TextMining.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> Text Mining with Cosine Similarities </h2>\n",
    "<h4> Ian Russell </h4>\n",
    "<p> To begin, the document must be processed (a). In order to do so, the following six steps need be performed. [1] Convert to lower case, [2] remove stop words, [3] remove punctuation, [4] remove singular characters, [5] stem all words, and [6] replace digits with their english representation. </p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "import os\n",
    "import nltk\n",
    "from nltk.stem import PorterStemmer\n",
    "from nltk.stem import LancasterStemmer\n",
    "import pandas as pd\n",
    "from num2words import num2words\n",
    "import ast\n",
    "import csv\n",
    "import numpy as np\n",
    "import queue\n",
    "import time\n",
    "import json"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2> Building a Tool Set </h2>\n",
    "<h3> Processing documents </h3>\n",
    "<p> In order to process many documents in a clean and readable fashion, each document will be treated as an object. This document class is shown below and incorporates a pre-process functionality with the rules mentioned above. Furthermore, there is a similar pre-process function to be called on pure text as opposed to a file.</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Document:\n",
    "    \n",
    "    def __init__(self, filename = '', path = '', text = ''):\n",
    "        self.filename = filename\n",
    "        self.path = path\n",
    "        self.text = text\n",
    "        \n",
    "    def process_query(self):\n",
    "        \n",
    "        \n",
    "        stop_words = ['ourselves', 'hers', 'between', 'yourself', 'but', 'again', 'there', 'about', 'once', 'during', 'out', 'very', 'having', 'with', 'they', 'own', 'an', 'be', 'some', 'for', 'do', 'its', 'yours', 'such', 'into', 'of', 'most', 'itself', 'other', 'off', 'is', 's', 'am', 'or', 'who', 'as', 'from', 'him', 'each', 'the', 'themselves', 'until', 'below', 'are', 'we', 'these', 'your', 'his', 'through', 'don', 'nor', 'me', 'were', 'her', 'more', 'himself', 'this', 'down', 'should', 'our', 'their', 'while', 'above', 'both', 'up', 'to', 'ours', 'had', 'she', 'all', 'no', 'when', 'at', 'any', 'before', 'them', 'same', 'and', 'been', 'have', 'in', 'will', 'on', 'does', 'yourselves', 'then', 'that', 'because', 'what', 'over', 'why', 'so', 'can', 'did', 'not', 'now', 'under', 'he', 'you', 'herself', 'has', 'just', 'where', 'too', 'only', 'myself', 'which', 'those', 'i', 'after', 'few', 'whom', 't', 'being', 'if', 'theirs', 'my', 'against', 'a', 'by', 'doing', 'it', 'how', 'further', 'was', 'here', 'than']\n",
    "        porter = PorterStemmer()\n",
    "        \n",
    "        query = self.text\n",
    "        \n",
    "        # Tokenize\n",
    "        query = re.sub(r'\\W+', ' ', query).split()\n",
    "        # apply lower case \n",
    "        query = [x.lower() for x in query]\n",
    "        # remove stop words\n",
    "        query = [i for i in query if not i in stop_words]\n",
    "        # remove single characters\n",
    "        query = [i for i in query if len(i) > 1]\n",
    "        # stemming\n",
    "        tmp = []\n",
    "        for word in query:\n",
    "            tmp.append(porter.stem(word))\n",
    "        query = tmp\n",
    "\n",
    "        # convert numbers\n",
    "        index = 0\n",
    "        for word in query:\n",
    "            if word.isdigit():\n",
    "                query[index] = num2words(word)\n",
    "            index += 1\n",
    "\n",
    "        return query\n",
    "\n",
    "        \n",
    "    def pre_process(self):\n",
    "        \"\"\"\n",
    "        Pre-processor function to remove and tokenize indivual document\n",
    "        object for prepartion of analysis. Returns processed data.\n",
    "        \"\"\"\n",
    "        \n",
    "        stop_words = ['ourselves', 'hers', 'between', 'yourself', 'but', 'again', 'there', 'about', 'once', 'during', 'out', 'very', 'having', 'with', 'they', 'own', 'an', 'be', 'some', 'for', 'do', 'its', 'yours', 'such', 'into', 'of', 'most', 'itself', 'other', 'off', 'is', 's', 'am', 'or', 'who', 'as', 'from', 'him', 'each', 'the', 'themselves', 'until', 'below', 'are', 'we', 'these', 'your', 'his', 'through', 'don', 'nor', 'me', 'were', 'her', 'more', 'himself', 'this', 'down', 'should', 'our', 'their', 'while', 'above', 'both', 'up', 'to', 'ours', 'had', 'she', 'all', 'no', 'when', 'at', 'any', 'before', 'them', 'same', 'and', 'been', 'have', 'in', 'will', 'on', 'does', 'yourselves', 'then', 'that', 'because', 'what', 'over', 'why', 'so', 'can', 'did', 'not', 'now', 'under', 'he', 'you', 'herself', 'has', 'just', 'where', 'too', 'only', 'myself', 'which', 'those', 'i', 'after', 'few', 'whom', 't', 'being', 'if', 'theirs', 'my', 'against', 'a', 'by', 'doing', 'it', 'how', 'further', 'was', 'here', 'than']\n",
    "        porter = PorterStemmer()\n",
    "        \n",
    "        with open(os.path.join(path, self.filename), encoding=\"utf8\", errors=\"surrogateescape\") as text:\n",
    "\n",
    "            data = text.read()\n",
    "            \n",
    "            # Tokenize\n",
    "            data = re.sub(r'\\W+', ' ', data).split()\n",
    "            # apply lower case \n",
    "            data = [x.lower() for x in data]\n",
    "            # remove stop words\n",
    "            data = [i for i in data if not i in stop_words]\n",
    "            # remove single characters\n",
    "            data = [i for i in data if len(i) > 1]\n",
    "            # stemming\n",
    "            tmp = []\n",
    "            for word in data:\n",
    "                tmp.append(porter.stem(word))\n",
    "            data = tmp\n",
    "            \n",
    "            # convert numbers\n",
    "            index = 0\n",
    "            for word in data:\n",
    "                if word.isdigit():\n",
    "                    data[index] = num2words(word)\n",
    "                index += 1\n",
    "            \n",
    "            print(\"Document ready!\")\n",
    "            \n",
    "            return data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Calculating TF-IDF Vectors </h3>\n",
    "<p> Simlar to the document class, the TFIDFVector class will generate a vector object from data parameters such as document frequencies and universal word totals. This object maintains the ability to convert itself into an TF-IDF vector coressponding to an individual document. Similar to the case in the document class a seperate vectorize function is used for text based queries.\n",
    "</p>\n",
    "\n",
    "<p> It is useful to calculate such a vector that includes both term frequecy and inverse document frequency because the information contained by those terms encompasses statistics for the indivual document and the entire corpus, respectively. </p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class TFIDFVector:\n",
    "    def __init__(self, document, N, DF):\n",
    "        \"\"\"\n",
    "        Creates document vector to compute TF-IDF.\n",
    "        For document vectorization, document should\n",
    "        be a dictionary with word counts. For a query\n",
    "        document should be in a string format.\n",
    "        \"\"\"\n",
    "        self.document = document\n",
    "        self.N = N\n",
    "        self.DF = DF\n",
    "        \n",
    "        \n",
    "    def vectorize(self):\n",
    "        \"\"\"\n",
    "        Function generates TF-IDF Vector for\n",
    "        individual document in corpus.\n",
    "        \"\"\"\n",
    "        tf_idf_vector = {}\n",
    "        for term in self.document:\n",
    "            # term frequency\n",
    "            count = self.document[term]\n",
    "            tf = count/len(self.document)\n",
    "            # document frequency\n",
    "            df = sum(self.DF[term])\n",
    "            # inverse document frequency\n",
    "            idf = np.log(self.N/(df + 1))\n",
    "            # TF-IDF\n",
    "            tf_idf = tf*idf\n",
    "            save = {term : tf_idf}\n",
    "            tf_idf_vector.update(save)\n",
    "            \n",
    "        return tf_idf_vector\n",
    "    \n",
    "    def query_vectorize(self):\n",
    "        \n",
    "        tf_idf_vector_query = {}\n",
    "       \n",
    "        for term in self.document:\n",
    "            count = counter(self.document, term)[1]\n",
    "            tf = count/len(self.document)\n",
    "            # document frequency\n",
    "            df = sum(self.DF[term])\n",
    "            # inverse document frequency\n",
    "            idf = np.log(self.N/(df + 1))\n",
    "            # TF-IDF\n",
    "            tf_idf = tf*idf\n",
    "            save = {term : tf_idf}\n",
    "            tf_idf_vector_query.update(save)\n",
    "            \n",
    "        return tf_idf_vector_query\n",
    "    \n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Utility Functions </h3> \n",
    "<p> Each function below is used to help calculate individual data parameters.\n",
    "the precise purpose of each function is described in its documentation. </p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def main(directory):\n",
    "    \"\"\"\n",
    "    Main driver function, takes in directory and returns term counts for\n",
    "    each individual document.\n",
    "    \"\"\"\n",
    "    docs = []\n",
    "    for entry in entries:\n",
    "        docs.append(Document(entry, path))\n",
    "\n",
    "    processed = []\n",
    "    for document in docs:\n",
    "         processed.append(document.pre_process())\n",
    "    \n",
    "    processed_counts = termCounts(processed)\n",
    "    \n",
    "    with open('wordCounts.txt', 'w') as file:\n",
    "        file.write(json.dumps(processed_counts))\n",
    "    \n",
    "    return processed_counts\n",
    "\n",
    "\n",
    "def counter(lst, term): \n",
    "    \"\"\"\n",
    "    Utility function to count redundant occurences\n",
    "    in a list.\n",
    "    \"\"\"\n",
    "    count = 0\n",
    "    for ele in lst: \n",
    "        if (ele == term): \n",
    "            count = count + 1\n",
    "    return term, count\n",
    "\n",
    "\n",
    "def termCounts(corpus):\n",
    "    \"\"\"\n",
    "    Takes list of pre-processed documents (corpus) and returns individual\n",
    "    term counts for each document.\n",
    "    \"\"\"\n",
    "    count = 0\n",
    "    termCount_corpus = []\n",
    "    for document in corpus:\n",
    "        termCounts_doc = {}\n",
    "        tmp = []\n",
    "        print(\"Counting... \" + str(count))\n",
    "        for term in document:\n",
    "            tmp.append(counter(document,term))\n",
    "        terms = set(tmp)\n",
    "        terms = list(terms)\n",
    "        termCounts_doc.update(terms)\n",
