32-rotulagem-pais-sobrenome.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#BASE = 'dados/afastamentos'\n",
    "BASE = 'dados/cadastro'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(BASE + '-sobrenomes.csv', index_col=0,\n",
    "                 dtype={'QTDE': 'uint32', 'PERC': np.float32})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(df[df.index.isna()].index, inplace=True)\n",
    "#df = df.loc[~df.index.isna()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\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>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SILVA</th>\n",
       "      <td>48617</td>\n",
       "      <td>7.5320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANTOS</th>\n",
       "      <td>26656</td>\n",
       "      <td>4.1297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLIVEIRA</th>\n",
       "      <td>21617</td>\n",
       "      <td>3.3490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOUZA</th>\n",
       "      <td>15604</td>\n",
       "      <td>2.4174</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIMA</th>\n",
       "      <td>11941</td>\n",
       "      <td>1.8500</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           QTDE    PERC\n",
       "UNOME                  \n",
       "SILVA     48617  7.5320\n",
       "SANTOS    26656  4.1297\n",
       "OLIVEIRA  21617  3.3490\n",
       "SOUZA     15604  2.4174\n",
       "LIMA      11941  1.8500"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "QTDE     uint32\n",
       "PERC    float32\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .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>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SILVA</th>\n",
       "      <td>48617</td>\n",
       "      <td>7.5320</td>\n",
       "      <td>AVLIS</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANTOS</th>\n",
       "      <td>26656</td>\n",
       "      <td>4.1297</td>\n",
       "      <td>SOTNAS</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLIVEIRA</th>\n",
       "      <td>21617</td>\n",
       "      <td>3.3490</td>\n",
       "      <td>ARIEVILO</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOUZA</th>\n",
       "      <td>15604</td>\n",
       "      <td>2.4174</td>\n",
       "      <td>AZUOS</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIMA</th>\n",
       "      <td>11941</td>\n",
       "      <td>1.8500</td>\n",
       "      <td>AMIL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           QTDE    PERC       REV  PAIS\n",
       "UNOME                                  \n",
       "SILVA     48617  7.5320     AVLIS  None\n",
       "SANTOS    26656  4.1297    SOTNAS  None\n",
       "OLIVEIRA  21617  3.3490  ARIEVILO  None\n",
       "SOUZA     15604  2.4174     AZUOS  None\n",
       "LIMA      11941  1.8500      AMIL  None"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df['LETRAS'] = 0\n",
    "df['REV'] = df.index\n",
    "df['REV'] = df['REV'].apply(lambda x: x[::-1])\n",
    "#df['LETRAS'] = df['REV'].apply(lambda x: len(x))\n",
    "df['PAIS'] = None\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "QTDE     uint32\n",
       "PERC    float32\n",
       "REV      object\n",
       "PAIS     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "maior = df['LETRAS'].max()\n",
    "maior"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "maior = 16 # fixado para o maior arquivo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Constantes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "PORTUGAL = 'PT'\n",
    "ESPANHA = 'ES'\n",
    "ITALIA = 'IT'\n",
    "ALEMANHA = 'DE'\n",
    "FRANCA = 'FR'\n",
    "JAPAO = 'JP'\n",
    "POLONIA = 'PL'\n",
    "RUSSIA = 'RU'\n",
    "UCRANIA = 'UA'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1) Espanhol se terminar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "sufixos = [\n",
    "\"EZ\",\n",
    "\"LLO\",\n",
    "\"LLON\",\n",
    "]\n",
    "\n",
    "for suf in sufixos:\n",
    "    df.loc[df['REV'].str.startswith(suf[::-1]), 'PAIS'] = ESPANHA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.1) Italiano se terminar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "sufixos = [\n",
    "\"CHIA\",\n",
    "\"ETTA\",\n",
    "\"GLIA\",\n",
    "\"INI\",\n",
    "\"IERI\",\n",
    "\"ELLA\",\n",
    "\"ELLI\",\n",
    "\"ELLO\",\n",
    "\"ETTI\",\n",
    "\"ETTO\",\n",
