Ranking_ITTF_TOP100.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 272,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-12T02:39:17.586903Z",
     "start_time": "2020-02-12T02:39:17.565902Z"
    }
   },
   "outputs": [],
   "source": [
    "import bs4 as bs\n",
    "import urllib.request\n",
    "import json\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "#REFERENCIAS\n",
    "#https://stackoverflow.com/questions/21104592/json-to-pandas-dataframe"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-12T02:39:26.434978Z",
     "start_time": "2020-02-12T02:39:17.593903Z"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2160x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "html_mulheres = urllib.request.urlopen('https://ranking.ittf.com/public/s/ranking/list?category=SEN&typeGender=W%3BSINGLES&year=2020&week=6&offset=0&size=100').read()\n",
    "html_homens   = urllib.request.urlopen('https://ranking.ittf.com/public/s/ranking/list?category=SEN&typeGender=M%3BSINGLES&year=2020&week=6&offset=0&size=100').read()\n",
    "\n",
    "def ranking(html, top):\n",
    "    soup = bs.BeautifulSoup(html, 'lxml') # pega so o html\n",
    "    soup = soup.find(\"p\").get_text('') # pega o json dentro e tira as aspas -> <p>'json'</p>\n",
    "    json_top100 = json.loads(soup)\n",
    "\n",
    "    nome, pais, pontos, rank_atual, rank_anterior, player_id = [], [], [], [], [], []\n",
    "\n",
    "    for elemento in json_top100['ranks']:\n",
    "        rank_anterior.append(elemento['PrevRk'])\n",
    "        rank_atual.append(elemento['Rk'])\n",
    "        pontos.append(elemento['Points'])\n",
    "        pais.append(elemento['Country']['desc'])\n",
    "        nome.append(elemento['Player']['Name'])\n",
    "        player_id.append(elemento['Player']['ittfId'])\n",
    "\n",
    "    df = pd.DataFrame([rank_atual, rank_anterior, pontos, pais, nome, player_id]).T\n",
    "    colunas = ['Ranking Atual','Ranking Anterior', 'Pontos', 'PaÃ­s', 'Nome', 'Id']\n",
    "    df.columns = colunas\n",
    "    return df.head(top)\n",
    "\n",
    "\n",
    "def progresso(ittf_id, sexo): #singles\n",
    "    \n",
    "    url = 'https://ranking.ittf.com/public/s/ranking/progress/'+str(ittf_id)+'?category=SEN&typeGender='+str(sexo)+'%3BSINGLES'\n",
    "    html = urllib.request.urlopen(url).read()\n",
    "    soup = bs.BeautifulSoup(html, 'lxml') # pega so o html\n",
    "    soup = soup.find(\"p\").get_text() # pega o json dentro e tira as aspas -> <p>'json'</p>\n",
    "    json_progresso = json.loads(soup)\n",
    "\n",
    "    data, rank = [], []\n",
    "    for elemento in json_progresso['ranks']:\n",
    "        data.append(elemento['Date'])\n",
    "        rank.append(elemento['Rk'])\n",
    "\n",
    "    df = pd.DataFrame([data, rank]).T\n",
    "    colunas = ['Data', 'Ranking']\n",
    "    df.columns = colunas\n",
    "    x = df['Data']\n",
    "    y = df['Ranking']\n",
    "    fig, ax = plt.subplots(figsize=(30, 10))\n",
    "    plt.gca().invert_yaxis()\n",
    "    plt.xticks(rotation=90)\n",
    "    ax.plot(x, y)\n",
    "    ax.set_xlabel('Data')\n",
    "    ax.set_ylabel('Ranking')\n",
    "    ax.set_title('Progresso do jogador ao longo do tempo')\n",
    "    ax.grid(True)\n",
    "    return plt.show()\n",
    "\n",
    "progresso('112019', 'W')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-12T02:39:26.570983Z",
     "start_time": "2020-02-12T02:39:26.434978Z"
    }
   },
   "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>Ranking Atual</th>\n",
       "      <th>Ranking Anterior</th>\n",
       "      <th>Pontos</th>\n",
       "      <th>PaÃ­s</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>17015</td>\n",
       "      <td>China</td>\n",
       "      <td>CHEN Meng</td>\n",
       "      <td>112019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>15460</td>\n",
       "      <td>China</td>\n",
       "      <td>SUN Yingsha</td>\n",
       "      <td>131163</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>14720</td>\n",
       "      <td>Japan</td>\n",
       "      <td>ITO Mima</td>\n",
       "      <td>117821</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>14425</td>\n",
       "      <td>China</td>\n",
       "      <td>WANG Manyu</td>\n",
       "      <td>121411</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>4</td>\n",
       "      <td>14400</td>\n",
       "      <td>China</td>\n",
       "      <td>LIU Shiwen</td>\n",
       "      <td>105482</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>13450</td>\n",
       "      <td>China</td>\n",
       "      <td>DING Ning</td>\n",