    "        termCount_corpus.append(termCounts_doc)\n",
    "        print(len(termCount_corpus))\n",
    "        count += 1\n",
    "    return termCount_corpus\n",
    "\n",
    "    \n",
    "\n",
    "\n",
    "def universe_size(data):\n",
    "    \"\"\"\n",
    "    Utility function to compute and return\n",
    "    term universe size 'N'.\n",
    "    \"\"\"\n",
    "    N = 0\n",
    "    for doc in data: \n",
    "        n=0\n",
    "        for term in doc:\n",
    "            count = doc[term]\n",
    "            n += count\n",
    "        N += n\n",
    "    return N\n",
    "        \n",
    "def document_frequency(data):\n",
    "    \"\"\"\n",
    "    Utility function to compute document frequency for \n",
    "    all terms in pre-processed corpus.\n",
    "    \"\"\"\n",
    "    DF = {}\n",
    "    for i in range(len(data)):\n",
    "        tokens = data[i]\n",
    "        for w in tokens:\n",
    "            try:\n",
    "                DF[w].add(i)\n",
    "            except:\n",
    "                DF[w] = {i}\n",
    "    return DF"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Cosine Similarity </h3>\n",
    "<p> Cosine similarity allows for a metric to compare to n-dimensional vectors landing between the values of 0 and 1. This similarity is quantified by the tightness of the angle between any two vectors. The function below performs this calculation for every possible pair of documents in the data set (250 x 250)!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def cosineSim(data):\n",
    "    \"\"\"\n",
    "    Function to compute the pairwise cosine similarity\n",
    "    throughout all documents. Produces an n x n matrix\n",
    "    saved as a csv. n is number of documents. \n",
    "    \n",
    "    \"\"\"\n",
    "    \n",
    "    start_time = time.time()\n",
    "    \n",
    "    # Initialize all tf-idf vectors\n",
    "    start_vectors  = []\n",
    "    print('Initializing...')\n",
    "    print()\n",
    "    \n",
    "    # Append each tfd-idf vector to start_vectors (all docs)\n",
    "    for i in range(len(data)):\n",
    "        start_vectors.append(TFIDFVector(data[i], universe_size(data), document_frequency(data)).vectorize())\n",
    "\n",
    "    # Queue up vectors for comparison\n",
    "    to_compare = queue.Queue(maxsize = len(data))\n",
    "    cols = [\"col\" + str(i) for i in range(len(data))]\n",
    "\n",
    "    for vector in start_vectors:\n",
    "        to_compare.put(vector)\n",
    "\n",
    "    print(\"Vectors ready\")\n",
    "    print()\n",
    "    print(\"Working...\")\n",
    "    tick = 0\n",
    "    \n",
    "    # Start comparisons\n",
    "    sims = pd.DataFrame()\n",
    "    \n",
    "    # Outer loop handles queued vectors\n",
    "    for vector in start_vectors:\n",
    "        base = to_compare.get()\n",
    "        print()\n",
    "        column = []\n",
    "        \n",
    "        # Inner loop compares each vector in data to current vector in the queue\n",
    "        for i in range(len(data)):\n",
    "            \n",
    "            # Convert pair of vectors to data frame\n",
    "            comparison = pd.DataFrame([base, start_vectors[i]])\n",
    "            \n",
    "            # Replace non-present words from opposing document with 0 values\n",
    "            comparison.fillna(0, inplace = True)\n",
    "            a = comparison.iloc[0]\n",
    "            b = comparison.iloc[1]\n",
    "            \n",
    "            # Convert to numpy vectors\n",
    "            a = a.to_numpy()\n",
    "            b = b.to_numpy()\n",
    "\n",
    "            # manually compute cosine similarity\n",
    "            dot = np.dot(a,b)\n",
    "            norma = np.linalg.norm(a)\n",
    "            normb = np.linalg.norm(b)\n",
    "            cos = round(dot / (norma * normb), 5)\n",
    "            column.append(cos)\n",
    "        \n",
    "        # Insert pair wise comparison as column in final matrix\n",
    "        insertion = pd.Series(column)\n",
    "        sims.insert(tick, cols[tick], insertion)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "        tick += 1\n",
    "        print(\"#####################################\")\n",
    "        print(\"Computation complete for vector \" + str(tick) + \"/\" + str(len(data)))\n",
    "        print(\"#####################################\")\n",
    "\n",
    "\n",
    "\n",
    "    export_csv = sims.to_csv (r'/home/ian/Dropbox/School/Current_courses/Data_Mining/assignment_3/matrix.csv', index = None, header=True)\n",
    "\n",
    "    print(\"--- %s minutes ---\" % round(((time.time() - start_time)/60), 2))\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "def retrieval(queries, data):\n",
    "    \"\"\"\n",
    "    Function performs a comparison\n",
    "    analysis between TF-IDF vectorized queries \n",
    "    and all documents in the data parameter. Data\n",
    "    must be in pre-processed format.\n",
    "    \"\"\"\n",
    "    \n",
    "    start_time = time.time()\n",
    "    \n",
    "    # Initialize all tf-idf vectors\n",
    "    print()\n",
    "    print('Initializing data...')\n",
    "    \n",
    "    start_vectors  = []\n",
    "    \n",
    "    # Append each tfd-idf vector to start_vectors (all docs)\n",
    "    for i in range(len(data)):\n",
    "        start_vectors.append(TFIDFVector(data[i], universe_size(data), document_frequency(data)).vectorize())\n",
    "\n",
    "    # Queue up vectors for comparison\n",
    "    to_compare = queue.Queue(maxsize = len(data))\n",
    "    cols = [\"col\" + str(i) for i in range(len(data))]\n",
    "\n",
    "    for vector in start_vectors:\n",
    "        to_compare.put(vector)\n",
    "    \n",
    "    print('Intializing queries...')\n",
    "    \n",
    "    # Pre-process queries\n",
    "    processed_queries = []\n",
    "    for query in queries:\n",
    "        filename = ''\n",
    "        q = Document(filename, path, text = query)\n",
    "        processed_queries.append(q.process_query())\n",
    "    \n",
    "    \n",
    "    # Vectorize queries\n",
    "    query_vectors = []\n",
    "    for i in range(len(queries)):\n",
    "        query_vectors.append(TFIDFVector(processed_queries[i], universe_size(data), document_frequency(data)).query_vectorize())\n",
    "    \n",
    "    print('Queries processed!')\n",
    "    \n",
    "    # Comparisons\n",
    "    \n",
    "    \n",
    "    # Queue up vectors for comparison\n",
    "    to_search = queue.Queue(maxsize = len(query_vectors))\n",
    "    cols = [\"col\" + str(i) for i in range(len(data))]\n",
    "\n",
    "    for vector in query_vectors:\n",
    "        to_search.put(vector)\n",
    "    \n",
    "    retrievals = pd.DataFrame()\n",
    "    \n",
    "    tick = 0\n",
    "    # Outer loop handles queued vectors\n",
    "    \n",
    "    print(\"Searching...\")\n",
    "    for vector in query_vectors:\n",
    "        base = to_search.get()\n",
    "        column_retrievals = []\n",
    "        \n",
    "        # Inner loop compares each vector in data to current vector in the queue\n",
    "        for i in range(len(data)):\n",
    "            \n",
    "            # Convert pair of vectors to data frame\n",
    "            comparison = pd.DataFrame([base, start_vectors[i]])\n",
    "            \n",
    "            # Replace non-present words from opposing document with 0 values\n",
    "            comparison.fillna(0, inplace = True)\n",
    "            a = comparison.iloc[0]\n",
    "            b = comparison.iloc[1]\n",
    "            \n",
    "            # Convert to numpy vectors\n",
    "            a = a.to_numpy()\n",
    "            b = b.to_numpy()\n",
    "\n",
    "            # manually compute cosine similarity\n",
    "            dot = np.dot(a,b)\n",
    "            norma = np.linalg.norm(a)\n",
    "            normb = np.linalg.norm(b)\n",
    "            cos = round(dot / (norma * normb), 5)\n",
    "            column_retrievals.append(cos)\n",
    "        \n",
    "        # Insert pair wise comparison as column in final matrix\n",
    "        insertion = pd.Series(column_retrievals)\n",
    "        retrievals.insert(tick, cols[tick], insertion)\n",
    "        tick += 1\n",
    "    print('Done!')\n",
    "    print(\"--- %s seconds ---\" % round(((time.time() - start_time)), 2))\n",
    "        \n",
    "    return retrievals\n",
    "    \n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Pre-processing </h3>\n",
    "\n",
    "<p>\n",
    "This section of code combines the above functions\n",
    "and classes to generate the necessary term counts\n",
    "and document frequencies to compute individual TF-IDF\n",
    "vectors for idividual documents. Run to process new \n",
    "data. Data is saved to file 'termCounts.txt'.\n",
    "</p>\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#####################\n",
    "#### PRE-PROCESS ####\n",
    "#####################\n",
    "\n",
    "# Directory path\n",
    "path = '/home/ian/Dropbox/School/Current_courses/Data_Mining/assignment_3/Data'\n",
    "\n",
    "# Data directory\n",
    "entries = os.listdir(path)\n",
    "\n",
    "# Uncomment if file not already created\n",
    "results = main(entries)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "################\n",
    "### ANALYSIS ###\n",
    "################\n",
    "\n",
    "with open('wordCounts.txt', 'r') as file:\n",
    "    data = file.read()\n",
    "    data = ast.literal_eval(data)\n",
    "\n",
    "\n",
    "data;"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
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       "      <th>col2</th>\n",
       "      <th>col3</th>\n",
       "      <th>col4</th>\n",
       "      <th>col5</th>\n",
       "      <th>col6</th>\n",
       "      <th>col7</th>\n",
       "      <th>col8</th>\n",
       "      <th>col9</th>\n",
       "      <th>...</th>\n",
       "      <th>col239</th>\n",
       "      <th>col240</th>\n",
       "      <th>col241</th>\n",
       "      <th>col242</th>\n",
       "      <th>col243</th>\n",
       "      <th>col244</th>\n",
       "      <th>col245</th>\n",
       "      <th>col246</th>\n",
       "      <th>col247</th>\n",
       "      <th>col248</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.13074</td>\n",
       "      <td>0.15071</td>\n",
       "      <td>0.05337</td>\n",
       "      <td>0.07692</td>\n",
       "      <td>0.05715</td>\n",
       "      <td>0.03246</td>\n",
       "      <td>0.13397</td>\n",
       "      <td>0.07524</td>\n",
       "      <td>0.09731</td>\n",
       "      <td>...</td>\n",
       "      <td>0.15486</td>\n",
       "      <td>0.12591</td>\n",
       "      <td>0.09221</td>\n",
       "      <td>0.11318</td>\n",
       "      <td>0.02616</td>\n",
       "      <td>0.13777</td>\n",
       "      <td>0.00555</td>\n",
       "      <td>0.10723</td>\n",
