 is 0.6765407912431554\n",
      "cosine similarity between row 25 and row 22 is 0.6841212673583085\n",
      "cosine similarity between row 25 and row 23 is 0.6754812696862856\n",
      "cosine similarity between row 25 and row 24 is 0.6811574184902807\n",
      "cosine similarity between row 26 and row 0 is 0.6687750837900789\n",
      "cosine similarity between row 26 and row 1 is 0.6946048735746565\n",
      "cosine similarity between row 26 and row 2 is 0.6925048221892299\n",
      "cosine similarity between row 26 and row 3 is 0.6841916967694534\n",
      "cosine similarity between row 26 and row 4 is 0.7033869180905391\n",
      "cosine similarity between row 26 and row 5 is 0.6819880539870958\n",
      "cosine similarity between row 26 and row 6 is 0.6909839281776357\n",
      "cosine similarity between row 26 and row 7 is 0.7036344484915759\n",
      "cosine similarity between row 26 and row 8 is 0.6866098384167302\n",
      "cosine similarity between row 26 and row 9 is 0.694950216696793\n",
      "cosine similarity between row 26 and row 10 is 0.6743946985420693\n",
      "cosine similarity between row 26 and row 11 is 0.7021426653710624\n",
      "cosine similarity between row 26 and row 12 is 0.692564761754512\n",
      "cosine similarity between row 26 and row 13 is 0.6869323548583258\n",
      "cosine similarity between row 26 and row 14 is 0.6865305777917173\n",
      "cosine similarity between row 26 and row 15 is 0.6650447292087797\n",
      "cosine similarity between row 26 and row 16 is 0.6880187140829097\n",
      "cosine similarity between row 26 and row 17 is 0.6979244411590388\n",
      "cosine similarity between row 26 and row 18 is 0.7005793327221318\n",
      "cosine similarity between row 26 and row 19 is 0.721885770088287\n",
      "cosine similarity between row 26 and row 20 is 0.6773124690948558\n",
      "cosine similarity between row 26 and row 21 is 0.7036293820003944\n",
      "cosine similarity between row 26 and row 22 is 0.6845005382081454\n",
      "cosine similarity between row 26 and row 23 is 0.702396991888358\n",
      "cosine similarity between row 26 and row 24 is 0.6683809105733712\n",
      "cosine similarity between row 26 and row 25 is 0.6978174321055944\n",
      "cosine similarity between row 27 and row 0 is 0.670346417856271\n",
      "cosine similarity between row 27 and row 1 is 0.687200107481187\n",
      "cosine similarity between row 27 and row 2 is 0.6910770666955574\n",
      "cosine similarity between row 27 and row 3 is 0.6791898579760361\n",
      "cosine similarity between row 27 and row 4 is 0.6917022938080234\n",
      "cosine similarity between row 27 and row 5 is 0.6849305539866949\n",
      "cosine similarity between row 27 and row 6 is 0.6980411352455224\n",
      "cosine similarity between row 27 and row 7 is 0.7005254677963245\n",
      "cosine similarity between row 27 and row 8 is 0.6982779105771825\n",
      "cosine similarity between row 27 and row 9 is 0.7131956682689122\n",
      "cosine similarity between row 27 and row 10 is 0.7010236272121634\n",
      "cosine similarity between row 27 and row 11 is 0.6748709892860322\n",
      "cosine similarity between row 27 and row 12 is 0.6920983303199241\n",
      "cosine similarity between row 27 and row 13 is 0.7025992906094902\n",
      "cosine similarity between row 27 and row 14 is 0.6712511104900082\n",
      "cosine similarity between row 27 and row 15 is 0.6775720393440693\n",
      "cosine similarity between row 27 and row 16 is 0.6839176007893669\n",
      "cosine similarity between row 27 and row 17 is 0.6893562793109229\n",
      "cosine similarity between row 27 and row 18 is 0.6870697957071819\n",
      "cosine similarity between row 27 and row 19 is 0.6867357626452135\n",
      "cosine similarity between row 27 and row 20 is 0.6819200554158132\n",
      "cosine similarity between row 27 and row 21 is 0.6966154314302492\n",
      "cosine similarity between row 27 and row 22 is 0.6779790403642579\n",
      "cosine similarity between row 27 and row 23 is 0.6744478242332818\n",
      "cosine similarity between row 27 and row 24 is 0.6887640795866828\n",
      "cosine similarity between row 27 and row 25 is 0.6911333036860932\n",
      "cosine similarity between row 27 and row 26 is 0.6824754982895856\n",
      "cosine similarity between row 28 and row 0 is 0.6491468788594865\n",
      "cosine similarity between row 28 and row 1 is 0.6700272384935547\n",
      "cosine similarity between row 28 and row 2 is 0.6532966872340258\n",
      "cosine similarity between row 28 and row 3 is 0.6668871511072931\n",
      "cosine similarity between row 28 and row 4 is 0.6673017315129961\n",
      "cosine similarity between row 28 and row 5 is 0.6647180784145548\n",
      "cosine similarity between row 28 and row 6 is 0.6539315187780265\n",
      "cosine similarity between row 28 and row 7 is 0.6824547178944713\n",
      "cosine similarity between row 28 and row 8 is 0.6771913859600504\n",
      "cosine similarity between row 28 and row 9 is 0.6723442705430482\n",
      "cosine similarity between row 28 and row 10 is 0.6720081345080079\n",
      "cosine similarity between row 28 and row 11 is 0.673161145535363\n",
      "cosine similarity between row 28 and row 12 is 0.6609509436650622\n",
      "cosine similarity between row 28 and row 13 is 0.6669995457098832\n",
      "cosine similarity between row 28 and row 14 is 0.6636129934680829\n",
      "cosine similarity between row 28 and row 15 is 0.6460791143982557\n",
      "cosine similarity between row 28 and row 16 is 0.6733262178485208\n",
      "cosine similarity between row 28 and row 17 is 0.6882158012770059\n",
      "cosine similarity between row 28 and row 18 is 0.6881864520494914\n",
      "cosine similarity between row 28 and row 19 is 0.6799482366657638\n",
      "cosine similarity between row 28 and row 20 is 0.6454176128365519\n",
      "cosine similarity between row 28 and row 21 is 0.6594971931088885\n",
      "cosine similarity between row 28 and row 22 is 0.6669401802263681\n",
      "cosine similarity between row 28 and row 23 is 0.6892598138867453\n",
      "cosine similarity between row 28 and row 24 is 0.6451921005331567\n",
      "cosine similarity between row 28 and row 25 is 0.6715273857171198\n",
      "cosine similarity between row 28 and row 26 is 0.6885675776684765\n",
      "cosine similarity between row 28 and row 27 is 0.6733030984608105\n",
      "cosine similarity between row 29 and row 0 is 0.6553592242215514\n",
      "cosine similarity between row 29 and row 1 is 0.6531648756462529\n",
      "cosine similarity between row 29 and row 2 is 0.6660590394677187\n",
      "cosine similarity between row 29 and row 3 is 0.6688759016762025\n",
      "cosine similarity between row 29 and row 4 is 0.6739231686208942\n",
      "cosine similarity between row 29 and row 5 is 0.6620375605501165\n",
      "cosine similarity between row 29 and row 6 is 0.6697259965711497\n",
      "cosine similarity between row 29 and row 7 is 0.6757154760922107\n",
      "cosine similarity between row 29 and row 8 is 0.6827152489016831\n",
      "cosine similarity between row 29 and row 9 is 0.6886921018015915\n",
      "cosine similarity between row 29 and row 10 is 0.6683364176151679\n",
      "cosine similarity between row 29 and row 11 is 0.6817241311527257\n",
      "cosine similarity between row 29 and row 12 is 0.6851102603196038\n",
      "cosine similarity between row 29 and row 13 is 0.6849297741105701\n",
      "cosine similarity between row 29 and row 14 is 0.6632532671323679\n",
      "cosine similarity between row 29 and row 15 is 0.6412250163641613\n",
      "cosine similarity between row 29 and row 16 is 0.6622978805694453\n",
      "cosine similarity between row 29 and row 17 is 0.6658725077259668\n",
      "cosine similarity between row 29 and row 18 is 0.6711121549233849\n",
      "cosine similarity between row 29 and row 19 is 0.6678271583466947\n",
      "cosine similarity between row 29 and row 20 is 0.645850429408444\n",
      "cosine similarity between row 29 and row 21 is 0.6820027209186305\n",
      "cosine similarity between row 29 and row 22 is 0.6788925486665253\n",
      "cosine similarity between row 29 and row 23 is 0.6718690508090518\n",
      "cosine similarity between row 29 and row 24 is 0.6550342971595539\n",
      "cosine similarity between row 29 and row 25 is 0.6850783615356566\n",
      "cosine similarity between row 29 and row 26 is 0.6736946022771106\n",
      "cosine similarity between row 29 and row 27 is 0.6925986653439068\n",
      "cosine similarity between row 29 and row 28 is 0.6272515088804644\n",
      "cosine similarity between row 30 and row 0 is 0.6564438114082365\n",
      "cosine similarity between row 30 and row 1 is 0.679134855913559\n",
      "cosine similarity between row 30 and row 2 is 0.6930431309430143\n",
      "cosine similarity between row 30 and row 3 is 0.6848448299012343\n",
      "cosine similarity between row 30 and row 4 is 0.7016404949284772\n",
      "cosine similarity between row 30 and row 5 is 0.7014086201190167\n",
      "cosine similarity between row 30 and row 6 is 0.6853772454922098\n",
      "cosine similarity between row 30 and row 7 is 0.6844536526620411\n",