       "      <td>102265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>6</td>\n",
       "      <td>13015</td>\n",
       "      <td>China</td>\n",
       "      <td>ZHU Yuling</td>\n",
       "      <td>117332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>11100</td>\n",
       "      <td>Singapore</td>\n",
       "      <td>FENG Tianwei</td>\n",
       "      <td>102712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>10950</td>\n",
       "      <td>Japan</td>\n",
       "      <td>ISHIKAWA Kasumi</td>\n",
       "      <td>110752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>10</td>\n",
       "      <td>10915</td>\n",
       "      <td>Chinese Taipei</td>\n",
       "      <td>CHENG I-Ching</td>\n",
       "      <td>110797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>11</td>\n",
       "      <td>10815</td>\n",
       "      <td>Japan</td>\n",
       "      <td>HIRANO Miu</td>\n",
       "      <td>117820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>13</td>\n",
       "      <td>10435</td>\n",
       "      <td>China</td>\n",
       "      <td>WANG Yidi</td>\n",
       "      <td>124110</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>12</td>\n",
       "      <td>10145</td>\n",
       "      <td>China</td>\n",
       "      <td>CHEN Xingtong</td>\n",
       "      <td>121403</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>9095</td>\n",
       "      <td>Austria</td>\n",
       "      <td>POLCANOVA Sofia</td>\n",
       "      <td>107477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>15</td>\n",
       "      <td>9060</td>\n",
       "      <td>Hong Kong, China</td>\n",
       "      <td>DOO Hoi Kem</td>\n",
       "      <td>115543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>16</td>\n",
       "      <td>9020</td>\n",
       "      <td>Republic of Korea</td>\n",
       "      <td>JEON Jihee</td>\n",
       "      <td>118994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>18</td>\n",
       "      <td>8660</td>\n",
       "      <td>China</td>\n",
       "      <td>HE Zhuojia</td>\n",
       "      <td>119730</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>17</td>\n",
       "      <td>8550</td>\n",
       "      <td>Japan</td>\n",
       "      <td>SATO Hitomi</td>\n",
       "      <td>122261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>20</td>\n",
       "      <td>8065</td>\n",
       "      <td>Germany</td>\n",
       "      <td>SOLJA Petrissa</td>\n",
       "      <td>111065</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>21</td>\n",
       "      <td>7820</td>\n",
       "      <td>Puerto Rico</td>\n",
       "      <td>DIAZ Adriana</td>\n",
       "      <td>115009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>23</td>\n",
       "      <td>7745</td>\n",
       "      <td>Japan</td>\n",
       "      <td>HAYATA Hina</td>\n",
       "      <td>123672</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>19</td>\n",
       "      <td>7710</td>\n",
       "      <td>Romania</td>\n",
       "      <td>SZOCS Bernadette</td>\n",
       "      <td>111012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>22</td>\n",
       "      <td>7585</td>\n",
       "      <td>Japan</td>\n",
       "      <td>KATO Miyu</td>\n",
       "      <td>117822</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>30</td>\n",
       "      <td>7300</td>\n",
       "      <td>China</td>\n",
       "      <td>QIAN Tianyi</td>\n",
       "      <td>119797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>24</td>\n",
       "      <td>7265</td>\n",
       "      <td>Republic of Korea</td>\n",
       "      <td>SUH Hyowon</td>\n",
       "      <td>108470</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>25</td>\n",
       "      <td>7015</td>\n",
       "      <td>Chinese Taipei</td>\n",
       "      <td>CHEN Szu-Yu</td>\n",
       "      <td>114105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>29</td>\n",
       "      <td>6905</td>\n",
       "      <td>Germany</td>\n",
       "      <td>HAN Ying</td>\n",
       "      <td>118762</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>26</td>\n",
       "      <td>6890</td>\n",
       "      <td>United States</td>\n",
       "      <td>ZHANG Lily</td>\n",
       "      <td>112221</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>28</td>\n",
       "      <td>6750</td>\n",
       "      <td>Hong Kong, China</td>\n",
       "      <td>SOO Wai Yam Minnie</td>\n",
       "      <td>115037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>33</td>\n",
       "      <td>6590</td>\n",
       "      <td>United States</td>\n",
       "      <td>WU Yue</td>\n",