    "\"ONI\",\n",
    "\"ONO\",\n",
    "\"OTTI\",\n",
    "\"OTTO\",\n",
    "]\n",
    "\n",
    "for suf in sufixos:\n",
    "    df.loc[df['REV'].str.startswith(suf[::-1]), 'PAIS'] = ITALIA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2.2) Italiano se contiver ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "termos = [\n",
    "\"CCH\",\n",
    "\"GH\",\n",
    "\"ZZ\",\n",
    "]\n",
    "\n",
    "for termo in termos:\n",
    "    df.loc[df['REV'].str.contains(termo), 'PAIS'] = ITALIA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3) Francês se terminar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "sufixos = [\n",
    "\"AMP\",\n",
    "\"ARD\",\n",
    "\"AUD\",\n",
    "\"AUX\",\n",
    "\"EAU\",\n",
    "\"EAULT\",\n",
    "\"ET\",\n",
    "\"EU\",\n",
    "\"EUX\",\n",
    "\"IEU\",\n",
    "\"ILLE\",\n",
    "\"IER\",\n",
    "\"OT\",\n",
    "\"OIS\",\n",
    "\"OIT\",\n",
    "\"OUX\",\n",
    "\"FORT\",\n",
    "\"GNE\",\n",
    "\"MONT\"\n",
    "]\n",
    "\n",
    "for suf in sufixos:\n",
    "    df.loc[df['REV'].str.startswith(suf[::-1]), 'PAIS'] = FRANCA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.1) Alemão se terminar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "sufixos = [\n",
    "\"BACH\",\n",
    "\"TNER\",\n",
    "\"STEIN\",\n",
    "\"MANN\",\n",
    "\"ULLER\",\n",
    "\"HOFF\",\n",
    "\"WALD\",\n",
    "\"BAUM\",\n",
    "\"BERG\",\n",
    "\"BERGER\",\n",
    "\"HAUS\",\n",
    "\"MAYER\",\n",
    "\"GARTEN\",\n",
    "\"AUER\",\n",
    "\"KAMP\",\n",
    "\"HARDT\",\n",
    "\"RINGER\",\n",
    "\"STIEL\",\n",
    "\"HEIM\",\n",
    "\"FELD\",\n",
    "\"FELDT\",\n",
    "\"HORN\",\n",
    "\"BURG\",\n",
    "\"FRIED\",\n",
    "\"KOPF\",\n",
    "\"REICH\",\n",
    "\"MEISTER\",\n",
    "\"MEYER\",\n",
    "\"BLATT\",\n",
    "\"INGER\",\n",
    "\"MACHER\",\n",
    "\"HOLZ\"\n",
    "]\n",
    "\n",
    "for suf in sufixos:\n",
    "    df.loc[df['REV'].str.startswith(suf[::-1]), 'PAIS'] = ALEMANHA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4.2) Alemão se iniciar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "prefixos = [\n",
    "\"HOFF\",\n",
    "\"HART\",\n",
    "\"BERG\",\n",
    "\"SCHU\",\n",
    "\"BECKEN\",\n",
    "]\n",
    "\n",
    "for pref in prefixos:\n",
    "    df.loc[df.index.str.startswith(pref), 'PAIS'] = ALEMANHA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.1) Japonês se terminar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "sufixos = [\n",
    "\"AKA\",\n",
    "\"AKI\",\n",
    "\"ASHI\",\n",
    "\"ATSU\",\n",
    "\"AWA\",\n",
    "\"HARA\",\n",
    "\"HARU\",\n",
    "\"HIDA\",\n",
    "\"HIMA\",\n",
    "\"HIRO\",\n",
    "\"KITA\",\n",
    "\"OKA\",\n",
    "\"OSHI\",\n",
    "\"MARU\",\n",
    "\"MORI\",\n",
    "\"MOTO\",\n",
    "\"MURA\",\n",
    "\"NAGA\",\n",
    "\"NAKA\",\n",
    "\"RAYA\",\n",
    "\"UCHI\",\n",
    "\"UKA\",\n",
    "\"UMA\",\n",
    "\"YAMA\",\n",
    "]\n",
    "\n",
    "for suf in sufixos:\n",
    "    df.loc[df['REV'].str.startswith(suf[::-1]), 'PAIS'] = JAPAO"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5.2) Japonês se iniciar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "prefixos = [\n",
    "\"MATSU\",\n",
    "\"FUJI\",\n",
    "\"KOBA\",\n",
    "\"YAMA\",\n",
    "\"SAKI\",\n",
    "\"SAKA\",\n",
    "\"NAKA\",\n",
    "\"TAKA\",\n",
    "\"TAKE\",\n",
    "\"YOSHI\",\n",
    "\"NISHI\",\n",
    "\"UEM\",\n",
    "\"OKU\",\n",
    "\"OKI\",\n",
    "\"YOKO\",\n",
    "\"MIYA\",\n",
    "\"NISI\",\n",
    "\"MORI\",\n",
    "\"TASHI\",\n",
    "]\n",
    "\n",
    "for pref in prefixos:\n",
    "    df.loc[df.index.str.startswith(pref), 'PAIS'] = JAPAO"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 6) Polonês se terminar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "sufixos = [\n",
    "\"EVSKI\",\n",
    "\"EWSKI\",\n",
    "\"INSKI\",\n",
    "\"INSKY\",\n",
    "\"OVSKI\",\n",
    "\"OWSKI\",\n",
    "\"VICZ\",\n",
    "\"WICZ\",\n",
    "]\n",
    "\n",
    "for suf in sufixos:\n",
    "    df.loc[df['REV'].str.startswith(suf[::-1]), 'PAIS'] = POLONIA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 7) Russo se terminar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "sufixos = [\n",
    "\"VANOV\",\n",
    "\"VITCH\",\n",
    "]\n",
    "\n",
    "for suf in sufixos:\n",