      "cosine similarity between row 30 and row 8 is 0.7083143765131605\n",
      "cosine similarity between row 30 and row 9 is 0.6972432914683905\n",
      "cosine similarity between row 30 and row 10 is 0.6655790497778075\n",
      "cosine similarity between row 30 and row 11 is 0.6875512120289795\n",
      "cosine similarity between row 30 and row 12 is 0.6798612887109458\n",
      "cosine similarity between row 30 and row 13 is 0.6756397747423278\n",
      "cosine similarity between row 30 and row 14 is 0.6763853061529277\n",
      "cosine similarity between row 30 and row 15 is 0.6556737697831749\n",
      "cosine similarity between row 30 and row 16 is 0.6893213465222761\n",
      "cosine similarity between row 30 and row 17 is 0.7000228923459977\n",
      "cosine similarity between row 30 and row 18 is 0.6714512780094566\n",
      "cosine similarity between row 30 and row 19 is 0.7101790046334294\n",
      "cosine similarity between row 30 and row 20 is 0.6757142119280884\n",
      "cosine similarity between row 30 and row 21 is 0.697309160162751\n",
      "cosine similarity between row 30 and row 22 is 0.6949453291941194\n",
      "cosine similarity between row 30 and row 23 is 0.6955680609159307\n",
      "cosine similarity between row 30 and row 24 is 0.6582644858560431\n",
      "cosine similarity between row 30 and row 25 is 0.6900538046091286\n",
      "cosine similarity between row 30 and row 26 is 0.6887173931668145\n",
      "cosine similarity between row 30 and row 27 is 0.7021876788596766\n",
      "cosine similarity between row 30 and row 28 is 0.667365605782469\n",
      "cosine similarity between row 30 and row 29 is 0.6797528956576694\n",
      "cosine similarity between row 31 and row 0 is 0.6685685476438706\n",
      "cosine similarity between row 31 and row 1 is 0.6810729598697153\n",
      "cosine similarity between row 31 and row 2 is 0.6948478268608301\n",
      "cosine similarity between row 31 and row 3 is 0.6957169945071441\n",
      "cosine similarity between row 31 and row 4 is 0.6855588405898546\n",
      "cosine similarity between row 31 and row 5 is 0.6834568296755009\n",
      "cosine similarity between row 31 and row 6 is 0.681834033863555\n",
      "cosine similarity between row 31 and row 7 is 0.6904736335903593\n",
      "cosine similarity between row 31 and row 8 is 0.696272825669595\n",
      "cosine similarity between row 31 and row 9 is 0.6942706354357319\n",
      "cosine similarity between row 31 and row 10 is 0.6688566783514437\n",
      "cosine similarity between row 31 and row 11 is 0.703882076708548\n",
      "cosine similarity between row 31 and row 12 is 0.681088852399039\n",
      "cosine similarity between row 31 and row 13 is 0.6814589892952256\n",
      "cosine similarity between row 31 and row 14 is 0.6871758751082552\n",
      "cosine similarity between row 31 and row 15 is 0.6894523405063726\n",
      "cosine similarity between row 31 and row 16 is 0.6729653365942818\n",
      "cosine similarity between row 31 and row 17 is 0.6732943507994222\n",
      "cosine similarity between row 31 and row 18 is 0.6833082719378625\n",
      "cosine similarity between row 31 and row 19 is 0.6863150681603079\n",
      "cosine similarity between row 31 and row 20 is 0.657125466933472\n",
      "cosine similarity between row 31 and row 21 is 0.6842512081825924\n",
      "cosine similarity between row 31 and row 22 is 0.6792254600274358\n",
      "cosine similarity between row 31 and row 23 is 0.7010575146478993\n",
      "cosine similarity between row 31 and row 24 is 0.6715590118364749\n",
      "cosine similarity between row 31 and row 25 is 0.6941484990733136\n",
      "cosine similarity between row 31 and row 26 is 0.7013673652634108\n",
      "cosine similarity between row 31 and row 27 is 0.6850727978634026\n",
      "cosine similarity between row 31 and row 28 is 0.6690678448484023\n",
      "cosine similarity between row 31 and row 29 is 0.6915345920055519\n",
      "cosine similarity between row 31 and row 30 is 0.6845961618616822\n",
      "cosine similarity between row 32 and row 0 is 0.6637630391253954\n",
      "cosine similarity between row 32 and row 1 is 0.70459363245675\n",
      "cosine similarity between row 32 and row 2 is 0.6880730318170935\n",
      "cosine similarity between row 32 and row 3 is 0.6652056389714115\n",
      "cosine similarity between row 32 and row 4 is 0.6854517587825951\n",
      "cosine similarity between row 32 and row 5 is 0.6586777628445094\n",
      "cosine similarity between row 32 and row 6 is 0.6705733914814467\n",
      "cosine similarity between row 32 and row 7 is 0.7104023077119167\n",
      "cosine similarity between row 32 and row 8 is 0.7167475600778052\n",
      "cosine similarity between row 32 and row 9 is 0.6892562522984925\n",
      "cosine similarity between row 32 and row 10 is 0.6815854112039949\n",
      "cosine similarity between row 32 and row 11 is 0.7014424301748904\n",
      "cosine similarity between row 32 and row 12 is 0.6917979634778259\n",
      "cosine similarity between row 32 and row 13 is 0.6841965447651663\n",
      "cosine similarity between row 32 and row 14 is 0.6823692459995583\n",
      "cosine similarity between row 32 and row 15 is 0.66820316340116\n",
      "cosine similarity between row 32 and row 16 is 0.6969618223581174\n",
      "cosine similarity between row 32 and row 17 is 0.6817315682759459\n",
      "cosine similarity between row 32 and row 18 is 0.6733621657149786\n",
      "cosine similarity between row 32 and row 19 is 0.6986567018186255\n",
      "cosine similarity between row 32 and row 20 is 0.6488973239676323\n",
      "cosine similarity between row 32 and row 21 is 0.691655520203497\n",
      "cosine similarity between row 32 and row 22 is 0.6821304155257345\n",
      "cosine similarity between row 32 and row 23 is 0.6768948920990585\n",
      "cosine similarity between row 32 and row 24 is 0.6695083776699748\n",
      "cosine similarity between row 32 and row 25 is 0.681447359648876\n",
      "cosine similarity between row 32 and row 26 is 0.6713797474939253\n",
      "cosine similarity between row 32 and row 27 is 0.6865128326785171\n",
      "cosine similarity between row 32 and row 28 is 0.6712190523269574\n",
      "cosine similarity between row 32 and row 29 is 0.6602294087360995\n",
      "cosine similarity between row 32 and row 30 is 0.6940614446306653\n",
      "cosine similarity between row 32 and row 31 is 0.6667156548235325\n",
      "cosine similarity between row 33 and row 0 is 0.6751535011996446\n",
      "cosine similarity between row 33 and row 1 is 0.6856589980649324\n",
      "cosine similarity between row 33 and row 2 is 0.6889068366919936\n",
      "cosine similarity between row 33 and row 3 is 0.6825789180347971\n",
      "cosine similarity between row 33 and row 4 is 0.6935145206993695\n",
      "cosine similarity between row 33 and row 5 is 0.6864798639578142\n",
      "cosine similarity between row 33 and row 6 is 0.6715989347483099\n",
      "cosine similarity between row 33 and row 7 is 0.6906142320269074\n",
      "cosine similarity between row 33 and row 8 is 0.6874197009671866\n",
      "cosine similarity between row 33 and row 9 is 0.6931279897502024\n",
      "cosine similarity between row 33 and row 10 is 0.6880357671740184\n",
      "cosine similarity between row 33 and row 11 is 0.6885551028613448\n",
      "cosine similarity between row 33 and row 12 is 0.6620290661968525\n",
      "cosine similarity between row 33 and row 13 is 0.6559022560918216\n",
      "cosine similarity between row 33 and row 14 is 0.6777312412015076\n",
      "cosine similarity between row 33 and row 15 is 0.67140139264139\n",
      "cosine similarity between row 33 and row 16 is 0.6877586677048698\n",
      "cosine similarity between row 33 and row 17 is 0.6897379428386248\n",
      "cosine similarity between row 33 and row 18 is 0.6727030369714828\n",
      "cosine similarity between row 33 and row 19 is 0.6828293099050907\n",
      "cosine similarity between row 33 and row 20 is 0.679847944830315\n",
      "cosine similarity between row 33 and row 21 is 0.6944263643574087\n",
      "cosine similarity between row 33 and row 22 is 0.6906295567433258\n",
      "cosine similarity between row 33 and row 23 is 0.6778958587751297\n",
      "cosine similarity between row 33 and row 24 is 0.6743053863563245\n",
      "cosine similarity between row 33 and row 25 is 0.7007377068017194\n",
      "cosine similarity between row 33 and row 26 is 0.6966321381826317\n",
      "cosine similarity between row 33 and row 27 is 0.6795954928254568\n",
      "cosine similarity between row 33 and row 28 is 0.6473971794450969\n",
      "cosine similarity between row 33 and row 29 is 0.6775719792304086\n",
      "cosine similarity between row 33 and row 30 is 0.683156621225467\n",
      "cosine similarity between row 33 and row 31 is 0.6697734410169647\n",
      "cosine similarity between row 33 and row 32 is 0.6704723492069937\n",
      "cosine similarity between row 34 and row 0 is 0.6721237230017674\n",
      "cosine similarity between row 34 and row 1 is 0.6878000131482845\n",