       "      <td>110227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>32</td>\n",
       "      <td>6580</td>\n",
       "      <td>Egypt</td>\n",
       "      <td>MESHREF Dina</td>\n",
       "      <td>111656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>27</td>\n",
       "      <td>6565</td>\n",
       "      <td>Canada</td>\n",
       "      <td>ZHANG Mo</td>\n",
       "      <td>110560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>34</td>\n",
       "      <td>6480</td>\n",
       "      <td>Poland</td>\n",
       "      <td>LI Qian</td>\n",
       "      <td>111882</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>31</td>\n",
       "      <td>6375</td>\n",
       "      <td>Romania</td>\n",
       "      <td>SAMARA Elizabeta</td>\n",
       "      <td>108226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>35</td>\n",
       "      <td>6220</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>EKHOLM Matilda</td>\n",
       "      <td>102472</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>37</td>\n",
       "      <td>6210</td>\n",
       "      <td>China</td>\n",
       "      <td>GU Yuting</td>\n",
       "      <td>115760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>36</td>\n",
       "      <td>6020</td>\n",
       "      <td>Ukraine</td>\n",
       "      <td>PESOTSKA Margaryta</td>\n",
       "      <td>107321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>43</td>\n",
       "      <td>5945</td>\n",
       "      <td>Japan</td>\n",
       "      <td>SHIBATA Saki</td>\n",
       "      <td>123848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>46</td>\n",
       "      <td>5885</td>\n",
       "      <td>Japan</td>\n",
       "      <td>HASHIMOTO Honoka</td>\n",
       "      <td>133000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>40</td>\n",
       "      <td>39</td>\n",
       "      <td>5865</td>\n",
       "      <td>Germany</td>\n",
       "      <td>MITTELHAM Nina</td>\n",
       "      <td>114726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>40</td>\n",
       "      <td>5835</td>\n",
       "      <td>Hong Kong, China</td>\n",
       "      <td>LEE Ho Ching</td>\n",
       "      <td>105159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>42</td>\n",
       "      <td>5785</td>\n",
       "      <td>Thailand</td>\n",
       "      <td>SAWETTABUT Suthasini</td>\n",
       "      <td>111833</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>47</td>\n",
       "      <td>5700</td>\n",
       "      <td>Russian Federation</td>\n",
       "      <td>MIKHAILOVA Polina</td>\n",
       "      <td>106114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>44</td>\n",
       "      <td>38</td>\n",
       "      <td>5690</td>\n",
       "      <td>Hungary</td>\n",
       "      <td>POTA Georgina</td>\n",
       "      <td>107525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>49</td>\n",
       "      <td>5680</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>TAKAHASHI Bruna</td>\n",
       "      <td>121623</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>44</td>\n",
       "      <td>5650</td>\n",
       "      <td>Luxembourg</td>\n",
       "      <td>NI Xia Lian</td>\n",
       "      <td>106706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>45</td>\n",
       "      <td>5555</td>\n",
       "      <td>Netherlands</td>\n",
       "      <td>EERLAND Britt</td>\n",
       "      <td>113701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>50</td>\n",
       "      <td>5420</td>\n",
       "      <td>DPR Korea</td>\n",
       "      <td>KIM Song I</td>\n",
       "      <td>115781</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>51</td>\n",
       "      <td>5395</td>\n",
       "      <td>Japan</td>\n",
       "      <td>KIHARA Miyuu</td>\n",
       "      <td>131036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>48</td>\n",
       "      <td>5360</td>\n",
       "      <td>Czech Republic</td>\n",
       "      <td>MATELOVA Hana</td>\n",
       "      <td>105913</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Ranking Atual Ranking Anterior Pontos                PaÃ­s  \\\n",
       "0              1                1  17015               China   \n",
       "1              2                2  15460               China   \n",
       "2              3                3  14720               Japan   \n",
       "3              4                5  14425               China   \n",
       "4              5                4  14400               China   \n",
       "5              6                7  13450               China   \n",
       "6              7                6  13015               China   \n",