    "    df.loc[df['REV'].str.startswith(suf[::-1]), 'PAIS'] = RUSSIA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8) Ucraniano se terminar com ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "sufixos = [\n",
    "\"CZUK\",\n",
    "\"CZYK\",\n",
    "]\n",
    "\n",
    "for suf in sufixos:\n",
    "    df.loc[df['REV'].str.startswith(suf[::-1]), 'PAIS'] = UCRANIA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "IT:\n",
    ".XXX\n",
    ".XX.\n",
    "\n",
    "DE:\n",
    ".XXX\n",
    "\n",
    "PL:\n",
    ".XXX\n",
    "\n",
    "RU:\n",
    ".XXX\n",
    "\n",
    "UA:\n",
    ".XXX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 8) Sobrenomes Espanhóis ainda não classificados ou reclassificados"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "nomes = []\n",
    "with open('sobrenomes-espanhois.txt', 'r') as f:\n",
    "    nomes = [nome.rstrip() for nome in f.readlines()]\n",
    "\n",
    "for nome in nomes:\n",
    "    df.loc[df['REV'] == nome[::-1], 'PAIS'] = ESPANHA"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 9) Sobrenomes Portugueses ainda não classificados ou reclassificados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "nomes = []\n",
    "with open('rotulagem/sobrenomes-portugueses.txt', 'r') as f:\n",
    "    nomes = [nome.rstrip() for nome in f.readlines()]\n",
    "\n",
    "for nome in nomes:\n",
    "    df.loc[df['REV'] == nome[::-1], 'PAIS'] = PORTUGAL"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Testes individuais"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "QTDE      4204\n",
       "PERC    0.6513\n",
       "REV       OLEM\n",
       "PAIS        PT\n",
       "Name: MELO, dtype: object"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc['MELO']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Casos indefinidos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DANTAS</th>\n",
       "      <td>1327</td>\n",
       "      <td>0.2056</td>\n",
       "      <td>SATNAD</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAIVA</th>\n",
       "      <td>1173</td>\n",
       "      <td>0.1817</td>\n",
       "      <td>AVIAP</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TORRES</th>\n",
       "      <td>1128</td>\n",
       "      <td>0.1748</td>\n",
       "      <td>SERROT</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CHAVES</th>\n",
       "      <td>1071</td>\n",
       "      <td>0.1659</td>\n",
       "      <td>SEVAHC</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEAL</th>\n",
       "      <td>1062</td>\n",
       "      <td>0.1645</td>\n",
       "      <td>LAEL</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        QTDE    PERC     REV  PAIS\n",
       "UNOME                             \n",
       "DANTAS  1327  0.2056  SATNAD  None\n",
       "PAIVA   1173  0.1817   AVIAP  None\n",
       "TORRES  1128  0.1748  SERROT  None\n",
       "CHAVES  1071  0.1659  SEVAHC  None\n",
       "LEAL    1062  0.1645    LAEL  None"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'].isnull()].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Análise dos resultados por país"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "\n",
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       "        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>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>SILVA</th>\n",
       "      <td>48617</td>\n",
       "      <td>7.5320</td>\n",
       "      <td>AVLIS</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANTOS</th>\n",
       "      <td>26656</td>\n",
       "      <td>4.1297</td>\n",
       "      <td>SOTNAS</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OLIVEIRA</th>\n",
       "      <td>21617</td>\n",
       "      <td>3.3490</td>\n",
       "      <td>ARIEVILO</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SOUZA</th>\n",
       "      <td>15604</td>\n",
       "      <td>2.4174</td>\n",
       "      <td>AZUOS</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIMA</th>\n",
       "      <td>11941</td>\n",
       "      <td>1.8500</td>\n",
       "      <td>AMIL</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>COSTA</th>\n",
       "      <td>11019</td>\n",
       "      <td>1.7071</td>\n",
       "      <td>ATSOC</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PEREIRA</th>\n",
       "      <td>8645</td>\n",
       "      <td>1.3393</td>\n",
       "      <td>ARIEREP</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FERREIRA</th>\n",