      "cosine similarity between row 34 and row 2 is 0.6852180269835193\n",
      "cosine similarity between row 34 and row 3 is 0.6767452113046769\n",
      "cosine similarity between row 34 and row 4 is 0.6816570888976893\n",
      "cosine similarity between row 34 and row 5 is 0.6776789326750035\n",
      "cosine similarity between row 34 and row 6 is 0.6963582006725214\n",
      "cosine similarity between row 34 and row 7 is 0.6937596047780854\n",
      "cosine similarity between row 34 and row 8 is 0.6934026294889051\n",
      "cosine similarity between row 34 and row 9 is 0.710795287667841\n",
      "cosine similarity between row 34 and row 10 is 0.6895648203196616\n",
      "cosine similarity between row 34 and row 11 is 0.6909477043416515\n",
      "cosine similarity between row 34 and row 12 is 0.6804784489530382\n",
      "cosine similarity between row 34 and row 13 is 0.6847081812362324\n",
      "cosine similarity between row 34 and row 14 is 0.6882234833748228\n",
      "cosine similarity between row 34 and row 15 is 0.6740427369114361\n",
      "cosine similarity between row 34 and row 16 is 0.6856698419266208\n",
      "cosine similarity between row 34 and row 17 is 0.6781428413000102\n",
      "cosine similarity between row 34 and row 18 is 0.6737677301052656\n",
      "cosine similarity between row 34 and row 19 is 0.6965023652089816\n",
      "cosine similarity between row 34 and row 20 is 0.6684717237264651\n",
      "cosine similarity between row 34 and row 21 is 0.6858748046021652\n",
      "cosine similarity between row 34 and row 22 is 0.694156727287271\n",
      "cosine similarity between row 34 and row 23 is 0.6960069522278177\n",
      "cosine similarity between row 34 and row 24 is 0.6509086112231611\n",
      "cosine similarity between row 34 and row 25 is 0.6787723847897251\n",
      "cosine similarity between row 34 and row 26 is 0.6860319342435508\n",
      "cosine similarity between row 34 and row 27 is 0.677721112790993\n",
      "cosine similarity between row 34 and row 28 is 0.668804422428049\n",
      "cosine similarity between row 34 and row 29 is 0.6681800421241486\n",
      "cosine similarity between row 34 and row 30 is 0.6890698362579508\n",
      "cosine similarity between row 34 and row 31 is 0.6874441291225194\n",
      "cosine similarity between row 34 and row 32 is 0.6810132101084212\n",
      "cosine similarity between row 34 and row 33 is 0.6869470601014412\n",
      "cosine similarity between row 35 and row 0 is 0.6685138540203064\n",
      "cosine similarity between row 35 and row 1 is 0.6909038330441956\n",
      "cosine similarity between row 35 and row 2 is 0.6926235035179431\n",
      "cosine similarity between row 35 and row 3 is 0.6837955434510622\n",
      "cosine similarity between row 35 and row 4 is 0.6855637867037402\n",
      "cosine similarity between row 35 and row 5 is 0.6759922364896801\n",
      "cosine similarity between row 35 and row 6 is 0.6869435258171639\n",
      "cosine similarity between row 35 and row 7 is 0.7040592778650746\n",
      "cosine similarity between row 35 and row 8 is 0.6992636964338766\n",
      "cosine similarity between row 35 and row 9 is 0.7007216664955493\n",
      "cosine similarity between row 35 and row 10 is 0.6867383538637741\n",
      "cosine similarity between row 35 and row 11 is 0.692575415273143\n",
      "cosine similarity between row 35 and row 12 is 0.7111137276244414\n",
      "cosine similarity between row 35 and row 13 is 0.687375980809782\n",
      "cosine similarity between row 35 and row 14 is 0.6774749753044849\n",
      "cosine similarity between row 35 and row 15 is 0.6940973161860958\n",
      "cosine similarity between row 35 and row 16 is 0.6800043238542615\n",
      "cosine similarity between row 35 and row 17 is 0.6814222575275776\n",
      "cosine similarity between row 35 and row 18 is 0.6949857895993092\n",
      "cosine similarity between row 35 and row 19 is 0.6977838028988655\n",
      "cosine similarity between row 35 and row 20 is 0.6875794896012588\n",
      "cosine similarity between row 35 and row 21 is 0.678807949099671\n",
      "cosine similarity between row 35 and row 22 is 0.6901125276859698\n",
      "cosine similarity between row 35 and row 23 is 0.6664414448111973\n",
      "cosine similarity between row 35 and row 24 is 0.6767516125710007\n",
      "cosine similarity between row 35 and row 25 is 0.6861974167176504\n",
      "cosine similarity between row 35 and row 26 is 0.6899278719800516\n",
      "cosine similarity between row 35 and row 27 is 0.6946280468929676\n",
      "cosine similarity between row 35 and row 28 is 0.675523368879794\n",
      "cosine similarity between row 35 and row 29 is 0.6693852082232334\n",
      "cosine similarity between row 35 and row 30 is 0.6918735589479682\n",
      "cosine similarity between row 35 and row 31 is 0.6874606819436726\n",
      "cosine similarity between row 35 and row 32 is 0.693658525944391\n",
      "cosine similarity between row 35 and row 33 is 0.6844995398549407\n",
      "cosine similarity between row 35 and row 34 is 0.6958762508152132\n",
      "cosine similarity between row 36 and row 0 is 0.6738860883456492\n",
      "cosine similarity between row 36 and row 1 is 0.6884928141159101\n",
      "cosine similarity between row 36 and row 2 is 0.698203634334369\n",
      "cosine similarity between row 36 and row 3 is 0.6568710630623346\n",
      "cosine similarity between row 36 and row 4 is 0.6921206365883219\n",
      "cosine similarity between row 36 and row 5 is 0.6835084429439449\n",
      "cosine similarity between row 36 and row 6 is 0.6909517830103135\n",
      "cosine similarity between row 36 and row 7 is 0.7071162576917892\n",
      "cosine similarity between row 36 and row 8 is 0.6697345117255735\n",
      "cosine similarity between row 36 and row 9 is 0.6987415455575752\n",
      "cosine similarity between row 36 and row 10 is 0.6815891299880903\n",
      "cosine similarity between row 36 and row 11 is 0.6813605551388006\n",
      "cosine similarity between row 36 and row 12 is 0.677499749552776\n",
      "cosine similarity between row 36 and row 13 is 0.6649977160933844\n",
      "cosine similarity between row 36 and row 14 is 0.6802776139695762\n",
      "cosine similarity between row 36 and row 15 is 0.6821894474480789\n",
      "cosine similarity between row 36 and row 16 is 0.6742728755357553\n",
      "cosine similarity between row 36 and row 17 is 0.6752792778770207\n",
      "cosine similarity between row 36 and row 18 is 0.666568157728458\n",
      "cosine similarity between row 36 and row 19 is 0.6942245545759475\n",
      "cosine similarity between row 36 and row 20 is 0.6629230910551572\n",
      "cosine similarity between row 36 and row 21 is 0.6639266810580808\n",
      "cosine similarity between row 36 and row 22 is 0.6863152160191981\n",
      "cosine similarity between row 36 and row 23 is 0.6833813552857356\n",
      "cosine similarity between row 36 and row 24 is 0.6769709486878587\n",
      "cosine similarity between row 36 and row 25 is 0.7021125325424014\n",
      "cosine similarity between row 36 and row 26 is 0.6745063724220216\n",
      "cosine similarity between row 36 and row 27 is 0.693409411085394\n",
      "cosine similarity between row 36 and row 28 is 0.6753045167536874\n",
      "cosine similarity between row 36 and row 29 is 0.673826956613687\n",
      "cosine similarity between row 36 and row 30 is 0.6811070225039407\n",
      "cosine similarity between row 36 and row 31 is 0.676837596746906\n",
      "cosine similarity between row 36 and row 32 is 0.6686412568837948\n",
      "cosine similarity between row 36 and row 33 is 0.6897943128193429\n",
      "cosine similarity between row 36 and row 34 is 0.6776641581239222\n",
      "cosine similarity between row 36 and row 35 is 0.6847727217980439\n",
      "cosine similarity between row 37 and row 0 is 0.6623756970728031\n",
      "cosine similarity between row 37 and row 1 is 0.6753642341790147\n",
      "cosine similarity between row 37 and row 2 is 0.6743081816115933\n",
      "cosine similarity between row 37 and row 3 is 0.6681957918959611\n",
      "cosine similarity between row 37 and row 4 is 0.6811250873572369\n",
      "cosine similarity between row 37 and row 5 is 0.6729358414622535\n",
      "cosine similarity between row 37 and row 6 is 0.6672137166484362\n",
      "cosine similarity between row 37 and row 7 is 0.6853167127717621\n",
      "cosine similarity between row 37 and row 8 is 0.6690954454175205\n",
      "cosine similarity between row 37 and row 9 is 0.6840351455801795\n",
      "cosine similarity between row 37 and row 10 is 0.6866463162762119\n",
      "cosine similarity between row 37 and row 11 is 0.6893917496509783\n",
      "cosine similarity between row 37 and row 12 is 0.6669317600939484\n",
      "cosine similarity between row 37 and row 13 is 0.6826268533153559\n",
      "cosine similarity between row 37 and row 14 is 0.6663651944229229\n",
      "cosine similarity between row 37 and row 15 is 0.6543475498584291\n",
      "cosine similarity between row 37 and row 16 is 0.6546565829195843\n",
      "cosine similarity between row 37 and row 17 is 0.656480075974868\n",