       "      <td>0.05787</td>\n",
       "      <td>0.10710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.13074</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.42906</td>\n",
       "      <td>0.10437</td>\n",
       "      <td>0.13335</td>\n",
       "      <td>0.15244</td>\n",
       "      <td>0.06316</td>\n",
       "      <td>0.33175</td>\n",
       "      <td>0.12327</td>\n",
       "      <td>0.16180</td>\n",
       "      <td>...</td>\n",
       "      <td>0.50410</td>\n",
       "      <td>0.20103</td>\n",
       "      <td>0.13672</td>\n",
       "      <td>0.14929</td>\n",
       "      <td>0.06043</td>\n",
       "      <td>0.13403</td>\n",
       "      <td>0.24070</td>\n",
       "      <td>0.21832</td>\n",
       "      <td>0.11449</td>\n",
       "      <td>0.18694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.15071</td>\n",
       "      <td>0.42906</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.14807</td>\n",
       "      <td>0.17398</td>\n",
       "      <td>0.15496</td>\n",
       "      <td>0.07850</td>\n",
       "      <td>0.45667</td>\n",
       "      <td>0.16531</td>\n",
       "      <td>0.18229</td>\n",
       "      <td>...</td>\n",
       "      <td>0.54739</td>\n",
       "      <td>0.23365</td>\n",
       "      <td>0.16000</td>\n",
       "      <td>0.18468</td>\n",
       "      <td>0.07802</td>\n",
       "      <td>0.14582</td>\n",
       "      <td>0.21752</td>\n",
       "      <td>0.25073</td>\n",
       "      <td>0.13587</td>\n",
       "      <td>0.23150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.05337</td>\n",
       "      <td>0.10437</td>\n",
       "      <td>0.14807</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.06599</td>\n",
       "      <td>0.06573</td>\n",
       "      <td>0.03951</td>\n",
       "      <td>0.15739</td>\n",
       "      <td>0.08372</td>\n",
       "      <td>0.08062</td>\n",
       "      <td>...</td>\n",
       "      <td>0.13060</td>\n",
       "      <td>0.09218</td>\n",
       "      <td>0.05921</td>\n",
       "      <td>0.07375</td>\n",
       "      <td>0.03756</td>\n",
       "      <td>0.04925</td>\n",
       "      <td>0.01871</td>\n",
       "      <td>0.09496</td>\n",
       "      <td>0.06481</td>\n",
       "      <td>0.08932</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.07692</td>\n",
       "      <td>0.13335</td>\n",
       "      <td>0.17398</td>\n",
       "      <td>0.06599</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.07362</td>\n",
       "      <td>0.03496</td>\n",
       "      <td>0.19353</td>\n",
       "      <td>0.10675</td>\n",
       "      <td>0.08951</td>\n",
       "      <td>...</td>\n",
       "      <td>0.16040</td>\n",
       "      <td>0.10332</td>\n",
       "      <td>0.08538</td>\n",
       "      <td>0.05690</td>\n",
       "      <td>0.03659</td>\n",
       "      <td>0.05757</td>\n",
       "      <td>0.01401</td>\n",
       "      <td>0.11778</td>\n",
       "      <td>0.11069</td>\n",
       "      <td>0.13752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.05715</td>\n",
       "      <td>0.15244</td>\n",
       "      <td>0.15496</td>\n",
       "      <td>0.06573</td>\n",
       "      <td>0.07362</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.04047</td>\n",
       "      <td>0.17547</td>\n",
       "      <td>0.06948</td>\n",
       "      <td>0.08303</td>\n",
       "      <td>...</td>\n",
       "      <td>0.15040</td>\n",
       "      <td>0.12113</td>\n",
       "      <td>0.07376</td>\n",
       "      <td>0.07731</td>\n",
       "      <td>0.04388</td>\n",
       "      <td>0.06658</td>\n",
       "      <td>0.02480</td>\n",
       "      <td>0.10961</td>\n",
       "      <td>0.06009</td>\n",
       "      <td>0.09927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.03246</td>\n",
       "      <td>0.06316</td>\n",
       "      <td>0.07850</td>\n",
       "      <td>0.03951</td>\n",
       "      <td>0.03496</td>\n",
       "      <td>0.04047</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.09304</td>\n",
       "      <td>0.04752</td>\n",
       "      <td>0.04191</td>\n",
       "      <td>...</td>\n",
       "      <td>0.08173</td>\n",
       "      <td>0.08749</td>\n",
       "      <td>0.04751</td>\n",
       "      <td>0.04556</td>\n",
       "      <td>0.03665</td>\n",
       "      <td>0.05219</td>\n",
       "      <td>0.01117</td>\n",
       "      <td>0.05418</td>\n",
       "      <td>0.04220</td>\n",
       "      <td>0.05506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.13397</td>\n",
       "      <td>0.33175</td>\n",
       "      <td>0.45667</td>\n",
       "      <td>0.15739</td>\n",
       "      <td>0.19353</td>\n",
       "      <td>0.17547</td>\n",
       "      <td>0.09304</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.19088</td>\n",
       "      <td>0.21597</td>\n",
       "      <td>...</td>\n",
       "      <td>0.43341</td>\n",
       "      <td>0.25874</td>\n",
       "      <td>0.17991</td>\n",
       "      <td>0.17737</td>\n",
       "      <td>0.11308</td>\n",
       "      <td>0.15914</td>\n",
       "      <td>0.03475</td>\n",
       "      <td>0.26929</td>\n",
       "      <td>0.18833</td>\n",
       "      <td>0.28217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.07524</td>\n",
       "      <td>0.12327</td>\n",
       "      <td>0.16531</td>\n",
       "      <td>0.08372</td>\n",
       "      <td>0.10675</td>\n",
       "      <td>0.06948</td>\n",
       "      <td>0.04752</td>\n",
       "      <td>0.19088</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.09629</td>\n",
       "      <td>...</td>\n",
       "      <td>0.16176</td>\n",
       "      <td>0.17275</td>\n",
       "      <td>0.08042</td>\n",
       "      <td>0.12434</td>\n",
       "      <td>0.04587</td>\n",
       "      <td>0.09731</td>\n",
       "      <td>0.01108</td>\n",
       "      <td>0.16015</td>\n",
       "      <td>0.11140</td>\n",
       "      <td>0.13064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.09731</td>\n",
       "      <td>0.16180</td>\n",
       "      <td>0.18229</td>\n",
       "      <td>0.08062</td>\n",
       "      <td>0.08951</td>\n",
       "      <td>0.08303</td>\n",
       "      <td>0.04191</td>\n",
       "      <td>0.21597</td>\n",
       "      <td>0.09629</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.20069</td>\n",
       "      <td>0.15127</td>\n",
       "      <td>0.10650</td>\n",
       "      <td>0.09937</td>\n",
       "      <td>0.05922</td>\n",
       "      <td>0.09822</td>\n",
       "      <td>0.00917</td>\n",
       "      <td>0.16614</td>\n",
       "      <td>0.10291</td>\n",
       "      <td>0.16906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.14021</td>\n",
       "      <td>0.20744</td>\n",
       "      <td>0.25638</td>\n",
       "      <td>0.07014</td>\n",
       "      <td>0.13943</td>\n",
       "      <td>0.10950</td>\n",
       "      <td>0.05952</td>\n",
       "      <td>0.30852</td>\n",
       "      <td>0.15532</td>\n",
       "      <td>0.16094</td>\n",
       "      <td>...</td>\n",
       "      <td>0.28290</td>\n",
       "      <td>0.21424</td>\n",
       "      <td>0.17613</td>\n",
       "      <td>0.17506</td>\n",
       "      <td>0.07749</td>\n",
       "      <td>0.17048</td>\n",
       "      <td>0.02464</td>\n",
       "      <td>0.20380</td>\n",
       "      <td>0.16687</td>\n",
       "      <td>0.30571</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.02357</td>\n",
       "      <td>0.06311</td>\n",
       "      <td>0.09649</td>\n",
       "      <td>0.03624</td>\n",
       "      <td>0.05851</td>\n",
       "      <td>0.03884</td>\n",
       "      <td>0.02965</td>\n",
       "      <td>0.12875</td>\n",
       "      <td>0.04465</td>\n",
       "      <td>0.03885</td>\n",
       "      <td>...</td>\n",
       "      <td>0.07777</td>\n",
       "      <td>0.05428</td>\n",
       "      <td>0.04503</td>\n",
       "      <td>0.04058</td>\n",
       "      <td>0.02607</td>\n",
       "      <td>0.03566</td>\n",
       "      <td>0.01103</td>\n",
       "      <td>0.05951</td>\n",
       "      <td>0.03865</td>\n",
       "      <td>0.06632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.08719</td>\n",
       "      <td>0.12794</td>\n",
       "      <td>0.17085</td>\n",
       "      <td>0.06999</td>\n",
       "      <td>0.08295</td>\n",
       "      <td>0.07648</td>\n",
       "      <td>0.05533</td>\n",
       "      <td>0.17643</td>\n",
       "      <td>0.09895</td>\n",
       "      <td>0.09492</td>\n",
       "      <td>...</td>\n",
       "      <td>0.18317</td>\n",
       "      <td>0.14080</td>\n",
       "      <td>0.11831</td>\n",
       "      <td>0.12243</td>\n",
       "      <td>0.05117</td>\n",
       "      <td>0.11661</td>\n",
       "      <td>0.01310</td>\n",
       "      <td>0.14236</td>\n",
       "      <td>0.06443</td>\n",
       "      <td>0.12798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.06038</td>\n",
       "      <td>0.08462</td>\n",
       "      <td>0.10103</td>\n",
       "      <td>0.03159</td>\n",
       "      <td>0.04157</td>\n",
       "      <td>0.03752</td>\n",
       "      <td>0.02317</td>\n",
       "      <td>0.12649</td>\n",
       "      <td>0.04616</td>\n",
       "      <td>0.07013</td>\n",
       "      <td>...</td>\n",
       "      <td>0.10221</td>\n",
       "      <td>0.10123</td>\n",
       "      <td>0.05960</td>\n",
       "      <td>0.05852</td>\n",
       "      <td>0.02822</td>\n",
       "      <td>0.06257</td>\n",
       "      <td>0.00560</td>\n",
       "      <td>0.07459</td>\n",
       "      <td>0.04067</td>\n",
       "      <td>0.08662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.14240</td>\n",
       "      <td>0.12440</td>\n",
       "      <td>0.15397</td>\n",
       "      <td>0.21649</td>\n",
       "      <td>0.06960</td>\n",
       "      <td>0.06421</td>\n",
       "      <td>0.04997</td>\n",
       "      <td>0.16593</td>\n",
       "      <td>0.09032</td>\n",
       "      <td>0.09586</td>\n",
       "      <td>...</td>\n",
       "      <td>0.13621</td>\n",
       "      <td>0.15873</td>\n",
       "      <td>0.09953</td>\n",
       "      <td>0.10405</td>\n",
       "      <td>0.05052</td>\n",
       "      <td>0.12976</td>\n",
       "      <td>0.01238</td>\n",
       "      <td>0.11279</td>\n",
       "      <td>0.13280</td>\n",
       "      <td>0.13602</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.07975</td>\n",
       "      <td>0.10839</td>\n",
       "      <td>0.12881</td>\n",
       "      <td>0.05522</td>\n",
       "      <td>0.05348</td>\n",
       "      <td>0.05503</td>\n",
       "      <td>0.04411</td>\n",
       "      <td>0.12265</td>\n",
       "      <td>0.14184</td>\n",
       "      <td>0.06999</td>\n",
       "      <td>...</td>\n",
       "      <td>0.14242</td>\n",