       "      <td>8365</td>\n",
       "      <td>1.2959</td>\n",
       "      <td>ARIERREF</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARAUJO</th>\n",
       "      <td>7969</td>\n",
       "      <td>1.2346</td>\n",
       "      <td>OJUARA</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CARVALHO</th>\n",
       "      <td>7319</td>\n",
       "      <td>1.1339</td>\n",
       "      <td>OHLAVRAC</td>\n",
       "      <td>PT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           QTDE    PERC       REV PAIS\n",
       "UNOME                                 \n",
       "SILVA     48617  7.5320     AVLIS   PT\n",
       "SANTOS    26656  4.1297    SOTNAS   PT\n",
       "OLIVEIRA  21617  3.3490  ARIEVILO   PT\n",
       "SOUZA     15604  2.4174     AZUOS   PT\n",
       "LIMA      11941  1.8500      AMIL   PT\n",
       "COSTA     11019  1.7071     ATSOC   PT\n",
       "PEREIRA    8645  1.3393   ARIEREP   PT\n",
       "FERREIRA   8365  1.2959  ARIERREF   PT\n",
       "ARAUJO     7969  1.2346    OJUARA   PT\n",
       "CARVALHO   7319  1.1339  OHLAVRAC   PT"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == PORTUGAL].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>PEREZ</th>\n",
       "      <td>242</td>\n",
       "      <td>0.0375</td>\n",
       "      <td>ZEREP</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MARTINEZ</th>\n",
       "      <td>222</td>\n",
       "      <td>0.0344</td>\n",
       "      <td>ZENITRAM</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GONZALEZ</th>\n",
       "      <td>220</td>\n",
       "      <td>0.0341</td>\n",
       "      <td>ZELAZNOG</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RODRIGUEZ</th>\n",
       "      <td>216</td>\n",
       "      <td>0.0335</td>\n",
       "      <td>ZEUGIRDOR</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FERNANDEZ</th>\n",
       "      <td>159</td>\n",
       "      <td>0.0246</td>\n",
       "      <td>ZEDNANREF</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SANCHEZ</th>\n",
       "      <td>124</td>\n",
       "      <td>0.0192</td>\n",
       "      <td>ZEHCNAS</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CORTEZ</th>\n",
       "      <td>118</td>\n",
       "      <td>0.0183</td>\n",
       "      <td>ZETROC</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LOPEZ</th>\n",
       "      <td>116</td>\n",
       "      <td>0.0180</td>\n",
       "      <td>ZEPOL</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALVAREZ</th>\n",
       "      <td>115</td>\n",
       "      <td>0.0178</td>\n",
       "      <td>ZERAVLA</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HERNANDEZ</th>\n",
       "      <td>103</td>\n",
       "      <td>0.0160</td>\n",
       "      <td>ZEDNANREH</td>\n",
       "      <td>ES</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           QTDE    PERC        REV PAIS\n",
       "UNOME                                  \n",
       "PEREZ       242  0.0375      ZEREP   ES\n",
       "MARTINEZ    222  0.0344   ZENITRAM   ES\n",
       "GONZALEZ    220  0.0341   ZELAZNOG   ES\n",
       "RODRIGUEZ   216  0.0335  ZEUGIRDOR   ES\n",
       "FERNANDEZ   159  0.0246  ZEDNANREF   ES\n",
       "SANCHEZ     124  0.0192    ZEHCNAS   ES\n",
       "CORTEZ      118  0.0183     ZETROC   ES\n",
       "LOPEZ       116  0.0180      ZEPOL   ES\n",
       "ALVAREZ     115  0.0178    ZERAVLA   ES\n",
       "HERNANDEZ   103  0.0160  ZEDNANREH   ES"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == ESPANHA].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BELLO</th>\n",
       "      <td>81</td>\n",
       "      <td>0.0125</td>\n",
       "      <td>OLLEB</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RABELLO</th>\n",
       "      <td>77</td>\n",
       "      <td>0.0119</td>\n",
       "      <td>OLLEBAR</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MARTINI</th>\n",
       "      <td>72</td>\n",
       "      <td>0.0112</td>\n",
       "      <td>INITRAM</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PORTELLA</th>\n",
       "      <td>67</td>\n",
       "      <td>0.0104</td>\n",
       "      <td>ALLETROP</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BARBIERI</th>\n",
       "      <td>63</td>\n",
       "      <td>0.0098</td>\n",
       "      <td>IREIBRAB</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MARTINELLI</th>\n",