      "cosine similarity between row 37 and row 18 is 0.6691488141992622\n",
      "cosine similarity between row 37 and row 19 is 0.6613972219755428\n",
      "cosine similarity between row 37 and row 20 is 0.6617650465321309\n",
      "cosine similarity between row 37 and row 21 is 0.6874316558652667\n",
      "cosine similarity between row 37 and row 22 is 0.6717599488733904\n",
      "cosine similarity between row 37 and row 23 is 0.6844485042818903\n",
      "cosine similarity between row 37 and row 24 is 0.6650343243475254\n",
      "cosine similarity between row 37 and row 25 is 0.6919828949967206\n",
      "cosine similarity between row 37 and row 26 is 0.6810663173713034\n",
      "cosine similarity between row 37 and row 27 is 0.7047518122440691\n",
      "cosine similarity between row 37 and row 28 is 0.660669223871184\n",
      "cosine similarity between row 37 and row 29 is 0.650052935671875\n",
      "cosine similarity between row 37 and row 30 is 0.6691775727234484\n",
      "cosine similarity between row 37 and row 31 is 0.6734832956590305\n",
      "cosine similarity between row 37 and row 32 is 0.6732265523391545\n",
      "cosine similarity between row 37 and row 33 is 0.6829875824503517\n",
      "cosine similarity between row 37 and row 34 is 0.6705521796599565\n",
      "cosine similarity between row 37 and row 35 is 0.6704284296679017\n",
      "cosine similarity between row 37 and row 36 is 0.6708529302735702\n",
      "cosine similarity between row 38 and row 0 is 0.6705203525055679\n",
      "cosine similarity between row 38 and row 1 is 0.674423034560897\n",
      "cosine similarity between row 38 and row 2 is 0.6759724485133783\n",
      "cosine similarity between row 38 and row 3 is 0.6546027669991659\n",
      "cosine similarity between row 38 and row 4 is 0.682951850292214\n",
      "cosine similarity between row 38 and row 5 is 0.6669313887461324\n",
      "cosine similarity between row 38 and row 6 is 0.6778149702862778\n",
      "cosine similarity between row 38 and row 7 is 0.694400930684348\n",
      "cosine similarity between row 38 and row 8 is 0.6902434187442791\n",
      "cosine similarity between row 38 and row 9 is 0.6953565783061345\n",
      "cosine similarity between row 38 and row 10 is 0.6753732790607508\n",
      "cosine similarity between row 38 and row 11 is 0.6623350758148522\n",
      "cosine similarity between row 38 and row 12 is 0.6776372800837432\n",
      "cosine similarity between row 38 and row 13 is 0.6615384377323834\n",
      "cosine similarity between row 38 and row 14 is 0.682909314056348\n",
      "cosine similarity between row 38 and row 15 is 0.6514969638587228\n",
      "cosine similarity between row 38 and row 16 is 0.6630478159881976\n",
      "cosine similarity between row 38 and row 17 is 0.6795712596883009\n",
      "cosine similarity between row 38 and row 18 is 0.6648203748947659\n",
      "cosine similarity between row 38 and row 19 is 0.7068015910007269\n",
      "cosine similarity between row 38 and row 20 is 0.6503956780115894\n",
      "cosine similarity between row 38 and row 21 is 0.6880518053331173\n",
      "cosine similarity between row 38 and row 22 is 0.6699778578888085\n",
      "cosine similarity between row 38 and row 23 is 0.6750648524904902\n",
      "cosine similarity between row 38 and row 24 is 0.6754784526102189\n",
      "cosine similarity between row 38 and row 25 is 0.6779624153702414\n",
      "cosine similarity between row 38 and row 26 is 0.6813954958511268\n",
      "cosine similarity between row 38 and row 27 is 0.6815066221454945\n",
      "cosine similarity between row 38 and row 28 is 0.65154532085129\n",
      "cosine similarity between row 38 and row 29 is 0.6514258021373603\n",
      "cosine similarity between row 38 and row 30 is 0.6881962216039631\n",
      "cosine similarity between row 38 and row 31 is 0.666850990337082\n",
      "cosine similarity between row 38 and row 32 is 0.6912072473747496\n",
      "cosine similarity between row 38 and row 33 is 0.690470329167639\n",
      "cosine similarity between row 38 and row 34 is 0.6710386513989806\n",
      "cosine similarity between row 38 and row 35 is 0.69022881139501\n",
      "cosine similarity between row 38 and row 36 is 0.6747939811965297\n",
      "cosine similarity between row 38 and row 37 is 0.6729366095730035\n",
      "cosine similarity between row 39 and row 0 is 0.6630751197110613\n",
      "cosine similarity between row 39 and row 1 is 0.6696271851671448\n",
      "cosine similarity between row 39 and row 2 is 0.6841421585650926\n",
      "cosine similarity between row 39 and row 3 is 0.6687553079716542\n",
      "cosine similarity between row 39 and row 4 is 0.6966967762856408\n",
      "cosine similarity between row 39 and row 5 is 0.6794972786601574\n",
      "cosine similarity between row 39 and row 6 is 0.6855649445264086\n",
      "cosine similarity between row 39 and row 7 is 0.6915649211185553\n",
      "cosine similarity between row 39 and row 8 is 0.69256853008305\n",
      "cosine similarity between row 39 and row 9 is 0.696610243037746\n",
      "cosine similarity between row 39 and row 10 is 0.6943911235949082\n",
      "cosine similarity between row 39 and row 11 is 0.6955527846677598\n",
      "cosine similarity between row 39 and row 12 is 0.6899147671024384\n",
      "cosine similarity between row 39 and row 13 is 0.6747267250935679\n",
      "cosine similarity between row 39 and row 14 is 0.6789062036316822\n",
      "cosine similarity between row 39 and row 15 is 0.6719548109070936\n",
      "cosine similarity between row 39 and row 16 is 0.6901439160497606\n",
      "cosine similarity between row 39 and row 17 is 0.6666357915614858\n",
      "cosine similarity between row 39 and row 18 is 0.6864681979687983\n",
      "cosine similarity between row 39 and row 19 is 0.6962773996617975\n",
      "cosine similarity between row 39 and row 20 is 0.6582704361840535\n",
      "cosine similarity between row 39 and row 21 is 0.6904830069997714\n",
      "cosine similarity between row 39 and row 22 is 0.6894113904211703\n",
      "cosine similarity between row 39 and row 23 is 0.6905933404178446\n",
      "cosine similarity between row 39 and row 24 is 0.6762267702799054\n",
      "cosine similarity between row 39 and row 25 is 0.69286322890027\n",
      "cosine similarity between row 39 and row 26 is 0.696200036792315\n",
      "cosine similarity between row 39 and row 27 is 0.6780925635242837\n",
      "cosine similarity between row 39 and row 28 is 0.6591539989005627\n",
      "cosine similarity between row 39 and row 29 is 0.6643852721574224\n",
      "cosine similarity between row 39 and row 30 is 0.6881531750983362\n",
      "cosine similarity between row 39 and row 31 is 0.6745370374594354\n",
      "cosine similarity between row 39 and row 32 is 0.6752056110690301\n",
      "cosine similarity between row 39 and row 33 is 0.6865297563056042\n",
      "cosine similarity between row 39 and row 34 is 0.6935074482714488\n",
      "cosine similarity between row 39 and row 35 is 0.6764599759649459\n",
      "cosine similarity between row 39 and row 36 is 0.6879743303046082\n",
      "cosine similarity between row 39 and row 37 is 0.679105284025275\n",
      "cosine similarity between row 39 and row 38 is 0.6900072942393727\n",
      "cosine similarity between row 40 and row 0 is 0.6812257980946914\n",
      "cosine similarity between row 40 and row 1 is 0.6801392778241038\n",
      "cosine similarity between row 40 and row 2 is 0.6992247666201344\n",
      "cosine similarity between row 40 and row 3 is 0.6720622570716425\n",
      "cosine similarity between row 40 and row 4 is 0.6804514928299341\n",
      "cosine similarity between row 40 and row 5 is 0.6936766903256425\n",
      "cosine similarity between row 40 and row 6 is 0.6815918248785205\n",
      "cosine similarity between row 40 and row 7 is 0.7006807587175048\n",
      "cosine similarity between row 40 and row 8 is 0.6882987976904511\n",
      "cosine similarity between row 40 and row 9 is 0.6952084669892757\n",
      "cosine similarity between row 40 and row 10 is 0.694537816042958\n",
      "cosine similarity between row 40 and row 11 is 0.6957206740145935\n",
      "cosine similarity between row 40 and row 12 is 0.684687668161449\n",
      "cosine similarity between row 40 and row 13 is 0.6777822907209177\n",
      "cosine similarity between row 40 and row 14 is 0.6856059477651326\n",
      "cosine similarity between row 40 and row 15 is 0.6583532503096707\n",
      "cosine similarity between row 40 and row 16 is 0.6770768532038242\n",
      "cosine similarity between row 40 and row 17 is 0.6741242857978466\n",
      "cosine similarity between row 40 and row 18 is 0.6885861731951471\n",
      "cosine similarity between row 40 and row 19 is 0.7007027983913533\n",
      "cosine similarity between row 40 and row 20 is 0.6853024738875684\n",
      "cosine similarity between row 40 and row 21 is 0.6951418619030871\n",
      "cosine similarity between row 40 and row 22 is 0.674256028760557\n",
      "cosine similarity between row 40 and row 23 is 0.6897957897783273\n",
      "cosine similarity between row 40 and row 24 is 0.6641408636972118\n",