       "7              8                8  11100           Singapore   \n",
       "8              9                9  10950               Japan   \n",
       "9             10               10  10915      Chinese Taipei   \n",
       "10            11               11  10815               Japan   \n",
       "11            12               13  10435               China   \n",
       "12            13               12  10145               China   \n",
       "13            14               14   9095             Austria   \n",
       "14            15               15   9060    Hong Kong, China   \n",
       "15            16               16   9020   Republic of Korea   \n",
       "16            17               18   8660               China   \n",
       "17            18               17   8550               Japan   \n",
       "18            19               20   8065             Germany   \n",
       "19            20               21   7820         Puerto Rico   \n",
       "20            21               23   7745               Japan   \n",
       "21            22               19   7710             Romania   \n",
       "22            23               22   7585               Japan   \n",
       "23            24               30   7300               China   \n",
       "24            25               24   7265   Republic of Korea   \n",
       "25            26               25   7015      Chinese Taipei   \n",
       "26            27               29   6905             Germany   \n",
       "27            28               26   6890       United States   \n",
       "28            29               28   6750    Hong Kong, China   \n",
       "29            30               33   6590       United States   \n",
       "30            31               32   6580               Egypt   \n",
       "31            32               27   6565              Canada   \n",
       "32            33               34   6480              Poland   \n",
       "33            34               31   6375             Romania   \n",
       "34            35               35   6220              Sweden   \n",
       "35            36               37   6210               China   \n",
       "36            37               36   6020             Ukraine   \n",
       "37            38               43   5945               Japan   \n",
       "38            39               46   5885               Japan   \n",
       "39            40               39   5865             Germany   \n",
       "40            41               40   5835    Hong Kong, China   \n",
       "41            42               42   5785            Thailand   \n",
       "42            43               47   5700  Russian Federation   \n",
       "43            44               38   5690             Hungary   \n",
       "44            45               49   5680              Brazil   \n",
       "45            46               44   5650          Luxembourg   \n",
       "46            47               45   5555         Netherlands   \n",
       "47            48               50   5420           DPR Korea   \n",
       "48            49               51   5395               Japan   \n",
       "49            50               48   5360      Czech Republic   \n",
       "\n",
       "                    Nome      Id  \n",
       "0              CHEN Meng  112019  \n",
       "1            SUN Yingsha  131163  \n",
       "2               ITO Mima  117821  \n",
       "3             WANG Manyu  121411  \n",
       "4             LIU Shiwen  105482  \n",
       "5              DING Ning  102265  \n",
       "6             ZHU Yuling  117332  \n",
       "7           FENG Tianwei  102712  \n",
       "8        ISHIKAWA Kasumi  110752  \n",
       "9          CHENG I-Ching  110797  \n",
       "10            HIRANO Miu  117820  \n",
       "11             WANG Yidi  124110  \n",
       "12         CHEN Xingtong  121403  \n",
       "13       POLCANOVA Sofia  107477  \n",
       "14           DOO Hoi Kem  115543  \n",
       "15            JEON Jihee  118994  \n",
       "16            HE Zhuojia  119730  \n",
       "17           SATO Hitomi  122261  \n",
       "18        SOLJA Petrissa  111065  \n",
       "19          DIAZ Adriana  115009  \n",
       "20           HAYATA Hina  123672  \n",
       "21      SZOCS Bernadette  111012  \n",
       "22             KATO Miyu  117822  \n",
       "23           QIAN Tianyi  119797  \n",
       "24            SUH Hyowon  108470  \n",
       "25           CHEN Szu-Yu  114105  \n",
       "26              HAN Ying  118762  \n",
       "27            ZHANG Lily  112221  \n",
       "28    SOO Wai Yam Minnie  115037  \n",