       "      <td>62</td>\n",
       "      <td>0.0096</td>\n",
       "      <td>ILLENITRAM</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BARRETTO</th>\n",
       "      <td>54</td>\n",
       "      <td>0.0084</td>\n",
       "      <td>OTTERRAB</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>REBELLO</th>\n",
       "      <td>53</td>\n",
       "      <td>0.0082</td>\n",
       "      <td>OLLEBER</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZANELLA</th>\n",
       "      <td>52</td>\n",
       "      <td>0.0081</td>\n",
       "      <td>ALLENAZ</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>VENTURINI</th>\n",
       "      <td>49</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>INIRUTNEV</td>\n",
       "      <td>IT</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            QTDE    PERC         REV PAIS\n",
       "UNOME                                    \n",
       "BELLO         81  0.0125       OLLEB   IT\n",
       "RABELLO       77  0.0119     OLLEBAR   IT\n",
       "MARTINI       72  0.0112     INITRAM   IT\n",
       "PORTELLA      67  0.0104    ALLETROP   IT\n",
       "BARBIERI      63  0.0098    IREIBRAB   IT\n",
       "MARTINELLI    62  0.0096  ILLENITRAM   IT\n",
       "BARRETTO      54  0.0084    OTTERRAB   IT\n",
       "REBELLO       53  0.0082     OLLEBER   IT\n",
       "ZANELLA       52  0.0081     ALLENAZ   IT\n",
       "VENTURINI     49  0.0076   INIRUTNEV   IT"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == ITALIA].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>MULLER</th>\n",
       "      <td>251</td>\n",
       "      <td>0.0389</td>\n",
       "      <td>RELLUM</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HOFFMANN</th>\n",
       "      <td>93</td>\n",
       "      <td>0.0144</td>\n",
       "      <td>NNAMFFOH</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STEIN</th>\n",
       "      <td>61</td>\n",
       "      <td>0.0095</td>\n",
       "      <td>NIETS</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZIMMERMANN</th>\n",
       "      <td>55</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>NNAMREMMIZ</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HARTMANN</th>\n",
       "      <td>55</td>\n",
       "      <td>0.0085</td>\n",
       "      <td>NNAMTRAH</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEYER</th>\n",
       "      <td>53</td>\n",
       "      <td>0.0082</td>\n",
       "      <td>REYEM</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAYER</th>\n",
       "      <td>50</td>\n",
       "      <td>0.0077</td>\n",
       "      <td>REYAM</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NEUMANN</th>\n",
       "      <td>39</td>\n",
       "      <td>0.0060</td>\n",
       "      <td>NNAMUEN</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SCHULTZ</th>\n",
       "      <td>39</td>\n",
       "      <td>0.0060</td>\n",
       "      <td>ZTLUHCS</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HORN</th>\n",
       "      <td>36</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>NROH</td>\n",
       "      <td>DE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            QTDE    PERC         REV PAIS\n",
       "UNOME                                    \n",
       "MULLER       251  0.0389      RELLUM   DE\n",
       "HOFFMANN      93  0.0144    NNAMFFOH   DE\n",
       "STEIN         61  0.0095       NIETS   DE\n",
       "ZIMMERMANN    55  0.0085  NNAMREMMIZ   DE\n",
       "HARTMANN      55  0.0085    NNAMTRAH   DE\n",
       "MEYER         53  0.0082       REYEM   DE\n",
       "MAYER         50  0.0077       REYAM   DE\n",
       "NEUMANN       39  0.0060     NNAMUEN   DE\n",
       "SCHULTZ       39  0.0060     ZTLUHCS   DE\n",
       "HORN          36  0.0056        NROH   DE"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == ALEMANHA].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "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>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>DUMONT</th>\n",
       "      <td>30</td>\n",
       "      <td>0.0046</td>\n",
       "      <td>TNOMUD</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LAMOUNIER</th>\n",
       "      <td>29</td>\n",
       "      <td>0.0045</td>\n",
       "      <td>REINUOMAL</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BELFORT</th>\n",