      "cosine similarity between row 40 and row 25 is 0.6812992367758725\n",
      "cosine similarity between row 40 and row 26 is 0.688978445424331\n",
      "cosine similarity between row 40 and row 27 is 0.6796752922605869\n",
      "cosine similarity between row 40 and row 28 is 0.6661611070486053\n",
      "cosine similarity between row 40 and row 29 is 0.666955527754252\n",
      "cosine similarity between row 40 and row 30 is 0.6830976821875946\n",
      "cosine similarity between row 40 and row 31 is 0.6828335387235895\n",
      "cosine similarity between row 40 and row 32 is 0.6826917181415618\n",
      "cosine similarity between row 40 and row 33 is 0.6886720716859593\n",
      "cosine similarity between row 40 and row 34 is 0.6975735862318687\n",
      "cosine similarity between row 40 and row 35 is 0.6822702459768624\n",
      "cosine similarity between row 40 and row 36 is 0.6690697002560398\n",
      "cosine similarity between row 40 and row 37 is 0.6735825138278609\n",
      "cosine similarity between row 40 and row 38 is 0.6699216561578691\n",
      "cosine similarity between row 40 and row 39 is 0.6753170760885511\n",
      "cosine similarity between row 41 and row 0 is 0.6748376619076618\n",
      "cosine similarity between row 41 and row 1 is 0.6743627864128782\n",
      "cosine similarity between row 41 and row 2 is 0.6937225469727475\n",
      "cosine similarity between row 41 and row 3 is 0.670839770447158\n",
      "cosine similarity between row 41 and row 4 is 0.6877345221568648\n",
      "cosine similarity between row 41 and row 5 is 0.6870247314926412\n",
      "cosine similarity between row 41 and row 6 is 0.70554744415388\n",
      "cosine similarity between row 41 and row 7 is 0.6967775972326473\n",
      "cosine similarity between row 41 and row 8 is 0.6682199157569375\n",
      "cosine similarity between row 41 and row 9 is 0.682279359057155\n",
      "cosine similarity between row 41 and row 10 is 0.7007405595430758\n",
      "cosine similarity between row 41 and row 11 is 0.7032289064114481\n",
      "cosine similarity between row 41 and row 12 is 0.693697856648239\n",
      "cosine similarity between row 41 and row 13 is 0.6864934129601683\n",
      "cosine similarity between row 41 and row 14 is 0.6883622544947132\n",
      "cosine similarity between row 41 and row 15 is 0.6667741366633393\n",
      "cosine similarity between row 41 and row 16 is 0.676501865005632\n",
      "cosine similarity between row 41 and row 17 is 0.6730053720095467\n",
      "cosine similarity between row 41 and row 18 is 0.6757475621934245\n",
      "cosine similarity between row 41 and row 19 is 0.6998083376433842\n",
      "cosine similarity between row 41 and row 20 is 0.6831171451004606\n",
      "cosine similarity between row 41 and row 21 is 0.6870404592125045\n",
      "cosine similarity between row 41 and row 22 is 0.684880364678723\n",
      "cosine similarity between row 41 and row 23 is 0.6870996417488158\n",
      "cosine similarity between row 41 and row 24 is 0.6794552056681021\n",
      "cosine similarity between row 41 and row 25 is 0.6913849438337907\n",
      "cosine similarity between row 41 and row 26 is 0.6986065858743622\n",
      "cosine similarity between row 41 and row 27 is 0.6874266889717684\n",
      "cosine similarity between row 41 and row 28 is 0.684032400761002\n",
      "cosine similarity between row 41 and row 29 is 0.665550034224086\n",
      "cosine similarity between row 41 and row 30 is 0.6905400223989632\n",
      "cosine similarity between row 41 and row 31 is 0.6690892612534254\n",
      "cosine similarity between row 41 and row 32 is 0.672533492556569\n",
      "cosine similarity between row 41 and row 33 is 0.6776544328274269\n",
      "cosine similarity between row 41 and row 34 is 0.6841885840773947\n",
      "cosine similarity between row 41 and row 35 is 0.6736186035649189\n",
      "cosine similarity between row 41 and row 36 is 0.6813141806462839\n",
      "cosine similarity between row 41 and row 37 is 0.6794694814570362\n",
      "cosine similarity between row 41 and row 38 is 0.67907065922044\n",
      "cosine similarity between row 41 and row 39 is 0.6861119226465664\n",
      "cosine similarity between row 41 and row 40 is 0.6856465284519954\n",
      "cosine similarity between row 42 and row 0 is 0.6855247048047651\n",
      "cosine similarity between row 42 and row 1 is 0.6678885255198337\n",
      "cosine similarity between row 42 and row 2 is 0.6890484922761553\n",
      "cosine similarity between row 42 and row 3 is 0.6701740300113498\n",
      "cosine similarity between row 42 and row 4 is 0.6700766963188494\n",
      "cosine similarity between row 42 and row 5 is 0.6929355139088422\n",
      "cosine similarity between row 42 and row 6 is 0.6851903463560398\n",
      "cosine similarity between row 42 and row 7 is 0.6978627561338581\n",
      "cosine similarity between row 42 and row 8 is 0.6867925275372779\n",
      "cosine similarity between row 42 and row 9 is 0.6982990155482139\n",
      "cosine similarity between row 42 and row 10 is 0.6937790607280107\n",
      "cosine similarity between row 42 and row 11 is 0.6972548938213597\n",
      "cosine similarity between row 42 and row 12 is 0.6749696123389668\n",
      "cosine similarity between row 42 and row 13 is 0.6791274060722423\n",
      "cosine similarity between row 42 and row 14 is 0.6840132248465342\n",
      "cosine similarity between row 42 and row 15 is 0.6754550771658343\n",
      "cosine similarity between row 42 and row 16 is 0.6835909916130049\n",
      "cosine similarity between row 42 and row 17 is 0.6742959898325699\n",
      "cosine similarity between row 42 and row 18 is 0.6882910895726082\n",
      "cosine similarity between row 42 and row 19 is 0.6806223047991221\n",
      "cosine similarity between row 42 and row 20 is 0.6661915296389908\n",
      "cosine similarity between row 42 and row 21 is 0.6791763982659202\n",
      "cosine similarity between row 42 and row 22 is 0.6911839139314142\n",
      "cosine similarity between row 42 and row 23 is 0.6891284117220278\n",
      "cosine similarity between row 42 and row 24 is 0.6578773169468166\n",
      "cosine similarity between row 42 and row 25 is 0.685267642207625\n",
      "cosine similarity between row 42 and row 26 is 0.690356573208011\n",
      "cosine similarity between row 42 and row 27 is 0.6875308238770271\n",
      "cosine similarity between row 42 and row 28 is 0.6625112046630978\n",
      "cosine similarity between row 42 and row 29 is 0.6640903046067155\n",
      "cosine similarity between row 42 and row 30 is 0.6751888712845358\n",
      "cosine similarity between row 42 and row 31 is 0.6892391935043429\n",
      "cosine similarity between row 42 and row 32 is 0.6795760397914735\n",
      "cosine similarity between row 42 and row 33 is 0.683721393323642\n",
      "cosine similarity between row 42 and row 34 is 0.6772405938396956\n",
      "cosine similarity between row 42 and row 35 is 0.6959048934296416\n",
      "cosine similarity between row 42 and row 36 is 0.6659945897696651\n",
      "cosine similarity between row 42 and row 37 is 0.6568448485506465\n",
      "cosine similarity between row 42 and row 38 is 0.6736173758165314\n",
      "cosine similarity between row 42 and row 39 is 0.6729798481742645\n",
      "cosine similarity between row 42 and row 40 is 0.6910534872969283\n",
      "cosine similarity between row 42 and row 41 is 0.6832946051235801\n",
      "cosine similarity between row 43 and row 0 is 0.6768098507369191\n",
      "cosine similarity between row 43 and row 1 is 0.6664182599388531\n",
      "cosine similarity between row 43 and row 2 is 0.6876678839719472\n",
      "cosine similarity between row 43 and row 3 is 0.6785545895852187\n",
      "cosine similarity between row 43 and row 4 is 0.6911958129204147\n",
      "cosine similarity between row 43 and row 5 is 0.6791344052994209\n",
      "cosine similarity between row 43 and row 6 is 0.687582666819252\n",
      "cosine similarity between row 43 and row 7 is 0.683402914210046\n",
      "cosine similarity between row 43 and row 8 is 0.6736290029700402\n",
      "cosine similarity between row 43 and row 9 is 0.7185240869755299\n",
      "cosine similarity between row 43 and row 10 is 0.6799211762668301\n",
      "cosine similarity between row 43 and row 11 is 0.6973918183066904\n",
      "cosine similarity between row 43 and row 12 is 0.6726887690806534\n",
      "cosine similarity between row 43 and row 13 is 0.668403422515005\n",
      "cosine similarity between row 43 and row 14 is 0.6654364833047519\n",
      "cosine similarity between row 43 and row 15 is 0.6700461192393229\n",
      "cosine similarity between row 43 and row 16 is 0.6608843873147274\n",
      "cosine similarity between row 43 and row 17 is 0.6753708286257398\n",
      "cosine similarity between row 43 and row 18 is 0.6723945482706655\n",
      "cosine similarity between row 43 and row 19 is 0.7076471567612833\n",
      "cosine similarity between row 43 and row 20 is 0.6715591402698842\n",
      "cosine similarity between row 43 and row 21 is 0.6880711134345385\n",
      "cosine similarity between row 43 and row 22 is 0.6908973702371838\n",