       "29                WU Yue  110227  \n",
       "30          MESHREF Dina  111656  \n",
       "31              ZHANG Mo  110560  \n",
       "32               LI Qian  111882  \n",
       "33      SAMARA Elizabeta  108226  \n",
       "34        EKHOLM Matilda  102472  \n",
       "35             GU Yuting  115760  \n",
       "36    PESOTSKA Margaryta  107321  \n",
       "37          SHIBATA Saki  123848  \n",
       "38      HASHIMOTO Honoka  133000  \n",
       "39        MITTELHAM Nina  114726  \n",
       "40          LEE Ho Ching  105159  \n",
       "41  SAWETTABUT Suthasini  111833  \n",
       "42     MIKHAILOVA Polina  106114  \n",
       "43         POTA Georgina  107525  \n",
       "44       TAKAHASHI Bruna  121623  \n",
       "45           NI Xia Lian  106706  \n",
       "46         EERLAND Britt  113701  \n",
       "47            KIM Song I  115781  \n",
       "48          KIHARA Miyuu  131036  \n",
       "49         MATELOVA Hana  105913  "
      ]
     },
     "execution_count": 274,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking(html_mulheres, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2020-02-12T02:39:26.850999Z",
     "start_time": "2020-02-12T02:39:26.576983Z"
    }
   },
   "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>Ranking Atual</th>\n",
       "      <th>Ranking Anterior</th>\n",
       "      <th>Pontos</th>\n",
       "      <th>PaÃ­s</th>\n",
       "      <th>Nome</th>\n",
       "      <th>Id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>17260</td>\n",
       "      <td>China</td>\n",
       "      <td>XU Xin</td>\n",
       "      <td>110267</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>16915</td>\n",
       "      <td>China</td>\n",
       "      <td>FAN Zhendong</td>\n",
       "      <td>121404</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>16335</td>\n",
       "      <td>China</td>\n",
       "      <td>MA Long</td>\n",
       "      <td>105649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>13915</td>\n",
       "      <td>China</td>\n",
       "      <td>LIN Gaoyuan</td>\n",
       "      <td>115910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>12615</td>\n",
       "      <td>Japan</td>\n",
       "      <td>HARIMOTO Tomokazu</td>\n",
       "      <td>123980</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>12585</td>\n",
       "      <td>Chinese Taipei</td>\n",
       "      <td>LIN Yun-Ju</td>\n",
       "      <td>121582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>12315</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>CALDERANO Hugo</td>\n",
       "      <td>115641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>11630</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>FALCK Mattias</td>\n",
       "      <td>112074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>11205</td>\n",
       "      <td>China</td>\n",
       "      <td>LIANG Jingkun</td>\n",
       "      <td>119588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>11075</td>\n",
       "      <td>Germany</td>\n",
       "      <td>OVTCHAROV Dimitrij</td>\n",
       "      <td>107028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>11</td>\n",
       "      <td>10</td>\n",
       "      <td>10910</td>\n",
       "      <td>Germany</td>\n",
       "      <td>BOLL Timo</td>\n",
       "      <td>101222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>12</td>\n",
       "      <td>15</td>\n",
       "      <td>9570</td>\n",
       "      <td>Japan</td>\n",
       "      <td>NIWA Koki</td>\n",
       "      <td>110729</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>13</td>\n",
       "      <td>13</td>\n",
       "      <td>9555</td>\n",
       "      <td>Republic of Korea</td>\n",
       "      <td>JEOUNG Youngsik</td>\n",
       "      <td>104257</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>14</td>\n",
       "      <td>14</td>\n",
       "      <td>9455</td>\n",
       "      <td>Germany</td>\n",
       "      <td>FRANZISKA Patrick</td>\n",
       "      <td>102832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "      <td>9270</td>\n",
       "      <td>Japan</td>\n",
       "      <td>MIZUTANI Jun</td>\n",
       "      <td>106195</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>16</td>\n",
       "      <td>17</td>\n",
       "      <td>9015</td>\n",
       "      <td>Republic of Korea</td>\n",
       "      <td>JANG Woojin</td>\n",
       "      <td>114936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>17</td>\n",
       "      <td>12</td>\n",
       "      <td>8770</td>\n",
       "      <td>China</td>\n",