       "      <td>0.14690</td>\n",
       "      <td>0.10031</td>\n",
       "      <td>0.09416</td>\n",
       "      <td>0.03490</td>\n",
       "      <td>0.12943</td>\n",
       "      <td>0.01176</td>\n",
       "      <td>0.11170</td>\n",
       "      <td>0.04829</td>\n",
       "      <td>0.08238</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.04708</td>\n",
       "      <td>0.12851</td>\n",
       "      <td>0.18337</td>\n",
       "      <td>0.11757</td>\n",
       "      <td>0.14834</td>\n",
       "      <td>0.06788</td>\n",
       "      <td>0.04322</td>\n",
       "      <td>0.23519</td>\n",
       "      <td>0.09451</td>\n",
       "      <td>0.07082</td>\n",
       "      <td>...</td>\n",
       "      <td>0.16309</td>\n",
       "      <td>0.11809</td>\n",
       "      <td>0.08425</td>\n",
       "      <td>0.09268</td>\n",
       "      <td>0.05658</td>\n",
       "      <td>0.06454</td>\n",
       "      <td>0.02804</td>\n",
       "      <td>0.14832</td>\n",
       "      <td>0.11145</td>\n",
       "      <td>0.17155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.06407</td>\n",
       "      <td>0.08127</td>\n",
       "      <td>0.10457</td>\n",
       "      <td>0.05257</td>\n",
       "      <td>0.03777</td>\n",
       "      <td>0.04130</td>\n",
       "      <td>0.02312</td>\n",
       "      <td>0.11070</td>\n",
       "      <td>0.05541</td>\n",
       "      <td>0.06557</td>\n",
       "      <td>...</td>\n",
       "      <td>0.09491</td>\n",
       "      <td>0.09836</td>\n",
       "      <td>0.05729</td>\n",
       "      <td>0.07279</td>\n",
       "      <td>0.02444</td>\n",
       "      <td>0.10297</td>\n",
       "      <td>0.00797</td>\n",
       "      <td>0.08359</td>\n",
       "      <td>0.05183</td>\n",
       "      <td>0.10260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.04047</td>\n",
       "      <td>0.05792</td>\n",
       "      <td>0.09894</td>\n",
       "      <td>0.05002</td>\n",
       "      <td>0.02423</td>\n",
       "      <td>0.04579</td>\n",
       "      <td>0.03008</td>\n",
       "      <td>0.10223</td>\n",
       "      <td>0.08565</td>\n",
       "      <td>0.03406</td>\n",
       "      <td>...</td>\n",
       "      <td>0.07702</td>\n",
       "      <td>0.09178</td>\n",
       "      <td>0.05243</td>\n",
       "      <td>0.06516</td>\n",
       "      <td>0.07202</td>\n",
       "      <td>0.04487</td>\n",
       "      <td>0.00759</td>\n",
       "      <td>0.05801</td>\n",
       "      <td>0.03329</td>\n",
       "      <td>0.07629</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.14748</td>\n",
       "      <td>0.08439</td>\n",
       "      <td>0.11982</td>\n",
       "      <td>0.05164</td>\n",
       "      <td>0.05155</td>\n",
       "      <td>0.05395</td>\n",
       "      <td>0.02894</td>\n",
       "      <td>0.18960</td>\n",
       "      <td>0.05350</td>\n",
       "      <td>0.07653</td>\n",
       "      <td>...</td>\n",
       "      <td>0.11007</td>\n",
       "      <td>0.10118</td>\n",
       "      <td>0.05653</td>\n",
       "      <td>0.06234</td>\n",
       "      <td>0.04137</td>\n",
       "      <td>0.06118</td>\n",
       "      <td>0.00945</td>\n",
       "      <td>0.07636</td>\n",
       "      <td>0.14846</td>\n",
       "      <td>0.10509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.05025</td>\n",
       "      <td>0.11157</td>\n",
       "      <td>0.15699</td>\n",
       "      <td>0.06707</td>\n",
       "      <td>0.15787</td>\n",
       "      <td>0.06506</td>\n",
       "      <td>0.04344</td>\n",
       "      <td>0.17419</td>\n",
       "      <td>0.11288</td>\n",
       "      <td>0.07848</td>\n",
       "      <td>...</td>\n",
       "      <td>0.13620</td>\n",
       "      <td>0.13544</td>\n",
       "      <td>0.09079</td>\n",
       "      <td>0.07560</td>\n",
       "      <td>0.06904</td>\n",
       "      <td>0.04954</td>\n",
       "      <td>0.01573</td>\n",
       "      <td>0.10588</td>\n",
       "      <td>0.07955</td>\n",
       "      <td>0.10870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.02349</td>\n",
       "      <td>0.04908</td>\n",
       "      <td>0.06191</td>\n",
       "      <td>0.01580</td>\n",
       "      <td>0.08027</td>\n",
       "      <td>0.02935</td>\n",
       "      <td>0.09264</td>\n",
       "      <td>0.06092</td>\n",
       "      <td>0.03737</td>\n",
       "      <td>0.02690</td>\n",
       "      <td>...</td>\n",
       "      <td>0.05454</td>\n",
       "      <td>0.04737</td>\n",
       "      <td>0.02472</td>\n",
       "      <td>0.02649</td>\n",
       "      <td>0.01469</td>\n",
       "      <td>0.02582</td>\n",
       "      <td>0.00817</td>\n",
       "      <td>0.03975</td>\n",
       "      <td>0.04786</td>\n",
       "      <td>0.04923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.08782</td>\n",
       "      <td>0.12176</td>\n",
       "      <td>0.14018</td>\n",
       "      <td>0.06705</td>\n",
       "      <td>0.06383</td>\n",
       "      <td>0.06318</td>\n",
       "      <td>0.05049</td>\n",
       "      <td>0.14998</td>\n",
       "      <td>0.15020</td>\n",
       "      <td>0.10244</td>\n",
       "      <td>...</td>\n",
       "      <td>0.15216</td>\n",
       "      <td>0.17775</td>\n",
       "      <td>0.09068</td>\n",
       "      <td>0.12052</td>\n",
       "      <td>0.04625</td>\n",
       "      <td>0.10609</td>\n",
       "      <td>0.01138</td>\n",
       "      <td>0.12400</td>\n",
       "      <td>0.07461</td>\n",
       "      <td>0.12658</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.04387</td>\n",
       "      <td>0.08481</td>\n",
       "      <td>0.11905</td>\n",
       "      <td>0.05345</td>\n",
       "      <td>0.09947</td>\n",
       "      <td>0.04983</td>\n",
       "      <td>0.02615</td>\n",
       "      <td>0.11690</td>\n",
       "      <td>0.08045</td>\n",
       "      <td>0.12665</td>\n",
       "      <td>...</td>\n",
       "      <td>0.09532</td>\n",
       "      <td>0.09423</td>\n",
       "      <td>0.06254</td>\n",
       "      <td>0.06729</td>\n",
       "      <td>0.02434</td>\n",
       "      <td>0.06480</td>\n",
       "      <td>0.00657</td>\n",
       "      <td>0.11701</td>\n",
       "      <td>0.05994</td>\n",
       "      <td>0.08753</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.03710</td>\n",
       "      <td>0.06286</td>\n",
       "      <td>0.08373</td>\n",
       "      <td>0.02839</td>\n",
       "      <td>0.05035</td>\n",
       "      <td>0.04314</td>\n",
       "      <td>0.01651</td>\n",
       "      <td>0.07749</td>\n",
       "      <td>0.02551</td>\n",
       "      <td>0.08360</td>\n",
       "      <td>...</td>\n",
       "      <td>0.08106</td>\n",
       "      <td>0.06040</td>\n",
       "      <td>0.13140</td>\n",
       "      <td>0.03421</td>\n",
       "      <td>0.01785</td>\n",
       "      <td>0.03669</td>\n",
       "      <td>0.01079</td>\n",
       "      <td>0.05917</td>\n",
       "      <td>0.02506</td>\n",
       "      <td>0.08631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.06916</td>\n",
       "      <td>0.10820</td>\n",
       "      <td>0.11774</td>\n",
       "      <td>0.06198</td>\n",
       "      <td>0.04488</td>\n",
       "      <td>0.06044</td>\n",
       "      <td>0.03990</td>\n",
       "      <td>0.13566</td>\n",
       "      <td>0.08439</td>\n",
       "      <td>0.08582</td>\n",
       "      <td>...</td>\n",
       "      <td>0.12060</td>\n",
       "      <td>0.16002</td>\n",
       "      <td>0.06591</td>\n",
       "      <td>0.06848</td>\n",
       "      <td>0.03730</td>\n",
       "      <td>0.08546</td>\n",
       "      <td>0.01116</td>\n",
       "      <td>0.09755</td>\n",
       "      <td>0.05025</td>\n",
       "      <td>0.08830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.11839</td>\n",
       "      <td>0.17773</td>\n",
       "      <td>0.23393</td>\n",
       "      <td>0.11749</td>\n",
       "      <td>0.08429</td>\n",
       "      <td>0.09063</td>\n",
       "      <td>0.04820</td>\n",
       "      <td>0.24368</td>\n",
       "      <td>0.09941</td>\n",
       "      <td>0.12990</td>\n",
       "      <td>...</td>\n",
       "      <td>0.21293</td>\n",
       "      <td>0.19073</td>\n",
       "      <td>0.11857</td>\n",
       "      <td>0.12718</td>\n",
       "      <td>0.05237</td>\n",
       "      <td>0.13445</td>\n",
       "      <td>0.01985</td>\n",
       "      <td>0.14425</td>\n",
       "      <td>0.09007</td>\n",
       "      <td>0.18721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.03520</td>\n",
       "      <td>0.10019</td>\n",
       "      <td>0.14108</td>\n",
       "      <td>0.07594</td>\n",
       "      <td>0.10897</td>\n",
       "      <td>0.11820</td>\n",
       "      <td>0.03700</td>\n",
       "      <td>0.16958</td>\n",
       "      <td>0.09112</td>\n",
       "      <td>0.06588</td>\n",
       "      <td>...</td>\n",
       "      <td>0.12082</td>\n",
       "      <td>0.11247</td>\n",
       "      <td>0.05753</td>\n",
       "      <td>0.06079</td>\n",
       "      <td>0.03454</td>\n",
       "      <td>0.05019</td>\n",
       "      <td>0.01737</td>\n",
       "      <td>0.09133</td>\n",
       "      <td>0.08139</td>\n",
       "      <td>0.12810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.06159</td>\n",
       "      <td>0.08573</td>\n",
       "      <td>0.11083</td>\n",
       "      <td>0.04877</td>\n",
       "      <td>0.04021</td>\n",
       "      <td>0.05102</td>\n",
       "      <td>0.03282</td>\n",
       "      <td>0.12743</td>\n",
       "      <td>0.05706</td>\n",
       "      <td>0.06403</td>\n",
       "      <td>...</td>\n",
       "      <td>0.10533</td>\n",
       "      <td>0.08951</td>\n",
       "      <td>0.05941</td>\n",
       "      <td>0.06459</td>\n",
       "      <td>0.03640</td>\n",
       "      <td>0.09016</td>\n",
       "      <td>0.01462</td>\n",
       "      <td>0.07143</td>\n",
       "      <td>0.04304</td>\n",
       "      <td>0.08637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.07896</td>\n",
       "      <td>0.11944</td>\n",
       "      <td>0.13519</td>\n",
       "      <td>0.06674</td>\n",
       "      <td>0.11139</td>\n",
       "      <td>0.06386</td>\n",
       "      <td>0.04203</td>\n",
       "      <td>0.18301</td>\n",
       "      <td>0.11546</td>\n",
       "      <td>0.08218</td>\n",
       "      <td>...</td>\n",
       "      <td>0.15512</td>\n",
       "      <td>0.12991</td>\n",
       "      <td>0.09390</td>\n",
       "      <td>0.08614</td>\n",
       "      <td>0.05033</td>\n",
       "      <td>0.08821</td>\n",
       "      <td>0.03069</td>\n",
       "      <td>0.10184</td>\n",
       "      <td>0.11401</td>\n",
       "      <td>0.14244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>0.05518</td>\n",
       "      <td>0.11884</td>\n",