      "cosine similarity between row 43 and row 23 is 0.695663232703841\n",
      "cosine similarity between row 43 and row 24 is 0.6526958806601043\n",
      "cosine similarity between row 43 and row 25 is 0.6785049261779066\n",
      "cosine similarity between row 43 and row 26 is 0.684156527483321\n",
      "cosine similarity between row 43 and row 27 is 0.6746020562471071\n",
      "cosine similarity between row 43 and row 28 is 0.6794867741305973\n",
      "cosine similarity between row 43 and row 29 is 0.6601359555505317\n",
      "cosine similarity between row 43 and row 30 is 0.6893983691146085\n",
      "cosine similarity between row 43 and row 31 is 0.6594922389818852\n",
      "cosine similarity between row 43 and row 32 is 0.693327366791281\n",
      "cosine similarity between row 43 and row 33 is 0.6859086816191533\n",
      "cosine similarity between row 43 and row 34 is 0.6973010892263738\n",
      "cosine similarity between row 43 and row 35 is 0.6936788989013692\n",
      "cosine similarity between row 43 and row 36 is 0.6662248791056048\n",
      "cosine similarity between row 43 and row 37 is 0.676593845615189\n",
      "cosine similarity between row 43 and row 38 is 0.6698971261827413\n",
      "cosine similarity between row 43 and row 39 is 0.6813976629913312\n",
      "cosine similarity between row 43 and row 40 is 0.6914622644248031\n",
      "cosine similarity between row 43 and row 41 is 0.679542789625779\n",
      "cosine similarity between row 43 and row 42 is 0.6909537317012744\n",
      "cosine similarity between row 44 and row 0 is 0.7143310836202101\n",
      "cosine similarity between row 44 and row 1 is 0.6920828499755195\n",
      "cosine similarity between row 44 and row 2 is 0.6840706484086699\n",
      "cosine similarity between row 44 and row 3 is 0.6880797231315717\n",
      "cosine similarity between row 44 and row 4 is 0.7002610857310747\n",
      "cosine similarity between row 44 and row 5 is 0.6909013570433827\n",
      "cosine similarity between row 44 and row 6 is 0.6765885180400887\n",
      "cosine similarity between row 44 and row 7 is 0.7211213471455404\n",
      "cosine similarity between row 44 and row 8 is 0.6892145232603676\n",
      "cosine similarity between row 44 and row 9 is 0.7031047589714877\n",
      "cosine similarity between row 44 and row 10 is 0.6835320689243705\n",
      "cosine similarity between row 44 and row 11 is 0.6832649479202028\n",
      "cosine similarity between row 44 and row 12 is 0.6953896816223524\n",
      "cosine similarity between row 44 and row 13 is 0.6894779206735898\n",
      "cosine similarity between row 44 and row 14 is 0.6801512581358672\n",
      "cosine similarity between row 44 and row 15 is 0.6714589536062044\n",
      "cosine similarity between row 44 and row 16 is 0.6856076473644833\n",
      "cosine similarity between row 44 and row 17 is 0.6880511563033938\n",
      "cosine similarity between row 44 and row 18 is 0.6890001193626157\n",
      "cosine similarity between row 44 and row 19 is 0.6929903256930271\n",
      "cosine similarity between row 44 and row 20 is 0.6854266973680984\n",
      "cosine similarity between row 44 and row 21 is 0.6866797092652821\n",
      "cosine similarity between row 44 and row 22 is 0.7015352191027184\n",
      "cosine similarity between row 44 and row 23 is 0.6964148078796517\n",
      "cosine similarity between row 44 and row 24 is 0.6715378199111128\n",
      "cosine similarity between row 44 and row 25 is 0.6906870919332533\n",
      "cosine similarity between row 44 and row 26 is 0.699632591560959\n",
      "cosine similarity between row 44 and row 27 is 0.6821170424946279\n",
      "cosine similarity between row 44 and row 28 is 0.6757616019298455\n",
      "cosine similarity between row 44 and row 29 is 0.6835173636630968\n",
      "cosine similarity between row 44 and row 30 is 0.6831877967434171\n",
      "cosine similarity between row 44 and row 31 is 0.6871696502784648\n",
      "cosine similarity between row 44 and row 32 is 0.6835451694057805\n",
      "cosine similarity between row 44 and row 33 is 0.7000626148396809\n",
      "cosine similarity between row 44 and row 34 is 0.6918421202140131\n",
      "cosine similarity between row 44 and row 35 is 0.6928126792940417\n",
      "cosine similarity between row 44 and row 36 is 0.6882185767904023\n",
      "cosine similarity between row 44 and row 37 is 0.6659189419663781\n",
      "cosine similarity between row 44 and row 38 is 0.690186575804333\n",
      "cosine similarity between row 44 and row 39 is 0.6797252241383106\n",
      "cosine similarity between row 44 and row 40 is 0.6836412061296947\n",
      "cosine similarity between row 44 and row 41 is 0.6855982536578858\n",
      "cosine similarity between row 44 and row 42 is 0.6824767135776415\n",
      "cosine similarity between row 44 and row 43 is 0.6979608038147873\n",
      "cosine similarity between row 45 and row 0 is 0.665869222591629\n",
      "cosine similarity between row 45 and row 1 is 0.6669044797421901\n",
      "cosine similarity between row 45 and row 2 is 0.6797710307943796\n",
      "cosine similarity between row 45 and row 3 is 0.6778150774037797\n",
      "cosine similarity between row 45 and row 4 is 0.6886220095291579\n",
      "cosine similarity between row 45 and row 5 is 0.6786139633282807\n",
      "cosine similarity between row 45 and row 6 is 0.6801633613180202\n",
      "cosine similarity between row 45 and row 7 is 0.6889146274656227\n",
      "cosine similarity between row 45 and row 8 is 0.6667028817318591\n",
      "cosine similarity between row 45 and row 9 is 0.6803535897085582\n",
      "cosine similarity between row 45 and row 10 is 0.6859104541546094\n",
      "cosine similarity between row 45 and row 11 is 0.696118123654299\n",
      "cosine similarity between row 45 and row 12 is 0.6926506309857196\n",
      "cosine similarity between row 45 and row 13 is 0.683792624202957\n",
      "cosine similarity between row 45 and row 14 is 0.6629771127082007\n",
      "cosine similarity between row 45 and row 15 is 0.656257177864953\n",
      "cosine similarity between row 45 and row 16 is 0.6708485783845277\n",
      "cosine similarity between row 45 and row 17 is 0.6728589078611353\n",
      "cosine similarity between row 45 and row 18 is 0.6754518908052417\n",
      "cosine similarity between row 45 and row 19 is 0.6997769481786438\n",
      "cosine similarity between row 45 and row 20 is 0.662725610448258\n",
      "cosine similarity between row 45 and row 21 is 0.6806286941350006\n",
      "cosine similarity between row 45 and row 22 is 0.6851463531317676\n",
      "cosine similarity between row 45 and row 23 is 0.6738171526645762\n",
      "cosine similarity between row 45 and row 24 is 0.6557726410370623\n",
      "cosine similarity between row 45 and row 25 is 0.6809343036238266\n",
      "cosine similarity between row 45 and row 26 is 0.6755226115096834\n",
      "cosine similarity between row 45 and row 27 is 0.6767900432020181\n",
      "cosine similarity between row 45 and row 28 is 0.6591724161282486\n",
      "cosine similarity between row 45 and row 29 is 0.6706021219453617\n",
      "cosine similarity between row 45 and row 30 is 0.6809026554132038\n",
      "cosine similarity between row 45 and row 31 is 0.6762817190027559\n",
      "cosine similarity between row 45 and row 32 is 0.6717691661037117\n",
      "cosine similarity between row 45 and row 33 is 0.6848272610491303\n",
      "cosine similarity between row 45 and row 34 is 0.6960894288661306\n",
      "cosine similarity between row 45 and row 35 is 0.6860014247719973\n",
      "cosine similarity between row 45 and row 36 is 0.6790760680188204\n",
      "cosine similarity between row 45 and row 37 is 0.676910313087157\n",
      "cosine similarity between row 45 and row 38 is 0.6947374305854774\n",
      "cosine similarity between row 45 and row 39 is 0.6683444517199014\n",
      "cosine similarity between row 45 and row 40 is 0.6776038223525531\n",
      "cosine similarity between row 45 and row 41 is 0.6781565818885955\n",
      "cosine similarity between row 45 and row 42 is 0.6792470074648919\n",
      "cosine similarity between row 45 and row 43 is 0.6696204140993564\n",
      "cosine similarity between row 45 and row 44 is 0.6960351153447267\n",
      "cosine similarity between row 46 and row 0 is 0.6804255276888241\n",
      "cosine similarity between row 46 and row 1 is 0.6865049175705351\n",
      "cosine similarity between row 46 and row 2 is 0.6920680845347593\n",
      "cosine similarity between row 46 and row 3 is 0.6680999606871132\n",
      "cosine similarity between row 46 and row 4 is 0.6893374404495612\n",
      "cosine similarity between row 46 and row 5 is 0.6749316063625529\n",
      "cosine similarity between row 46 and row 6 is 0.6694055308601172\n",
      "cosine similarity between row 46 and row 7 is 0.6928430618115134\n",
      "cosine similarity between row 46 and row 8 is 0.6721387910549307\n",
      "cosine similarity between row 46 and row 9 is 0.6916225378448946\n",
      "cosine similarity between row 46 and row 10 is 0.6775100694444856\n",
      "cosine similarity between row 46 and row 11 is 0.6900359964934965\n",