       "      <td>WANG Chuqin</td>\n",
       "      <td>121558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>18</td>\n",
       "      <td>18</td>\n",
       "      <td>8710</td>\n",
       "      <td>Nigeria</td>\n",
       "      <td>ARUNA Quadri</td>\n",
       "      <td>112092</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>19</td>\n",
       "      <td>19</td>\n",
       "      <td>8695</td>\n",
       "      <td>Hong Kong, China</td>\n",
       "      <td>WONG Chun Ting</td>\n",
       "      <td>112620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
       "      <td>8620</td>\n",
       "      <td>Republic of Korea</td>\n",
       "      <td>LEE Sangsu</td>\n",
       "      <td>105197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>21</td>\n",
       "      <td>21</td>\n",
       "      <td>8530</td>\n",
       "      <td>France</td>\n",
       "      <td>GAUZY Simon</td>\n",
       "      <td>112062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>22</td>\n",
       "      <td>24</td>\n",
       "      <td>7750</td>\n",
       "      <td>China</td>\n",
       "      <td>ZHAO Zihao</td>\n",
       "      <td>134380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>23</td>\n",
       "      <td>22</td>\n",
       "      <td>7565</td>\n",
       "      <td>England</td>\n",
       "      <td>PITCHFORD Liam</td>\n",
       "      <td>112442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>24</td>\n",
       "      <td>22</td>\n",
       "      <td>7385</td>\n",
       "      <td>Belarus</td>\n",
       "      <td>SAMSONOV Vladimir</td>\n",
       "      <td>108246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>25</td>\n",
       "      <td>27</td>\n",
       "      <td>7190</td>\n",
       "      <td>United States</td>\n",
       "      <td>JHA Kanak</td>\n",
       "      <td>116021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>26</td>\n",
       "      <td>26</td>\n",
       "      <td>7010</td>\n",
       "      <td>Portugal</td>\n",
       "      <td>FREITAS Marcos</td>\n",
       "      <td>102841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>27</td>\n",
       "      <td>28</td>\n",
       "      <td>6900</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>GROTH Jonathan</td>\n",
       "      <td>112409</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>28</td>\n",
       "      <td>25</td>\n",
       "      <td>6835</td>\n",
       "      <td>Sweden</td>\n",
       "      <td>KARLSSON Kristian</td>\n",
       "      <td>104379</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>29</td>\n",
       "      <td>29</td>\n",
       "      <td>6625</td>\n",
       "      <td>Egypt</td>\n",
       "      <td>ASSAR Omar</td>\n",
       "      <td>100696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>30</td>\n",
       "      <td>30</td>\n",
       "      <td>6330</td>\n",
       "      <td>India</td>\n",
       "      <td>GNANASEKARAN Sathiyan</td>\n",
       "      <td>103126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>31</td>\n",
       "      <td>31</td>\n",
       "      <td>6220</td>\n",
       "      <td>Austria</td>\n",
       "      <td>HABESOHN Daniel</td>\n",
       "      <td>103345</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>32</td>\n",
       "      <td>32</td>\n",
       "      <td>5980</td>\n",
       "      <td>Croatia</td>\n",
       "      <td>PUCAR Tomislav</td>\n",
       "      <td>116532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>33</td>\n",
       "      <td>34</td>\n",
       "      <td>5945</td>\n",
       "      <td>Chinese Taipei</td>\n",
       "      <td>CHUANG Chih-Yuan</td>\n",
       "      <td>101820</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>34</td>\n",
       "      <td>33</td>\n",
       "      <td>5910</td>\n",
       "      <td>India</td>\n",
       "      <td>ACHANTA Sharath Kamal</td>\n",
       "      <td>104314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>35</td>\n",
       "      <td>39</td>\n",
       "      <td>5845</td>\n",
       "      <td>Republic of Korea</td>\n",
       "      <td>AN Jaehyun</td>\n",
       "      <td>121514</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>36</td>\n",
       "      <td>35</td>\n",
       "      <td>5775</td>\n",
       "      <td>Austria</td>\n",
       "      <td>GARDOS Robert</td>\n",
       "      <td>102968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>37</td>\n",
       "      <td>38</td>\n",
       "      <td>5765</td>\n",
       "      <td>Slovakia</td>\n",
       "      <td>WANG Yang</td>\n",
       "      <td>112735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>38</td>\n",