       "      <td>0.15940</td>\n",
       "      <td>0.07528</td>\n",
       "      <td>0.08327</td>\n",
       "      <td>0.07264</td>\n",
       "      <td>0.04782</td>\n",
       "      <td>0.17133</td>\n",
       "      <td>0.09306</td>\n",
       "      <td>0.10255</td>\n",
       "      <td>...</td>\n",
       "      <td>0.13814</td>\n",
       "      <td>0.14258</td>\n",
       "      <td>0.09502</td>\n",
       "      <td>0.07760</td>\n",
       "      <td>0.04070</td>\n",
       "      <td>0.05440</td>\n",
       "      <td>0.01458</td>\n",
       "      <td>0.10061</td>\n",
       "      <td>0.06972</td>\n",
       "      <td>0.10765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>0.14481</td>\n",
       "      <td>0.22488</td>\n",
       "      <td>0.24101</td>\n",
       "      <td>0.06842</td>\n",
       "      <td>0.11344</td>\n",
       "      <td>0.09812</td>\n",
       "      <td>0.05753</td>\n",
       "      <td>0.23947</td>\n",
       "      <td>0.15823</td>\n",
       "      <td>0.15032</td>\n",
       "      <td>...</td>\n",
       "      <td>0.28219</td>\n",
       "      <td>0.21168</td>\n",
       "      <td>0.14147</td>\n",
       "      <td>0.16885</td>\n",
       "      <td>0.05392</td>\n",
       "      <td>0.15262</td>\n",
       "      <td>0.03349</td>\n",
       "      <td>0.19640</td>\n",
       "      <td>0.14578</td>\n",
       "      <td>0.21316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>0.11180</td>\n",
       "      <td>0.18244</td>\n",
       "      <td>0.19717</td>\n",
       "      <td>0.06674</td>\n",
       "      <td>0.13085</td>\n",
       "      <td>0.08512</td>\n",
       "      <td>0.05442</td>\n",
       "      <td>0.24166</td>\n",
       "      <td>0.14578</td>\n",
       "      <td>0.13269</td>\n",
       "      <td>...</td>\n",
       "      <td>0.22245</td>\n",
       "      <td>0.19249</td>\n",
       "      <td>0.15931</td>\n",
       "      <td>0.13047</td>\n",
       "      <td>0.06180</td>\n",
       "      <td>0.11815</td>\n",
       "      <td>0.02204</td>\n",
       "      <td>0.18978</td>\n",
       "      <td>0.13892</td>\n",
       "      <td>0.21159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>0.02117</td>\n",
       "      <td>0.02323</td>\n",
       "      <td>0.02458</td>\n",
       "      <td>0.01038</td>\n",
       "      <td>0.02015</td>\n",
       "      <td>0.01217</td>\n",
       "      <td>0.00824</td>\n",
       "      <td>0.02379</td>\n",
       "      <td>0.01889</td>\n",
       "      <td>0.02125</td>\n",
       "      <td>...</td>\n",
       "      <td>0.02528</td>\n",
       "      <td>0.03038</td>\n",
       "      <td>0.02081</td>\n",
       "      <td>0.02964</td>\n",
       "      <td>0.00700</td>\n",
       "      <td>0.01962</td>\n",
       "      <td>0.00303</td>\n",
       "      <td>0.03120</td>\n",
       "      <td>0.02048</td>\n",
       "      <td>0.02842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>0.13403</td>\n",
       "      <td>0.19872</td>\n",
       "      <td>0.22568</td>\n",
       "      <td>0.09583</td>\n",
       "      <td>0.11528</td>\n",
       "      <td>0.10652</td>\n",
       "      <td>0.08350</td>\n",
       "      <td>0.24187</td>\n",
       "      <td>0.18893</td>\n",
       "      <td>0.16117</td>\n",
       "      <td>...</td>\n",
       "      <td>0.25545</td>\n",
       "      <td>0.27414</td>\n",
       "      <td>0.16558</td>\n",
       "      <td>0.19128</td>\n",
       "      <td>0.08656</td>\n",
       "      <td>0.15128</td>\n",
       "      <td>0.02802</td>\n",
       "      <td>0.21457</td>\n",
       "      <td>0.12155</td>\n",
       "      <td>0.22696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>0.10826</td>\n",
       "      <td>0.15350</td>\n",
       "      <td>0.18711</td>\n",
       "      <td>0.14203</td>\n",
       "      <td>0.09225</td>\n",
       "      <td>0.09372</td>\n",
       "      <td>0.05126</td>\n",
       "      <td>0.25063</td>\n",
       "      <td>0.13281</td>\n",
       "      <td>0.13164</td>\n",
       "      <td>...</td>\n",
       "      <td>0.19200</td>\n",
       "      <td>0.17815</td>\n",
       "      <td>0.10874</td>\n",
       "      <td>0.11231</td>\n",
       "      <td>0.05181</td>\n",
       "      <td>0.11237</td>\n",
       "      <td>0.02279</td>\n",
       "      <td>0.13658</td>\n",
       "      <td>0.07757</td>\n",
       "      <td>0.15388</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>0.16192</td>\n",
       "      <td>0.23974</td>\n",
       "      <td>0.27827</td>\n",
       "      <td>0.09297</td>\n",
       "      <td>0.14599</td>\n",
       "      <td>0.12124</td>\n",
       "      <td>0.08330</td>\n",
       "      <td>0.32918</td>\n",
       "      <td>0.17307</td>\n",
       "      <td>0.18311</td>\n",
       "      <td>...</td>\n",
       "      <td>0.29971</td>\n",
       "      <td>0.27793</td>\n",
       "      <td>0.18513</td>\n",
       "      <td>0.23150</td>\n",
       "      <td>0.09019</td>\n",
       "      <td>0.19534</td>\n",
       "      <td>0.02696</td>\n",
       "      <td>0.23442</td>\n",
       "      <td>0.16604</td>\n",
       "      <td>0.28723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>0.13025</td>\n",
       "      <td>0.18054</td>\n",
       "      <td>0.20011</td>\n",
       "      <td>0.05927</td>\n",
       "      <td>0.12900</td>\n",
       "      <td>0.09161</td>\n",
       "      <td>0.05770</td>\n",
       "      <td>0.21120</td>\n",
       "      <td>0.16069</td>\n",
       "      <td>0.11918</td>\n",
       "      <td>...</td>\n",
       "      <td>0.20791</td>\n",
       "      <td>0.19211</td>\n",
       "      <td>0.12973</td>\n",
       "      <td>0.15506</td>\n",
       "      <td>0.05398</td>\n",
       "      <td>0.12704</td>\n",
       "      <td>0.02205</td>\n",
       "      <td>0.15146</td>\n",
       "      <td>0.12653</td>\n",
       "      <td>0.19308</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>0.07852</td>\n",
       "      <td>0.11597</td>\n",
       "      <td>0.14529</td>\n",
       "      <td>0.07407</td>\n",
       "      <td>0.06043</td>\n",
       "      <td>0.06531</td>\n",
       "      <td>0.04073</td>\n",
       "      <td>0.15349</td>\n",
       "      <td>0.07447</td>\n",
       "      <td>0.10606</td>\n",
       "      <td>...</td>\n",
       "      <td>0.14362</td>\n",
       "      <td>0.12047</td>\n",
       "      <td>0.08029</td>\n",
       "      <td>0.08547</td>\n",
       "      <td>0.03580</td>\n",
       "      <td>0.08473</td>\n",
       "      <td>0.01559</td>\n",
       "      <td>0.10037</td>\n",
       "      <td>0.05678</td>\n",
       "      <td>0.10372</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>228</th>\n",
       "      <td>0.10988</td>\n",
       "      <td>0.15328</td>\n",
       "      <td>0.16118</td>\n",
       "      <td>0.07635</td>\n",
       "      <td>0.10532</td>\n",
       "      <td>0.08171</td>\n",
       "      <td>0.07528</td>\n",
       "      <td>0.19315</td>\n",
       "      <td>0.19108</td>\n",
       "      <td>0.10980</td>\n",
       "      <td>...</td>\n",
       "      <td>0.18657</td>\n",
       "      <td>0.18596</td>\n",
       "      <td>0.10144</td>\n",
       "      <td>0.13209</td>\n",
       "      <td>0.05645</td>\n",
       "      <td>0.18672</td>\n",
       "      <td>0.01848</td>\n",
       "      <td>0.14119</td>\n",
       "      <td>0.10768</td>\n",
       "      <td>0.21201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>229</th>\n",
       "      <td>0.07851</td>\n",
       "      <td>0.12420</td>\n",
       "      <td>0.15513</td>\n",
       "      <td>0.08956</td>\n",
       "      <td>0.06294</td>\n",
       "      <td>0.06058</td>\n",
       "      <td>0.03183</td>\n",
       "      <td>0.19187</td>\n",
       "      <td>0.06742</td>\n",
       "      <td>0.11676</td>\n",
       "      <td>...</td>\n",
       "      <td>0.14577</td>\n",
       "      <td>0.10871</td>\n",
       "      <td>0.08410</td>\n",
       "      <td>0.08115</td>\n",
       "      <td>0.03214</td>\n",
       "      <td>0.07894</td>\n",
       "      <td>0.01360</td>\n",
       "      <td>0.10066</td>\n",
       "      <td>0.06976</td>\n",
       "      <td>0.12683</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>230</th>\n",
       "      <td>0.08083</td>\n",
       "      <td>0.10078</td>\n",
       "      <td>0.12953</td>\n",
       "      <td>0.07269</td>\n",
       "      <td>0.05765</td>\n",
       "      <td>0.05969</td>\n",
       "      <td>0.04769</td>\n",
       "      <td>0.14527</td>\n",
       "      <td>0.09647</td>\n",
       "      <td>0.06950</td>\n",
       "      <td>...</td>\n",
       "      <td>0.12506</td>\n",
       "      <td>0.13033</td>\n",
       "      <td>0.09059</td>\n",
       "      <td>0.11189</td>\n",
       "      <td>0.04753</td>\n",
       "      <td>0.08806</td>\n",
       "      <td>0.01254</td>\n",
       "      <td>0.11357</td>\n",
       "      <td>0.06291</td>\n",
       "      <td>0.10005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>231</th>\n",
       "      <td>0.03807</td>\n",
       "      <td>0.06431</td>\n",
       "      <td>0.08257</td>\n",
       "      <td>0.02891</td>\n",
       "      <td>0.03934</td>\n",
       "      <td>0.02893</td>\n",
       "      <td>0.02030</td>\n",
       "      <td>0.08811</td>\n",
       "      <td>0.05057</td>\n",
       "      <td>0.04103</td>\n",
       "      <td>...</td>\n",
       "      <td>0.07101</td>\n",
       "      <td>0.06410</td>\n",
       "      <td>0.04974</td>\n",
       "      <td>0.04176</td>\n",
       "      <td>0.02125</td>\n",
       "      <td>0.04258</td>\n",
       "      <td>0.00987</td>\n",
       "      <td>0.05678</td>\n",
       "      <td>0.04028</td>\n",
       "      <td>0.05339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>232</th>\n",
       "      <td>0.06112</td>\n",
       "      <td>0.09882</td>\n",
       "      <td>0.13616</td>\n",
       "      <td>0.05422</td>\n",
       "      <td>0.05126</td>\n",
       "      <td>0.04781</td>\n",
       "      <td>0.04522</td>\n",
       "      <td>0.15251</td>\n",
       "      <td>0.09836</td>\n",
       "      <td>0.07964</td>\n",
       "      <td>...</td>\n",
       "      <td>0.12648</td>\n",
       "      <td>0.10922</td>\n",
       "      <td>0.06906</td>\n",
       "      <td>0.07457</td>\n",
       "      <td>0.03278</td>\n",
       "      <td>0.08121</td>\n",
       "      <td>0.01441</td>\n",
       "      <td>0.11264</td>\n",
       "      <td>0.05617</td>\n",
       "      <td>0.09196</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>233</th>\n",
       "      <td>0.07830</td>\n",
       "      <td>0.15326</td>\n",
       "      <td>0.16967</td>\n",
       "      <td>0.08732</td>\n",
       "      <td>0.09575</td>\n",
       "      <td>0.09181</td>\n",
       "      <td>0.05777</td>\n",
       "      <td>0.19515</td>\n",