      "cosine similarity between row 46 and row 12 is 0.6646889360497862\n",
      "cosine similarity between row 46 and row 13 is 0.6478421904546794\n",
      "cosine similarity between row 46 and row 14 is 0.6722396495723102\n",
      "cosine similarity between row 46 and row 15 is 0.6635473476610401\n",
      "cosine similarity between row 46 and row 16 is 0.6808540911878741\n",
      "cosine similarity between row 46 and row 17 is 0.6722300454577578\n",
      "cosine similarity between row 46 and row 18 is 0.6647993027046182\n",
      "cosine similarity between row 46 and row 19 is 0.6909727560822289\n",
      "cosine similarity between row 46 and row 20 is 0.6806922204707988\n",
      "cosine similarity between row 46 and row 21 is 0.6817033829209331\n",
      "cosine similarity between row 46 and row 22 is 0.6967161239598777\n",
      "cosine similarity between row 46 and row 23 is 0.6738646270234762\n",
      "cosine similarity between row 46 and row 24 is 0.6613001457460923\n",
      "cosine similarity between row 46 and row 25 is 0.6820419707198384\n",
      "cosine similarity between row 46 and row 26 is 0.6834965602439833\n",
      "cosine similarity between row 46 and row 27 is 0.6956600925822134\n",
      "cosine similarity between row 46 and row 28 is 0.660087800007309\n",
      "cosine similarity between row 46 and row 29 is 0.6609120453981877\n",
      "cosine similarity between row 46 and row 30 is 0.681933585493989\n",
      "cosine similarity between row 46 and row 31 is 0.6873512657882365\n",
      "cosine similarity between row 46 and row 32 is 0.672064564731261\n",
      "cosine similarity between row 46 and row 33 is 0.6675638820645916\n",
      "cosine similarity between row 46 and row 34 is 0.693130177754568\n",
      "cosine similarity between row 46 and row 35 is 0.6845846060267511\n",
      "cosine similarity between row 46 and row 36 is 0.6653476632125009\n",
      "cosine similarity between row 46 and row 37 is 0.6493272565302755\n",
      "cosine similarity between row 46 and row 38 is 0.6840011440288559\n",
      "cosine similarity between row 46 and row 39 is 0.6607890854233248\n",
      "cosine similarity between row 46 and row 40 is 0.6794659917496307\n",
      "cosine similarity between row 46 and row 41 is 0.676895963030511\n",
      "cosine similarity between row 46 and row 42 is 0.6776647857053807\n",
      "cosine similarity between row 46 and row 43 is 0.694914796417587\n",
      "cosine similarity between row 46 and row 44 is 0.6867828236604713\n",
      "cosine similarity between row 46 and row 45 is 0.6858969261843129\n",
      "cosine similarity between row 47 and row 0 is 0.6666385195890846\n",
      "cosine similarity between row 47 and row 1 is 0.6860821676970771\n",
      "cosine similarity between row 47 and row 2 is 0.6811011599021504\n",
      "cosine similarity between row 47 and row 3 is 0.6863090094694638\n",
      "cosine similarity between row 47 and row 4 is 0.6735505454919332\n",
      "cosine similarity between row 47 and row 5 is 0.6885800125841085\n",
      "cosine similarity between row 47 and row 6 is 0.6811368660937629\n",
      "cosine similarity between row 47 and row 7 is 0.7054596610997462\n",
      "cosine similarity between row 47 and row 8 is 0.6961744794706065\n",
      "cosine similarity between row 47 and row 9 is 0.680133469231468\n",
      "cosine similarity between row 47 and row 10 is 0.6785193754283954\n",
      "cosine similarity between row 47 and row 11 is 0.6818604842072021\n",
      "cosine similarity between row 47 and row 12 is 0.6669233448207521\n",
      "cosine similarity between row 47 and row 13 is 0.675675888866318\n",
      "cosine similarity between row 47 and row 14 is 0.6745753612813251\n",
      "cosine similarity between row 47 and row 15 is 0.6533696736330774\n",
      "cosine similarity between row 47 and row 16 is 0.6773484488799906\n",
      "cosine similarity between row 47 and row 17 is 0.6869744463957793\n",
      "cosine similarity between row 47 and row 18 is 0.6725102456737049\n",
      "cosine similarity between row 47 and row 19 is 0.691837077570002\n",
      "cosine similarity between row 47 and row 20 is 0.6577513621945658\n",
      "cosine similarity between row 47 and row 21 is 0.6781176518551236\n",
      "cosine similarity between row 47 and row 22 is 0.677356277436214\n",
      "cosine similarity between row 47 and row 23 is 0.6927225729958852\n",
      "cosine similarity between row 47 and row 24 is 0.6782960168927877\n",
      "cosine similarity between row 47 and row 25 is 0.6866813867783067\n",
      "cosine similarity between row 47 and row 26 is 0.6948133256886153\n",
      "cosine similarity between row 47 and row 27 is 0.6865742949852697\n",
      "cosine similarity between row 47 and row 28 is 0.6757585291486806\n",
      "cosine similarity between row 47 and row 29 is 0.6800345116318328\n",
      "cosine similarity between row 47 and row 30 is 0.6748500315979624\n",
      "cosine similarity between row 47 and row 31 is 0.6759487300495195\n",
      "cosine similarity between row 47 and row 32 is 0.6761980180833802\n",
      "cosine similarity between row 47 and row 33 is 0.6634366886938097\n",
      "cosine similarity between row 47 and row 34 is 0.6728068464524029\n",
      "cosine similarity between row 47 and row 35 is 0.665938396969883\n",
      "cosine similarity between row 47 and row 36 is 0.6875823178906045\n",
      "cosine similarity between row 47 and row 37 is 0.6545016641872735\n",
      "cosine similarity between row 47 and row 38 is 0.668299042786991\n",
      "cosine similarity between row 47 and row 39 is 0.683757897751365\n",
      "cosine similarity between row 47 and row 40 is 0.6788625164174781\n",
      "cosine similarity between row 47 and row 41 is 0.6832126871870939\n",
      "cosine similarity between row 47 and row 42 is 0.6760867353808873\n",
      "cosine similarity between row 47 and row 43 is 0.6799976467493379\n",
      "cosine similarity between row 47 and row 44 is 0.6918892284842733\n",
      "cosine similarity between row 47 and row 45 is 0.6615707566155996\n",
      "cosine similarity between row 47 and row 46 is 0.6579683703389387\n",
      "cosine similarity between row 48 and row 0 is 0.6774202667958832\n",
      "cosine similarity between row 48 and row 1 is 0.6608182772977418\n",
      "cosine similarity between row 48 and row 2 is 0.6787596423659726\n",
      "cosine similarity between row 48 and row 3 is 0.6594206550200368\n",
      "cosine similarity between row 48 and row 4 is 0.6797608750082089\n",
      "cosine similarity between row 48 and row 5 is 0.6774554700256666\n",
      "cosine similarity between row 48 and row 6 is 0.6649859471457686\n",
      "cosine similarity between row 48 and row 7 is 0.6944376133696799\n",
      "cosine similarity between row 48 and row 8 is 0.6919796173274679\n",
      "cosine similarity between row 48 and row 9 is 0.6897477430797637\n",
      "cosine similarity between row 48 and row 10 is 0.6756703520174991\n",
      "cosine similarity between row 48 and row 11 is 0.6875209902014842\n",
      "cosine similarity between row 48 and row 12 is 0.6710041578293672\n",
      "cosine similarity between row 48 and row 13 is 0.6698900282763522\n",
      "cosine similarity between row 48 and row 14 is 0.6863663703503459\n",
      "cosine similarity between row 48 and row 15 is 0.6486098289298569\n",
      "cosine similarity between row 48 and row 16 is 0.6738369131579967\n",
      "cosine similarity between row 48 and row 17 is 0.6630539763780552\n",
      "cosine similarity between row 48 and row 18 is 0.6772807133956015\n",
      "cosine similarity between row 48 and row 19 is 0.6838763071022476\n",
      "cosine similarity between row 48 and row 20 is 0.6623677607356631\n",
      "cosine similarity between row 48 and row 21 is 0.6866363592903226\n",
      "cosine similarity between row 48 and row 22 is 0.6720928790673446\n",
      "cosine similarity between row 48 and row 23 is 0.6786943349995789\n",
      "cosine similarity between row 48 and row 24 is 0.6778656872205616\n",
      "cosine similarity between row 48 and row 25 is 0.7000211937306408\n",
      "cosine similarity between row 48 and row 26 is 0.6814631205369778\n",
      "cosine similarity between row 48 and row 27 is 0.6886966590554128\n",
      "cosine similarity between row 48 and row 28 is 0.6758198015085118\n",
      "cosine similarity between row 48 and row 29 is 0.6619237322326124\n",
      "cosine similarity between row 48 and row 30 is 0.669292789651564\n",
      "cosine similarity between row 48 and row 31 is 0.6612556439953859\n",
      "cosine similarity between row 48 and row 32 is 0.6583611534020871\n",
      "cosine similarity between row 48 and row 33 is 0.6854773639890989\n",
      "cosine similarity between row 48 and row 34 is 0.6733299894894482\n",
      "cosine similarity between row 48 and row 35 is 0.6815097303907288\n",
      "cosine similarity between row 48 and row 36 is 0.6763854394594941\n",
      "cosine similarity between row 48 and row 37 is 0.667911108443486\n",
      "cosine similarity between row 48 and row 38 is 0.6882609422044808\n",