       "      <td>36</td>\n",
       "      <td>5635</td>\n",
       "      <td>Germany</td>\n",
       "      <td>FILUS Ruwen</td>\n",
       "      <td>102761</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>39</td>\n",
       "      <td>40</td>\n",
       "      <td>5605</td>\n",
       "      <td>Slovenia</td>\n",
       "      <td>JORGIC Darko</td>\n",
       "      <td>118927</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>40</td>\n",
       "      <td>40</td>\n",
       "      <td>5380</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>TSUBOI Gustavo</td>\n",
       "      <td>109581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>41</td>\n",
       "      <td>37</td>\n",
       "      <td>5310</td>\n",
       "      <td>France</td>\n",
       "      <td>LEBESSON Emmanuel</td>\n",
       "      <td>105136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>42</td>\n",
       "      <td>48</td>\n",
       "      <td>5285</td>\n",
       "      <td>Germany</td>\n",
       "      <td>DUDA Benedikt</td>\n",
       "      <td>116620</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>43</td>\n",
       "      <td>42</td>\n",
       "      <td>5195</td>\n",
       "      <td>Japan</td>\n",
       "      <td>MORIZONO Masataka</td>\n",
       "      <td>112580</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>44</td>\n",
       "      <td>53</td>\n",
       "      <td>5110</td>\n",
       "      <td>Croatia</td>\n",
       "      <td>GACINA Andrej</td>\n",
       "      <td>102891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>5080</td>\n",
       "      <td>Czech Republic</td>\n",
       "      <td>SIRUCEK Pavel</td>\n",
       "      <td>113243</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>46</td>\n",
       "      <td>44</td>\n",
       "      <td>5055</td>\n",
       "      <td>Japan</td>\n",
       "      <td>JIN Takuya</td>\n",
       "      <td>117336</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>47</td>\n",
       "      <td>46</td>\n",
       "      <td>4950</td>\n",
       "      <td>Belgium</td>\n",
       "      <td>NUYTINCK Cedric</td>\n",
       "      <td>106814</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>48</td>\n",
       "      <td>46</td>\n",
       "      <td>4860</td>\n",
       "      <td>Greece</td>\n",
       "      <td>GIONIS Panagiotis</td>\n",
       "      <td>103107</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>49</td>\n",
       "      <td>43</td>\n",
       "      <td>4840</td>\n",
       "      <td>Republic of Korea</td>\n",
       "      <td>LIM Jonghoon</td>\n",
       "      <td>117357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>50</td>\n",
       "      <td>50</td>\n",
       "      <td>4830</td>\n",
       "      <td>Japan</td>\n",
       "      <td>YOSHIMURA Kazuhiro</td>\n",
       "      <td>123962</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Ranking Atual Ranking Anterior Pontos               PaÃ­s  \\\n",
       "0              1                2  17260              China   \n",
       "1              2                1  16915              China   \n",
       "2              3                3  16335              China   \n",
       "3              4                4  13915              China   \n",
       "4              5                5  12615              Japan   \n",
       "5              6                6  12585     Chinese Taipei   \n",
       "6              7                7  12315             Brazil   \n",
       "7              8                8  11630             Sweden   \n",
       "8              9                9  11205              China   \n",
       "9             10               11  11075            Germany   \n",
       "10            11               10  10910            Germany   \n",
       "11            12               15   9570              Japan   \n",
       "12            13               13   9555  Republic of Korea   \n",
       "13            14               14   9455            Germany   \n",
       "14            15               16   9270              Japan   \n",
       "15            16               17   9015  Republic of Korea   \n",
       "16            17               12   8770              China   \n",
       "17            18               18   8710            Nigeria   \n",
       "18            19               19   8695   Hong Kong, China   \n",
       "19            20               20   8620  Republic of Korea   \n",
       "20            21               21   8530             France   \n",
       "21            22               24   7750              China   \n",
       "22            23               22   7565            England   \n",