       "      <td>0.09749</td>\n",
       "      <td>0.09399</td>\n",
       "      <td>...</td>\n",
       "      <td>0.18914</td>\n",
       "      <td>0.14797</td>\n",
       "      <td>0.10435</td>\n",
       "      <td>0.09937</td>\n",
       "      <td>0.04589</td>\n",
       "      <td>0.07384</td>\n",
       "      <td>0.01333</td>\n",
       "      <td>0.10933</td>\n",
       "      <td>0.08813</td>\n",
       "      <td>0.12550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>234</th>\n",
       "      <td>0.15240</td>\n",
       "      <td>0.10249</td>\n",
       "      <td>0.12326</td>\n",
       "      <td>0.16402</td>\n",
       "      <td>0.07053</td>\n",
       "      <td>0.06025</td>\n",
       "      <td>0.03410</td>\n",
       "      <td>0.14300</td>\n",
       "      <td>0.07587</td>\n",
       "      <td>0.07398</td>\n",
       "      <td>...</td>\n",
       "      <td>0.11790</td>\n",
       "      <td>0.13217</td>\n",
       "      <td>0.07085</td>\n",
       "      <td>0.07948</td>\n",
       "      <td>0.03431</td>\n",
       "      <td>0.08484</td>\n",
       "      <td>0.00970</td>\n",
       "      <td>0.09149</td>\n",
       "      <td>0.07136</td>\n",
       "      <td>0.09610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>235</th>\n",
       "      <td>0.04696</td>\n",
       "      <td>0.08492</td>\n",
       "      <td>0.09530</td>\n",
       "      <td>0.04203</td>\n",
       "      <td>0.04993</td>\n",
       "      <td>0.04304</td>\n",
       "      <td>0.02949</td>\n",
       "      <td>0.11234</td>\n",
       "      <td>0.05312</td>\n",
       "      <td>0.06173</td>\n",
       "      <td>...</td>\n",
       "      <td>0.10350</td>\n",
       "      <td>0.11485</td>\n",
       "      <td>0.06533</td>\n",
       "      <td>0.05749</td>\n",
       "      <td>0.02937</td>\n",
       "      <td>0.05246</td>\n",
       "      <td>0.04233</td>\n",
       "      <td>0.07891</td>\n",
       "      <td>0.04708</td>\n",
       "      <td>0.08391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>0.08914</td>\n",
       "      <td>0.11275</td>\n",
       "      <td>0.14697</td>\n",
       "      <td>0.08291</td>\n",
       "      <td>0.05262</td>\n",
       "      <td>0.06599</td>\n",
       "      <td>0.04856</td>\n",
       "      <td>0.15098</td>\n",
       "      <td>0.06667</td>\n",
       "      <td>0.08964</td>\n",
       "      <td>...</td>\n",
       "      <td>0.14631</td>\n",
       "      <td>0.13191</td>\n",
       "      <td>0.06535</td>\n",
       "      <td>0.15872</td>\n",
       "      <td>0.03513</td>\n",
       "      <td>0.09489</td>\n",
       "      <td>0.00976</td>\n",
       "      <td>0.09158</td>\n",
       "      <td>0.04385</td>\n",
       "      <td>0.08751</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>237</th>\n",
       "      <td>0.11050</td>\n",
       "      <td>0.17155</td>\n",
       "      <td>0.19186</td>\n",
       "      <td>0.08560</td>\n",
       "      <td>0.09131</td>\n",
       "      <td>0.09097</td>\n",
       "      <td>0.06045</td>\n",
       "      <td>0.22880</td>\n",
       "      <td>0.20614</td>\n",
       "      <td>0.12162</td>\n",
       "      <td>...</td>\n",
       "      <td>0.20585</td>\n",
       "      <td>0.19802</td>\n",
       "      <td>0.12125</td>\n",
       "      <td>0.17317</td>\n",
       "      <td>0.06054</td>\n",
       "      <td>0.13727</td>\n",
       "      <td>0.01420</td>\n",
       "      <td>0.17526</td>\n",
       "      <td>0.10859</td>\n",
       "      <td>0.15802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>0.20560</td>\n",
       "      <td>0.45880</td>\n",
       "      <td>0.54053</td>\n",
       "      <td>0.16144</td>\n",
       "      <td>0.17808</td>\n",
       "      <td>0.17410</td>\n",
       "      <td>0.10234</td>\n",
       "      <td>0.50739</td>\n",
       "      <td>0.23398</td>\n",
       "      <td>0.23775</td>\n",
       "      <td>...</td>\n",
       "      <td>0.56994</td>\n",
       "      <td>0.33215</td>\n",
       "      <td>0.20075</td>\n",
       "      <td>0.22919</td>\n",
       "      <td>0.10435</td>\n",
       "      <td>0.20589</td>\n",
       "      <td>0.12633</td>\n",
       "      <td>0.29845</td>\n",
       "      <td>0.16134</td>\n",
       "      <td>0.28408</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>239</th>\n",
       "      <td>0.15486</td>\n",
       "      <td>0.50410</td>\n",
       "      <td>0.54739</td>\n",
       "      <td>0.13060</td>\n",
       "      <td>0.16040</td>\n",
       "      <td>0.15040</td>\n",
       "      <td>0.08173</td>\n",
       "      <td>0.43341</td>\n",
       "      <td>0.16176</td>\n",
       "      <td>0.20069</td>\n",
       "      <td>...</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.24572</td>\n",
       "      <td>0.17472</td>\n",
       "      <td>0.17626</td>\n",
       "      <td>0.08405</td>\n",
       "      <td>0.15709</td>\n",
       "      <td>0.28689</td>\n",
       "      <td>0.25589</td>\n",
       "      <td>0.17852</td>\n",
       "      <td>0.24116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>240</th>\n",
       "      <td>0.12591</td>\n",
       "      <td>0.20103</td>\n",
       "      <td>0.23365</td>\n",
       "      <td>0.09218</td>\n",
       "      <td>0.10332</td>\n",
       "      <td>0.12113</td>\n",
       "      <td>0.08749</td>\n",
       "      <td>0.25874</td>\n",
       "      <td>0.17275</td>\n",
       "      <td>0.15127</td>\n",
       "      <td>...</td>\n",
       "      <td>0.24572</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.14386</td>\n",
       "      <td>0.17700</td>\n",
       "      <td>0.08838</td>\n",
       "      <td>0.14591</td>\n",
       "      <td>0.01630</td>\n",
       "      <td>0.19279</td>\n",
       "      <td>0.11850</td>\n",
       "      <td>0.25155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>241</th>\n",
       "      <td>0.09221</td>\n",
       "      <td>0.13672</td>\n",
       "      <td>0.16000</td>\n",
       "      <td>0.05921</td>\n",
       "      <td>0.08538</td>\n",
       "      <td>0.07376</td>\n",
       "      <td>0.04751</td>\n",
       "      <td>0.17991</td>\n",
       "      <td>0.08042</td>\n",
       "      <td>0.10650</td>\n",
       "      <td>...</td>\n",
       "      <td>0.17472</td>\n",
       "      <td>0.14386</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.10250</td>\n",
       "      <td>0.06147</td>\n",
       "      <td>0.09158</td>\n",
       "      <td>0.01413</td>\n",
       "      <td>0.12986</td>\n",
       "      <td>0.08729</td>\n",
       "      <td>0.13901</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>242</th>\n",
       "      <td>0.11318</td>\n",
       "      <td>0.14929</td>\n",
       "      <td>0.18468</td>\n",
       "      <td>0.07375</td>\n",
       "      <td>0.05690</td>\n",
       "      <td>0.07731</td>\n",
       "      <td>0.04556</td>\n",
       "      <td>0.17737</td>\n",
       "      <td>0.12434</td>\n",
       "      <td>0.09937</td>\n",
       "      <td>...</td>\n",
       "      <td>0.17626</td>\n",
       "      <td>0.17700</td>\n",
       "      <td>0.10250</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.04285</td>\n",
       "      <td>0.13446</td>\n",
       "      <td>0.01706</td>\n",
       "      <td>0.12680</td>\n",
       "      <td>0.05085</td>\n",
       "      <td>0.13416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>243</th>\n",
       "      <td>0.02616</td>\n",
       "      <td>0.06043</td>\n",
       "      <td>0.07802</td>\n",
       "      <td>0.03756</td>\n",
       "      <td>0.03659</td>\n",
       "      <td>0.04388</td>\n",
       "      <td>0.03665</td>\n",
       "      <td>0.11308</td>\n",
       "      <td>0.04587</td>\n",
       "      <td>0.05922</td>\n",
       "      <td>...</td>\n",
       "      <td>0.08405</td>\n",
       "      <td>0.08838</td>\n",
       "      <td>0.06147</td>\n",
       "      <td>0.04285</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.03721</td>\n",
       "      <td>0.00791</td>\n",
       "      <td>0.06370</td>\n",
       "      <td>0.03812</td>\n",
       "      <td>0.09227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>244</th>\n",
       "      <td>0.13777</td>\n",
       "      <td>0.13403</td>\n",
       "      <td>0.14582</td>\n",
       "      <td>0.04925</td>\n",
       "      <td>0.05757</td>\n",
       "      <td>0.06658</td>\n",
       "      <td>0.05219</td>\n",
       "      <td>0.15914</td>\n",
       "      <td>0.09731</td>\n",
       "      <td>0.09822</td>\n",
       "      <td>...</td>\n",
       "      <td>0.15709</td>\n",
       "      <td>0.14591</td>\n",
       "      <td>0.09158</td>\n",
       "      <td>0.13446</td>\n",
       "      <td>0.03721</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.01842</td>\n",
       "      <td>0.11455</td>\n",
       "      <td>0.07383</td>\n",
       "      <td>0.12822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>245</th>\n",
       "      <td>0.00555</td>\n",
       "      <td>0.24070</td>\n",
       "      <td>0.21752</td>\n",
       "      <td>0.01871</td>\n",
       "      <td>0.01401</td>\n",
       "      <td>0.02480</td>\n",
       "      <td>0.01117</td>\n",
       "      <td>0.03475</td>\n",
       "      <td>0.01108</td>\n",
       "      <td>0.00917</td>\n",
       "      <td>...</td>\n",
       "      <td>0.28689</td>\n",
       "      <td>0.01630</td>\n",
       "      <td>0.01413</td>\n",
       "      <td>0.01706</td>\n",
       "      <td>0.00791</td>\n",
       "      <td>0.01842</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.02737</td>\n",
       "      <td>0.00712</td>\n",
       "      <td>0.01867</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>246</th>\n",
       "      <td>0.10723</td>\n",
       "      <td>0.21832</td>\n",
       "      <td>0.25073</td>\n",
       "      <td>0.09496</td>\n",
       "      <td>0.11778</td>\n",
       "      <td>0.10961</td>\n",
       "      <td>0.05418</td>\n",
       "      <td>0.26929</td>\n",
       "      <td>0.16015</td>\n",
       "      <td>0.16614</td>\n",
       "      <td>...</td>\n",
       "      <td>0.25589</td>\n",
       "      <td>0.19279</td>\n",
       "      <td>0.12986</td>\n",
       "      <td>0.12680</td>\n",
       "      <td>0.06370</td>\n",
       "      <td>0.11455</td>\n",
       "      <td>0.02737</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.11443</td>\n",
       "      <td>0.19421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>247</th>\n",
       "      <td>0.05787</td>\n",
       "      <td>0.11449</td>\n",
       "      <td>0.13587</td>\n",
       "      <td>0.06481</td>\n",
       "      <td>0.11069</td>\n",
       "      <td>0.06009</td>\n",
       "      <td>0.04220</td>\n",
       "      <td>0.18833</td>\n",
       "      <td>0.11140</td>\n",
       "      <td>0.10291</td>\n",
       "      <td>...</td>\n",