       "      <td>24</td>\n",
       "      <td>0.0037</td>\n",
       "      <td>TROFLEB</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BALBINOT</th>\n",
       "      <td>20</td>\n",
       "      <td>0.0031</td>\n",
       "      <td>TONIBLAB</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MAIER</th>\n",
       "      <td>17</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>REIAM</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARNAUD</th>\n",
       "      <td>17</td>\n",
       "      <td>0.0026</td>\n",
       "      <td>DUANRA</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CALVET</th>\n",
       "      <td>16</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>TEVLAC</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FROSSARD</th>\n",
       "      <td>16</td>\n",
       "      <td>0.0025</td>\n",
       "      <td>DRASSORF</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PENAFORT</th>\n",
       "      <td>14</td>\n",
       "      <td>0.0022</td>\n",
       "      <td>TROFANEP</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MEIER</th>\n",
       "      <td>13</td>\n",
       "      <td>0.0020</td>\n",
       "      <td>REIEM</td>\n",
       "      <td>FR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           QTDE    PERC        REV PAIS\n",
       "UNOME                                  \n",
       "DUMONT       30  0.0046     TNOMUD   FR\n",
       "LAMOUNIER    29  0.0045  REINUOMAL   FR\n",
       "BELFORT      24  0.0037    TROFLEB   FR\n",
       "BALBINOT     20  0.0031   TONIBLAB   FR\n",
       "MAIER        17  0.0026      REIAM   FR\n",
       "ARNAUD       17  0.0026     DUANRA   FR\n",
       "CALVET       16  0.0025     TEVLAC   FR\n",
       "FROSSARD     16  0.0025   DRASSORF   FR\n",
       "PENAFORT     14  0.0022   TROFANEP   FR\n",
       "MEIER        13  0.0020      REIEM   FR"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == FRANCA].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>TANAKA</th>\n",
       "      <td>77</td>\n",
       "      <td>0.0119</td>\n",
       "      <td>AKANAT</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NAKAMURA</th>\n",
       "      <td>69</td>\n",
       "      <td>0.0107</td>\n",
       "      <td>ARUMAKAN</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TAKAHASHI</th>\n",
       "      <td>49</td>\n",
       "      <td>0.0076</td>\n",
       "      <td>IHSAHAKAT</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YAMAMOTO</th>\n",
       "      <td>48</td>\n",
       "      <td>0.0074</td>\n",
       "      <td>OTOMAMAY</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>YAMADA</th>\n",
       "      <td>38</td>\n",
       "      <td>0.0059</td>\n",
       "      <td>ADAMAY</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ARAKAKI</th>\n",
       "      <td>36</td>\n",
       "      <td>0.0056</td>\n",
       "      <td>IKAKARA</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MORI</th>\n",
       "      <td>34</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>IROM</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HAYASHI</th>\n",
       "      <td>34</td>\n",
       "      <td>0.0053</td>\n",
       "      <td>IHSAYAH</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KIMURA</th>\n",
       "      <td>32</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>ARUMIK</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SASAKI</th>\n",
       "      <td>32</td>\n",
       "      <td>0.0050</td>\n",
       "      <td>IKASAS</td>\n",
       "      <td>JP</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           QTDE    PERC        REV PAIS\n",
       "UNOME                                  \n",
       "TANAKA       77  0.0119     AKANAT   JP\n",
       "NAKAMURA     69  0.0107   ARUMAKAN   JP\n",
       "TAKAHASHI    49  0.0076  IHSAHAKAT   JP\n",
       "YAMAMOTO     48  0.0074   OTOMAMAY   JP\n",
       "YAMADA       38  0.0059     ADAMAY   JP\n",
       "ARAKAKI      36  0.0056    IKAKARA   JP\n",
       "MORI         34  0.0053       IROM   JP\n",
       "HAYASHI      34  0.0053    IHSAYAH   JP\n",
       "KIMURA       32  0.0050     ARUMIK   JP\n",
       "SASAKI       32  0.0050     IKASAS   JP"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == JAPAO].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>KAMINSKI</th>\n",
       "      <td>23</td>\n",
       "      <td>0.0036</td>\n",