      "cosine similarity between row 48 and row 39 is 0.678017589897476\n",
      "cosine similarity between row 48 and row 40 is 0.7035934626867052\n",
      "cosine similarity between row 48 and row 41 is 0.6797316904780379\n",
      "cosine similarity between row 48 and row 42 is 0.6712446117488713\n",
      "cosine similarity between row 48 and row 43 is 0.6796524027172769\n",
      "cosine similarity between row 48 and row 44 is 0.688835366120433\n",
      "cosine similarity between row 48 and row 45 is 0.6752896376308419\n",
      "cosine similarity between row 48 and row 46 is 0.666172541348671\n",
      "cosine similarity between row 48 and row 47 is 0.6515508100085082\n",
      "cosine similarity between row 49 and row 0 is 0.6714850450468535\n",
      "cosine similarity between row 49 and row 1 is 0.686632225872949\n",
      "cosine similarity between row 49 and row 2 is 0.6784682801174405\n",
      "cosine similarity between row 49 and row 3 is 0.6736487998085836\n",
      "cosine similarity between row 49 and row 4 is 0.7043062360204917\n",
      "cosine similarity between row 49 and row 5 is 0.690157381751047\n",
      "cosine similarity between row 49 and row 6 is 0.6929486466098627\n",
      "cosine similarity between row 49 and row 7 is 0.6901212320222159\n",
      "cosine similarity between row 49 and row 8 is 0.6976831644818493\n",
      "cosine similarity between row 49 and row 9 is 0.7087407912118152\n",
      "cosine similarity between row 49 and row 10 is 0.6870905714163646\n",
      "cosine similarity between row 49 and row 11 is 0.7030651700339313\n",
      "cosine similarity between row 49 and row 12 is 0.6730441003225157\n",
      "cosine similarity between row 49 and row 13 is 0.6803976752131328\n",
      "cosine similarity between row 49 and row 14 is 0.6821045159446847\n",
      "cosine similarity between row 49 and row 15 is 0.67516781395663\n",
      "cosine similarity between row 49 and row 16 is 0.673386195285333\n",
      "cosine similarity between row 49 and row 17 is 0.6805901438334709\n",
      "cosine similarity between row 49 and row 18 is 0.6790275811649588\n",
      "cosine similarity between row 49 and row 19 is 0.7079173847230755\n",
      "cosine similarity between row 49 and row 20 is 0.6818403034466055\n",
      "cosine similarity between row 49 and row 21 is 0.6780018993973463\n",
      "cosine similarity between row 49 and row 22 is 0.697591259585236\n",
      "cosine similarity between row 49 and row 23 is 0.6913380971870903\n",
      "cosine similarity between row 49 and row 24 is 0.6759874729612558\n",
      "cosine similarity between row 49 and row 25 is 0.68545712831662\n",
      "cosine similarity between row 49 and row 26 is 0.7070569923755148\n",
      "cosine similarity between row 49 and row 27 is 0.6614135064643396\n",
      "cosine similarity between row 49 and row 28 is 0.6974953186516301\n",
      "cosine similarity between row 49 and row 29 is 0.6715933400588221\n",
      "cosine similarity between row 49 and row 30 is 0.6822516358703633\n",
      "cosine similarity between row 49 and row 31 is 0.6781425360380233\n",
      "cosine similarity between row 49 and row 32 is 0.6922217449607279\n",
      "cosine similarity between row 49 and row 33 is 0.6846010858618037\n",
      "cosine similarity between row 49 and row 34 is 0.6909481438145775\n",
      "cosine similarity between row 49 and row 35 is 0.7032280895207496\n",
      "cosine similarity between row 49 and row 36 is 0.6807569432306002\n",
      "cosine similarity between row 49 and row 37 is 0.6941129927012265\n",
      "cosine similarity between row 49 and row 38 is 0.6741222889699514\n",
      "cosine similarity between row 49 and row 39 is 0.6765755255034875\n",
      "cosine similarity between row 49 and row 40 is 0.6834215694666105\n",
      "cosine similarity between row 49 and row 41 is 0.6834703615949578\n",
      "cosine similarity between row 49 and row 42 is 0.6864282016893869\n",
      "cosine similarity between row 49 and row 43 is 0.6957573052513277\n",
      "cosine similarity between row 49 and row 44 is 0.697538641410127\n",
      "cosine similarity between row 49 and row 45 is 0.7023375122509893\n",
      "cosine similarity between row 49 and row 46 is 0.6805224720267842\n",
      "cosine similarity between row 49 and row 47 is 0.6692052665503951\n",
      "cosine similarity between row 49 and row 48 is 0.6667933875310724\n"
     ]
    }
   ],
   "source": [
    "# print cosine similarity for between each row in df\n",
    "results = []\n",
    "for i in range(0, len(df)):\n",
    "    for j in range(0, len(df)):\n",
    "        cs = 1 - distance.cosine(df.iloc[i], df.iloc[j])\n",
    "        if cs == 1:\n",
    "            break\n",
    "        results.append({\n",
    "            'X': i,\n",
    "            'Y': j,\n",
    "            'score': cs\n",
    "        })\n",
    "        print(\"cosine similarity between row {} and row {} is {}\".format(i, j, cs))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "outputs": [
    {
     "data": {
      "text/plain": "[{'X': 1, 'Y': 0, 'score': 0.6936463066285999},\n {'X': 2, 'Y': 0, 'score': 0.6755202878582166},\n {'X': 2, 'Y': 1, 'score': 0.6822867740453196},\n {'X': 3, 'Y': 0, 'score': 0.6848527491097506},\n {'X': 3, 'Y': 1, 'score': 0.6902323737872296},\n {'X': 3, 'Y': 2, 'score': 0.6780926658117028},\n {'X': 4, 'Y': 0, 'score': 0.6814302278152795},\n {'X': 4, 'Y': 1, 'score': 0.6889167525232867},\n {'X': 4, 'Y': 2, 'score': 0.6790306316246786},\n {'X': 4, 'Y': 3, 'score': 0.6943451188807976},\n {'X': 5, 'Y': 0, 'score': 0.6543980831366638},\n {'X': 5, 'Y': 1, 'score': 0.660835501223758},\n {'X': 5, 'Y': 2, 'score': 0.6741113983727295},\n {'X': 5, 'Y': 3, 'score': 0.6704209180333824},\n {'X': 5, 'Y': 4, 'score': 0.6879061364120791},\n {'X': 6, 'Y': 0, 'score': 0.6666678938254708},\n {'X': 6, 'Y': 1, 'score': 0.6643693189661543},\n {'X': 6, 'Y': 2, 'score': 0.6862025988989627},\n {'X': 6, 'Y': 3, 'score': 0.6804057498465833},\n {'X': 6, 'Y': 4, 'score': 0.6852613945969009},\n 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{'X': 44, 'Y': 1, 'score': 0.6920828499755195},\n {'X': 44, 'Y': 2, 'score': 0.6840706484086699},\n {'X': 44, 'Y': 3, 'score': 0.6880797231315717},\n {'X': 44, 'Y': 4, 'score': 0.7002610857310747},\n {'X': 44, 'Y': 5, 'score': 0.6909013570433827},\n {'X': 44, 'Y': 6, 'score': 0.6765885180400887},\n {'X': 44, 'Y': 7, 'score': 0.7211213471455404},\n {'X': 44, 'Y': 8, 'score': 0.6892145232603676},\n {'X': 44, 'Y': 9, 'score': 0.7031047589714877},\n {'X': 44, 'Y': 10, 'score': 0.6835320689243705},\n {'X': 44, 'Y': 11, 'score': 0.6832649479202028},\n {'X': 44, 'Y': 12, 'score': 0.6953896816223524},\n {'X': 44, 'Y': 13, 'score': 0.6894779206735898},\n {'X': 44, 'Y': 14, 'score': 0.6801512581358672},\n {'X': 44, 'Y': 15, 'score': 0.6714589536062044},\n {'X': 44, 'Y': 16, 'score': 0.6856076473644833},\n {'X': 44, 'Y': 17, 'score': 0.6880511563033938},\n {'X': 44, 'Y': 18, 'score': 0.6890001193626157},\n {'X': 44, 'Y': 19, 'score': 0.6929903256930271},\n {'X': 44, 'Y': 20, 'score': 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'Y': 40, 'score': 0.6836412061296947},\n {'X': 44, 'Y': 41, 'score': 0.6855982536578858},\n {'X': 44, 'Y': 42, 'score': 0.6824767135776415},\n {'X': 44, 'Y': 43, 'score': 0.6979608038147873},\n {'X': 45, 'Y': 0, 'score': 0.665869222591629},\n {'X': 45, 'Y': 1, 'score': 0.6669044797421901},\n {'X': 45, 'Y': 2, 'score': 0.6797710307943796},\n {'X': 45, 'Y': 3, 'score': 0.6778150774037797},\n {'X': 45, 'Y': 4, 'score': 0.6886220095291579},\n {'X': 45, 'Y': 5, 'score': 0.6786139633282807},\n {'X': 45, 'Y': 6, 'score': 0.6801633613180202},\n {'X': 45, 'Y': 7, 'score': 0.6889146274656227},\n {'X': 45, 'Y': 8, 'score': 0.6667028817318591},\n {'X': 45, 'Y': 9, 'score': 0.6803535897085582},\n ...]"
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "results"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "outputs": [],
   "source": [
    "df_results = pd.DataFrame(results)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "outputs": [],
   "source": [
    "X, Y, score = df_results.max(axis=0, skipna=True)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "outputs": [
    {
     "data": {
      "text/plain": "<AxesSubplot:xlabel='Y', ylabel='X'>"
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": "<Figure size 640x480 with 2 Axes>",
      "image/png": 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\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df_results.pivot(index='X', columns='Y', values='score'))"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  },
  {
   "cell_type": "markdown",
   "source": [],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%% md\n"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "X        26.000000\n",
      "Y        19.000000\n",
      "score     0.721886\n",
      "Name: 344, dtype: float64\n"
     ]
    }
   ],
   "source": [
    "# find the row where score is the highest\n",
    "mod_index = df_results.loc[df_results['score'].idxmax()]\n",
    "\n",
    "print(mod_index)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "name": "#%%\n"
    }
   }
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}