       "      <td>0.17852</td>\n",
       "      <td>0.11850</td>\n",
       "      <td>0.08729</td>\n",
       "      <td>0.05085</td>\n",
       "      <td>0.03812</td>\n",
       "      <td>0.07383</td>\n",
       "      <td>0.00712</td>\n",
       "      <td>0.11443</td>\n",
       "      <td>1.00000</td>\n",
       "      <td>0.15795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>248</th>\n",
       "      <td>0.10710</td>\n",
       "      <td>0.18694</td>\n",
       "      <td>0.23150</td>\n",
       "      <td>0.08932</td>\n",
       "      <td>0.13752</td>\n",
       "      <td>0.09927</td>\n",
       "      <td>0.05506</td>\n",
       "      <td>0.28217</td>\n",
       "      <td>0.13064</td>\n",
       "      <td>0.16906</td>\n",
       "      <td>...</td>\n",
       "      <td>0.24116</td>\n",
       "      <td>0.25155</td>\n",
       "      <td>0.13901</td>\n",
       "      <td>0.13416</td>\n",
       "      <td>0.09227</td>\n",
       "      <td>0.12822</td>\n",
       "      <td>0.01867</td>\n",
       "      <td>0.19421</td>\n",
       "      <td>0.15795</td>\n",
       "      <td>1.00000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>249 rows × 249 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "        col0     col1     col2     col3     col4     col5     col6     col7  \\\n",
       "0    1.00000  0.13074  0.15071  0.05337  0.07692  0.05715  0.03246  0.13397   \n",
       "1    0.13074  1.00000  0.42906  0.10437  0.13335  0.15244  0.06316  0.33175   \n",
       "2    0.15071  0.42906  1.00000  0.14807  0.17398  0.15496  0.07850  0.45667   \n",
       "3    0.05337  0.10437  0.14807  1.00000  0.06599  0.06573  0.03951  0.15739   \n",
       "4    0.07692  0.13335  0.17398  0.06599  1.00000  0.07362  0.03496  0.19353   \n",
       "5    0.05715  0.15244  0.15496  0.06573  0.07362  1.00000  0.04047  0.17547   \n",
       "6    0.03246  0.06316  0.07850  0.03951  0.03496  0.04047  1.00000  0.09304   \n",
       "7    0.13397  0.33175  0.45667  0.15739  0.19353  0.17547  0.09304  1.00000   \n",
       "8    0.07524  0.12327  0.16531  0.08372  0.10675  0.06948  0.04752  0.19088   \n",
       "9    0.09731  0.16180  0.18229  0.08062  0.08951  0.08303  0.04191  0.21597   \n",
       "10   0.14021  0.20744  0.25638  0.07014  0.13943  0.10950  0.05952  0.30852   \n",
       "11   0.02357  0.06311  0.09649  0.03624  0.05851  0.03884  0.02965  0.12875   \n",
       "12   0.08719  0.12794  0.17085  0.06999  0.08295  0.07648  0.05533  0.17643   \n",
       "13   0.06038  0.08462  0.10103  0.03159  0.04157  0.03752  0.02317  0.12649   \n",
       "14   0.14240  0.12440  0.15397  0.21649  0.06960  0.06421  0.04997  0.16593   \n",
       "15   0.07975  0.10839  0.12881  0.05522  0.05348  0.05503  0.04411  0.12265   \n",
       "16   0.04708  0.12851  0.18337  0.11757  0.14834  0.06788  0.04322  0.23519   \n",
       "17   0.06407  0.08127  0.10457  0.05257  0.03777  0.04130  0.02312  0.11070   \n",
       "18   0.04047  0.05792  0.09894  0.05002  0.02423  0.04579  0.03008  0.10223   \n",
       "19   0.14748  0.08439  0.11982  0.05164  0.05155  0.05395  0.02894  0.18960   \n",
       "20   0.05025  0.11157  0.15699  0.06707  0.15787  0.06506  0.04344  0.17419   \n",
       "21   0.02349  0.04908  0.06191  0.01580  0.08027  0.02935  0.09264  0.06092   \n",
       "22   0.08782  0.12176  0.14018  0.06705  0.06383  0.06318  0.05049  0.14998   \n",
       "23   0.04387  0.08481  0.11905  0.05345  0.09947  0.04983  0.02615  0.11690   \n",
       "24   0.03710  0.06286  0.08373  0.02839  0.05035  0.04314  0.01651  0.07749   \n",
       "25   0.06916  0.10820  0.11774  0.06198  0.04488  0.06044  0.03990  0.13566   \n",
       "26   0.11839  0.17773  0.23393  0.11749  0.08429  0.09063  0.04820  0.24368   \n",
       "27   0.03520  0.10019  0.14108  0.07594  0.10897  0.11820  0.03700  0.16958   \n",
       "28   0.06159  0.08573  0.11083  0.04877  0.04021  0.05102  0.03282  0.12743   \n",
       "29   0.07896  0.11944  0.13519  0.06674  0.11139  0.06386  0.04203  0.18301   \n",
       "..       ...      ...      ...      ...      ...      ...      ...      ...   \n",
       "219  0.05518  0.11884  0.15940  0.07528  0.08327  0.07264  0.04782  0.17133   \n",
       "220  0.14481  0.22488  0.24101  0.06842  0.11344  0.09812  0.05753  0.23947   \n",
       "221  0.11180  0.18244  0.19717  0.06674  0.13085  0.08512  0.05442  0.24166   \n",
       "222  0.02117  0.02323  0.02458  0.01038  0.02015  0.01217  0.00824  0.02379   \n",
       "223  0.13403  0.19872  0.22568  0.09583  0.11528  0.10652  0.08350  0.24187   \n",
       "224  0.10826  0.15350  0.18711  0.14203  0.09225  0.09372  0.05126  0.25063   \n",
       "225  0.16192  0.23974  0.27827  0.09297  0.14599  0.12124  0.08330  0.32918   \n",
       "226  0.13025  0.18054  0.20011  0.05927  0.12900  0.09161  0.05770  0.21120   \n",
       "227  0.07852  0.11597  0.14529  0.07407  0.06043  0.06531  0.04073  0.15349   \n",
       "228  0.10988  0.15328  0.16118  0.07635  0.10532  0.08171  0.07528  0.19315   \n",
       "229  0.07851  0.12420  0.15513  0.08956  0.06294  0.06058  0.03183  0.19187   \n",
       "230  0.08083  0.10078  0.12953  0.07269  0.05765  0.05969  0.04769  0.14527   \n",
       "231  0.03807  0.06431  0.08257  0.02891  0.03934  0.02893  0.02030  0.08811   \n",
       "232  0.06112  0.09882  0.13616  0.05422  0.05126  0.04781  0.04522  0.15251   \n",
       "233  0.07830  0.15326  0.16967  0.08732  0.09575  0.09181  0.05777  0.19515   \n",
       "234  0.15240  0.10249  0.12326  0.16402  0.07053  0.06025  0.03410  0.14300   \n",
       "235  0.04696  0.08492  0.09530  0.04203  0.04993  0.04304  0.02949  0.11234   \n",
       "236  0.08914  0.11275  0.14697  0.08291  0.05262  0.06599  0.04856  0.15098   \n",
       "237  0.11050  0.17155  0.19186  0.08560  0.09131  0.09097  0.06045  0.22880   \n",
       "238  0.20560  0.45880  0.54053  0.16144  0.17808  0.17410  0.10234  0.50739   \n",
       "239  0.15486  0.50410  0.54739  0.13060  0.16040  0.15040  0.08173  0.43341   \n",
       "240  0.12591  0.20103  0.23365  0.09218  0.10332  0.12113  0.08749  0.25874   \n",
       "241  0.09221  0.13672  0.16000  0.05921  0.08538  0.07376  0.04751  0.17991   \n",
       "242  0.11318  0.14929  0.18468  0.07375  0.05690  0.07731  0.04556  0.17737   \n",
       "243  0.02616  0.06043  0.07802  0.03756  0.03659  0.04388  0.03665  0.11308   \n",
       "244  0.13777  0.13403  0.14582  0.04925  0.05757  0.06658  0.05219  0.15914   \n",
       "245  0.00555  0.24070  0.21752  0.01871  0.01401  0.02480  0.01117  0.03475   \n",
       "246  0.10723  0.21832  0.25073  0.09496  0.11778  0.10961  0.05418  0.26929   \n",
       "247  0.05787  0.11449  0.13587  0.06481  0.11069  0.06009  0.04220  0.18833   \n",
       "248  0.10710  0.18694  0.23150  0.08932  0.13752  0.09927  0.05506  0.28217   \n",
       "\n",
       "        col8     col9  ...   col239   col240   col241   col242   col243  \\\n",
       "0    0.07524  0.09731  ...  0.15486  0.12591  0.09221  0.11318  0.02616   \n",
       "1    0.12327  0.16180  ...  0.50410  0.20103  0.13672  0.14929  0.06043   \n",
       "2    0.16531  0.18229  ...  0.54739  0.23365  0.16000  0.18468  0.07802   \n",
       "3    0.08372  0.08062  ...  0.13060  0.09218  0.05921  0.07375  0.03756   \n",
       "4    0.10675  0.08951  ...  0.16040  0.10332  0.08538  0.05690  0.03659   \n",
       "5    0.06948  0.08303  ...  0.15040  0.12113  0.07376  0.07731  0.04388   \n",
       "6    0.04752  0.04191  ...  0.08173  0.08749  0.04751  0.04556  0.03665   \n",
       "7    0.19088  0.21597  ...  0.43341  0.25874  0.17991  0.17737  0.11308   \n",
       "8    1.00000  0.09629  ...  0.16176  0.17275  0.08042  0.12434  0.04587   \n",
       "9    0.09629  1.00000  ...  0.20069  0.15127  0.10650  0.09937  0.05922   \n",
       "10   0.15532  0.16094  ...  0.28290  0.21424  0.17613  0.17506  0.07749   \n",
       "11   0.04465  0.03885  ...  0.07777  0.05428  0.04503  0.04058  0.02607   \n",
       "12   0.09895  0.09492  ...  0.18317  0.14080  0.11831  0.12243  0.05117   \n",
       "13   0.04616  0.07013  ...  0.10221  0.10123  0.05960  0.05852  0.02822   \n",
       "14   0.09032  0.09586  ...  0.13621  0.15873  0.09953  0.10405  0.05052   \n",
       "15   0.14184  0.06999  ...  0.14242  0.14690  0.10031  0.09416  0.03490   \n",
       "16   0.09451  0.07082  ...  0.16309  0.11809  0.08425  0.09268  0.05658   \n",
       "17   0.05541  0.06557  ...  0.09491  0.09836  0.05729  0.07279  0.02444   \n",
       "18   0.08565  0.03406  ...  0.07702  0.09178  0.05243  0.06516  0.07202   \n",
       "19   0.05350  0.07653  ...  0.11007  0.10118  0.05653  0.06234  0.04137   \n",
       "20   0.11288  0.07848  ...  0.13620  0.13544  0.09079  0.07560  0.06904   \n",
       "21   0.03737  0.02690  ...  0.05454  0.04737  0.02472  0.02649  0.01469   \n",
       "22   0.15020  0.10244  ...  0.15216  0.17775  0.09068  0.12052  0.04625   \n",
       "23   0.08045  0.12665  ...  0.09532  0.09423  0.06254  0.06729  0.02434   \n",
       "24   0.02551  0.08360  ...  0.08106  0.06040  0.13140  0.03421  0.01785   \n",
       "25   0.08439  0.08582  ...  0.12060  0.16002  0.06591  0.06848  0.03730   \n",
       "26   0.09941  0.12990  ...  0.21293  0.19073  0.11857  0.12718  0.05237   \n",
       "27   0.09112  0.06588  ...  0.12082  0.11247  0.05753  0.06079  0.03454   \n",
       "28   0.05706  0.06403  ...  0.10533  0.08951  0.05941  0.06459  0.03640   \n",
       "29   0.11546  0.08218  ...  0.15512  0.12991  0.09390  0.08614  0.05033   \n",
       "..       ...      ...  ...      ...      ...      ...      ...      ...   \n",
       "219  0.09306  0.10255  ...  0.13814  0.14258  0.09502  0.07760  0.04070   \n",
       "220  0.15823  0.15032  ...  0.28219  0.21168  0.14147  0.16885  0.05392   \n",
       "221  0.14578  0.13269  ...  0.22245  0.19249  0.15931  0.13047  0.06180   \n",
       "222  0.01889  0.02125  ...  0.02528  0.03038  0.02081  0.02964  0.00700   \n",
       "223  0.18893  0.16117  ...  0.25545  0.27414  0.16558  0.19128  0.08656   \n",
       "224  0.13281  0.13164  ...  0.19200  0.17815  0.10874  0.11231  0.05181   \n",
       "225  0.17307  0.18311  ...  0.29971  0.27793  0.18513  0.23150  0.09019   \n",
       "226  0.16069  0.11918  ...  0.20791  0.19211  0.12973  0.15506  0.05398   \n",
       "227  0.07447  0.10606  ...  0.14362  0.12047  0.08029  0.08547  0.03580   \n",
       "228  0.19108  0.10980  ...  0.18657  0.18596  0.10144  0.13209  0.05645   \n",
       "229  0.06742  0.11676  ...  0.14577  0.10871  0.08410  0.08115  0.03214   \n",
       "230  0.09647  0.06950  ...  0.12506  0.13033  0.09059  0.11189  0.04753   \n",
       "231  0.05057  0.04103  ...  0.07101  0.06410  0.04974  0.04176  0.02125   \n",
       "232  0.09836  0.07964  ...  0.12648  0.10922  0.06906  0.07457  0.03278   \n",
       "233  0.09749  0.09399  ...  0.18914  0.14797  0.10435  0.09937  0.04589   \n",