       "23            24               22   7385            Belarus   \n",
       "24            25               27   7190      United States   \n",
       "25            26               26   7010           Portugal   \n",
       "26            27               28   6900            Denmark   \n",
       "27            28               25   6835             Sweden   \n",
       "28            29               29   6625              Egypt   \n",
       "29            30               30   6330              India   \n",
       "30            31               31   6220            Austria   \n",
       "31            32               32   5980            Croatia   \n",
       "32            33               34   5945     Chinese Taipei   \n",
       "33            34               33   5910              India   \n",
       "34            35               39   5845  Republic of Korea   \n",
       "35            36               35   5775            Austria   \n",
       "36            37               38   5765           Slovakia   \n",
       "37            38               36   5635            Germany   \n",
       "38            39               40   5605           Slovenia   \n",
       "39            40               40   5380             Brazil   \n",
       "40            41               37   5310             France   \n",
       "41            42               48   5285            Germany   \n",
       "42            43               42   5195              Japan   \n",
       "43            44               53   5110            Croatia   \n",
       "44            45               45   5080     Czech Republic   \n",
       "45            46               44   5055              Japan   \n",
       "46            47               46   4950            Belgium   \n",
       "47            48               46   4860             Greece   \n",
       "48            49               43   4840  Republic of Korea   \n",
       "49            50               50   4830              Japan   \n",
       "\n",
       "                     Nome      Id  \n",
       "0                  XU Xin  110267  \n",
       "1            FAN Zhendong  121404  \n",
       "2                 MA Long  105649  \n",
       "3             LIN Gaoyuan  115910  \n",
       "4       HARIMOTO Tomokazu  123980  \n",
       "5              LIN Yun-Ju  121582  \n",
       "6          CALDERANO Hugo  115641  \n",
       "7           FALCK Mattias  112074  \n",
       "8           LIANG Jingkun  119588  \n",
       "9      OVTCHAROV Dimitrij  107028  \n",
       "10              BOLL Timo  101222  \n",
       "11              NIWA Koki  110729  \n",
       "12        JEOUNG Youngsik  104257  \n",
       "13      FRANZISKA Patrick  102832  \n",
       "14           MIZUTANI Jun  106195  \n",
       "15            JANG Woojin  114936  \n",
       "16            WANG Chuqin  121558  \n",
       "17           ARUNA Quadri  112092  \n",
       "18         WONG Chun Ting  112620  \n",
       "19             LEE Sangsu  105197  \n",
       "20            GAUZY Simon  112062  \n",
       "21             ZHAO Zihao  134380  \n",
       "22         PITCHFORD Liam  112442  \n",
       "23      SAMSONOV Vladimir  108246  \n",
       "24              JHA Kanak  116021  \n",
       "25         FREITAS Marcos  102841  \n",
       "26         GROTH Jonathan  112409  \n",
       "27      KARLSSON Kristian  104379  \n",
       "28             ASSAR Omar  100696  \n",
       "29  GNANASEKARAN Sathiyan  103126  \n",
       "30        HABESOHN Daniel  103345  \n",
       "31         PUCAR Tomislav  116532  \n",
       "32       CHUANG Chih-Yuan  101820  \n",
       "33  ACHANTA Sharath Kamal  104314  \n",
       "34             AN Jaehyun  121514  \n",
       "35          GARDOS Robert  102968  \n",
       "36              WANG Yang  112735  \n",
       "37            FILUS Ruwen  102761  \n",
       "38           JORGIC Darko  118927  \n",
       "39         TSUBOI Gustavo  109581  \n",
       "40      LEBESSON Emmanuel  105136  \n",
       "41          DUDA Benedikt  116620  \n",
       "42      MORIZONO Masataka  112580  \n",
       "43          GACINA Andrej  102891  \n",
       "44          SIRUCEK Pavel  113243  \n",
       "45             JIN Takuya  117336  \n",
       "46        NUYTINCK Cedric  106814  \n",
       "47      GIONIS Panagiotis  103107  \n",
       "48           LIM Jonghoon  117357  \n",
       "49     YOSHIMURA Kazuhiro  123962  "
      ]
     },
     "execution_count": 275,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ranking(html_homens, 50)"
   ]
  }
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