       "234  0.07587  0.07398  ...  0.11790  0.13217  0.07085  0.07948  0.03431   \n",
       "235  0.05312  0.06173  ...  0.10350  0.11485  0.06533  0.05749  0.02937   \n",
       "236  0.06667  0.08964  ...  0.14631  0.13191  0.06535  0.15872  0.03513   \n",
       "237  0.20614  0.12162  ...  0.20585  0.19802  0.12125  0.17317  0.06054   \n",
       "238  0.23398  0.23775  ...  0.56994  0.33215  0.20075  0.22919  0.10435   \n",
       "239  0.16176  0.20069  ...  1.00000  0.24572  0.17472  0.17626  0.08405   \n",
       "240  0.17275  0.15127  ...  0.24572  1.00000  0.14386  0.17700  0.08838   \n",
       "241  0.08042  0.10650  ...  0.17472  0.14386  1.00000  0.10250  0.06147   \n",
       "242  0.12434  0.09937  ...  0.17626  0.17700  0.10250  1.00000  0.04285   \n",
       "243  0.04587  0.05922  ...  0.08405  0.08838  0.06147  0.04285  1.00000   \n",
       "244  0.09731  0.09822  ...  0.15709  0.14591  0.09158  0.13446  0.03721   \n",
       "245  0.01108  0.00917  ...  0.28689  0.01630  0.01413  0.01706  0.00791   \n",
       "246  0.16015  0.16614  ...  0.25589  0.19279  0.12986  0.12680  0.06370   \n",
       "247  0.11140  0.10291  ...  0.17852  0.11850  0.08729  0.05085  0.03812   \n",
       "248  0.13064  0.16906  ...  0.24116  0.25155  0.13901  0.13416  0.09227   \n",
       "\n",
       "      col244   col245   col246   col247   col248  \n",
       "0    0.13777  0.00555  0.10723  0.05787  0.10710  \n",
       "1    0.13403  0.24070  0.21832  0.11449  0.18694  \n",
       "2    0.14582  0.21752  0.25073  0.13587  0.23150  \n",
       "3    0.04925  0.01871  0.09496  0.06481  0.08932  \n",
       "4    0.05757  0.01401  0.11778  0.11069  0.13752  \n",
       "5    0.06658  0.02480  0.10961  0.06009  0.09927  \n",
       "6    0.05219  0.01117  0.05418  0.04220  0.05506  \n",
       "7    0.15914  0.03475  0.26929  0.18833  0.28217  \n",
       "8    0.09731  0.01108  0.16015  0.11140  0.13064  \n",
       "9    0.09822  0.00917  0.16614  0.10291  0.16906  \n",
       "10   0.17048  0.02464  0.20380  0.16687  0.30571  \n",
       "11   0.03566  0.01103  0.05951  0.03865  0.06632  \n",
       "12   0.11661  0.01310  0.14236  0.06443  0.12798  \n",
       "13   0.06257  0.00560  0.07459  0.04067  0.08662  \n",
       "14   0.12976  0.01238  0.11279  0.13280  0.13602  \n",
       "15   0.12943  0.01176  0.11170  0.04829  0.08238  \n",
       "16   0.06454  0.02804  0.14832  0.11145  0.17155  \n",
       "17   0.10297  0.00797  0.08359  0.05183  0.10260  \n",
       "18   0.04487  0.00759  0.05801  0.03329  0.07629  \n",
       "19   0.06118  0.00945  0.07636  0.14846  0.10509  \n",
       "20   0.04954  0.01573  0.10588  0.07955  0.10870  \n",
       "21   0.02582  0.00817  0.03975  0.04786  0.04923  \n",
       "22   0.10609  0.01138  0.12400  0.07461  0.12658  \n",
       "23   0.06480  0.00657  0.11701  0.05994  0.08753  \n",
       "24   0.03669  0.01079  0.05917  0.02506  0.08631  \n",
       "25   0.08546  0.01116  0.09755  0.05025  0.08830  \n",
       "26   0.13445  0.01985  0.14425  0.09007  0.18721  \n",
       "27   0.05019  0.01737  0.09133  0.08139  0.12810  \n",
       "28   0.09016  0.01462  0.07143  0.04304  0.08637  \n",
       "29   0.08821  0.03069  0.10184  0.11401  0.14244  \n",
       "..       ...      ...      ...      ...      ...  \n",
       "219  0.05440  0.01458  0.10061  0.06972  0.10765  \n",
       "220  0.15262  0.03349  0.19640  0.14578  0.21316  \n",
       "221  0.11815  0.02204  0.18978  0.13892  0.21159  \n",
       "222  0.01962  0.00303  0.03120  0.02048  0.02842  \n",
       "223  0.15128  0.02802  0.21457  0.12155  0.22696  \n",
       "224  0.11237  0.02279  0.13658  0.07757  0.15388  \n",
       "225  0.19534  0.02696  0.23442  0.16604  0.28723  \n",
       "226  0.12704  0.02205  0.15146  0.12653  0.19308  \n",
       "227  0.08473  0.01559  0.10037  0.05678  0.10372  \n",
       "228  0.18672  0.01848  0.14119  0.10768  0.21201  \n",
       "229  0.07894  0.01360  0.10066  0.06976  0.12683  \n",
       "230  0.08806  0.01254  0.11357  0.06291  0.10005  \n",
       "231  0.04258  0.00987  0.05678  0.04028  0.05339  \n",
       "232  0.08121  0.01441  0.11264  0.05617  0.09196  \n",
       "233  0.07384  0.01333  0.10933  0.08813  0.12550  \n",
       "234  0.08484  0.00970  0.09149  0.07136  0.09610  \n",
       "235  0.05246  0.04233  0.07891  0.04708  0.08391  \n",
       "236  0.09489  0.00976  0.09158  0.04385  0.08751  \n",
       "237  0.13727  0.01420  0.17526  0.10859  0.15802  \n",
       "238  0.20589  0.12633  0.29845  0.16134  0.28408  \n",
       "239  0.15709  0.28689  0.25589  0.17852  0.24116  \n",
       "240  0.14591  0.01630  0.19279  0.11850  0.25155  \n",
       "241  0.09158  0.01413  0.12986  0.08729  0.13901  \n",
       "242  0.13446  0.01706  0.12680  0.05085  0.13416  \n",
       "243  0.03721  0.00791  0.06370  0.03812  0.09227  \n",
       "244  1.00000  0.01842  0.11455  0.07383  0.12822  \n",
       "245  0.01842  1.00000  0.02737  0.00712  0.01867  \n",
       "246  0.11455  0.02737  1.00000  0.11443  0.19421  \n",
       "247  0.07383  0.00712  0.11443  1.00000  0.15795  \n",
       "248  0.12822  0.01867  0.19421  0.15795  1.00000  \n",
       "\n",
       "[249 rows x 249 columns]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('matrix.csv')\n",
    "df\n",
    "# Run cosineSim() if not been run already (run time ~ 75 minutes)\n",
    "# matrix = cosineSim(data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Query Processing </h3>\n",
    "\n",
    "<p> In order to search the data set and find a best matching document to some query, the query itself must be 'vectorized' (i.e. compute a TF-IDF vector) and that vector must be compared via the cosine similarity to all other documents in the data set. Once completed the results for each query are sorted by cosine similarity output from largest to smallest. We the take the top 10 results and display them below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "queries = [\"\"\"Once upon a time . . . \n",
    "there were three little pigs, \n",
    "who left their mummy and daddy to see the\n",
    "world.\"\"\",\n",
    "\"\"\"There once lived a poor tailor, who had a son called Aladdin, \n",
    "a careless, idle boy who would\n",
    "do nothing but play all day long \n",
    "in the streets with little idle boys like himself.\"\"\"]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Initializing data...\n",
      "Intializing queries...\n",
      "Queries processed!\n",
      "Searching...\n",
      "Done!\n",
      "--- 45.13 seconds ---\n"
     ]
    }
   ],
   "source": [
    "df = retrieval(queries, data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Document\"] = entries\n",
    "\n",
    "df['query1'] = df[\"col0\"]\n",
    "df['query2'] = df[\"col1\"]\n",
    "df.drop(['col0', 'col1'], axis=1)\n",
    "\n",
    "query1 = pd.DataFrame(df['Document'])\n",
    "query1['Score'] = df['query1']\n",
    "\n",
    "query2 = pd.DataFrame(df['Document'])\n",
    "query2['Score'] = df['query2']\n",
    "\n",
    "five_d1 = query1.sort_values(by=['Score'], ascending=False).head(n=10)\n",
    "five_d2 = query2.sort_values(by=['Score'], ascending=False).head(n=10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3> Results </h3>\n",
    "<p> The resultant scores for each query given are displayed in the data frames below.\n",
    "As can be seen, the query returned the most relavent documents by highest score. The validity of this result can be checked by observing the titles of the highest scoring documents!</p>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Document</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>3lpigs.txt</td>\n",
       "      <td>0.40721</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>238</th>\n",
       "      <td>enginer.txt</td>\n",
       "      <td>0.14670</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>gulliver.txt</td>\n",
       "      <td>0.14432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>lgoldbrd.txt</td>\n",
       "      <td>0.14432</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>empty.txt</td>\n",
       "      <td>0.13223</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>ccm.txt</td>\n",
       "      <td>0.13131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5orange.txt</td>\n",
       "      <td>0.12428</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>hound-b.txt</td>\n",
       "      <td>0.11972</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>darkness.txt</td>\n",
       "      <td>0.11508</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>abbey.txt</td>\n",
       "      <td>0.11485</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Document    Score\n",
       "43     3lpigs.txt  0.40721\n",
       "238   enginer.txt  0.14670\n",
       "7    gulliver.txt  0.14432\n",
       "27   lgoldbrd.txt  0.14432\n",
       "160     empty.txt  0.13223\n",
       "81        ccm.txt  0.13131\n",
       "2     5orange.txt  0.12428\n",
       "178   hound-b.txt  0.11972\n",
       "197  darkness.txt  0.11508\n",
       "70      abbey.txt  0.11485"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Query 1\n",
    "five_d1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Document</th>\n",
       "      <th>Score</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>alad10.txt</td>\n",
       "      <td>0.35603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>adv_alad.txt</td>\n",
       "      <td>0.33792</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>tinsoldr.txt</td>\n",
       "      <td>0.16191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>yukon.txt</td>\n",
       "      <td>0.12163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>fantasy.txt</td>\n",
       "      <td>0.12065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>darkness.txt</td>\n",
       "      <td>0.10851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>empty.txt</td>\n",
       "      <td>0.10630</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>236</th>\n",
       "      <td>snowmaid.txt</td>\n",
       "      <td>0.10380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>lmtchgrl.txt</td>\n",
       "      <td>0.10281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>aesop11.txt</td>\n",
       "      <td>0.09160</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Document    Score\n",
       "97     alad10.txt  0.35603\n",
       "28   adv_alad.txt  0.33792\n",
       "116  tinsoldr.txt  0.16191\n",
       "147     yukon.txt  0.12163\n",
       "202   fantasy.txt  0.12065\n",
       "197  darkness.txt  0.10851\n",
       "160     empty.txt  0.10630\n",
       "236  snowmaid.txt  0.10380\n",
       "146  lmtchgrl.txt  0.10281\n",
       "53    aesop11.txt  0.09160"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Query 2\n",
    "five_d2"
   ]
  }
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