       "      <td>IKSNIMAK</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WISNIEWSKI</th>\n",
       "      <td>8</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>IKSWEINSIW</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEWANDOWSKI</th>\n",
       "      <td>8</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>IKSWODNAWEL</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOZLOWSKI</th>\n",
       "      <td>8</td>\n",
       "      <td>0.0012</td>\n",
       "      <td>IKSWOLZOK</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WASILEWSKI</th>\n",
       "      <td>7</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>IKSWELISAW</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KARPINSKI</th>\n",
       "      <td>7</td>\n",
       "      <td>0.0011</td>\n",
       "      <td>IKSNIPRAK</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LIPINSKI</th>\n",
       "      <td>5</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>IKSNIPIL</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MALINOWSKI</th>\n",
       "      <td>5</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>IKSWONILAM</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BOROWSKI</th>\n",
       "      <td>5</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>IKSWOROB</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OSTROVSKI</th>\n",
       "      <td>5</td>\n",
       "      <td>0.0008</td>\n",
       "      <td>IKSVORTSO</td>\n",
       "      <td>PL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             QTDE    PERC          REV PAIS\n",
       "UNOME                                      \n",
       "KAMINSKI       23  0.0036     IKSNIMAK   PL\n",
       "WISNIEWSKI      8  0.0012   IKSWEINSIW   PL\n",
       "LEWANDOWSKI     8  0.0012  IKSWODNAWEL   PL\n",
       "KOZLOWSKI       8  0.0012    IKSWOLZOK   PL\n",
       "WASILEWSKI      7  0.0011   IKSWELISAW   PL\n",
       "KARPINSKI       7  0.0011    IKSNIPRAK   PL\n",
       "LIPINSKI        5  0.0008     IKSNIPIL   PL\n",
       "MALINOWSKI      5  0.0008   IKSWONILAM   PL\n",
       "BOROWSKI        5  0.0008     IKSWOROB   PL\n",
       "OSTROVSKI       5  0.0008    IKSVORTSO   PL"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == POLONIA].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>IVANOV</th>\n",
       "      <td>4</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>VONAVI</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POLIVANOV</th>\n",
       "      <td>2</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>VONAVILOP</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PACIEVITCH</th>\n",
       "      <td>2</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>HCTIVEICAP</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZUVANOV</th>\n",
       "      <td>2</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>VONAVUZ</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STREJEVITCH</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>HCTIVEJERTS</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>STRAGEVITCH</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>HCTIVEGARTS</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ZAHAIKEVITCH</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>HCTIVEKIAHAZ</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>WOLFOVITCH</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>HCTIVOFLOW</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PROTASIEVITCH</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>HCTIVEISATORP</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PUCHEVITCH</th>\n",
       "      <td>1</td>\n",
       "      <td>0.0002</td>\n",
       "      <td>HCTIVEHCUP</td>\n",
       "      <td>RU</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               QTDE    PERC            REV PAIS\n",
       "UNOME                                          \n",
       "IVANOV            4  0.0006         VONAVI   RU\n",
       "POLIVANOV         2  0.0003      VONAVILOP   RU\n",
       "PACIEVITCH        2  0.0003     HCTIVEICAP   RU\n",
       "ZUVANOV           2  0.0003        VONAVUZ   RU\n",
       "STREJEVITCH       1  0.0002    HCTIVEJERTS   RU\n",
       "STRAGEVITCH       1  0.0002    HCTIVEGARTS   RU\n",
       "ZAHAIKEVITCH      1  0.0002   HCTIVEKIAHAZ   RU\n",
       "WOLFOVITCH        1  0.0002     HCTIVOFLOW   RU\n",
       "PROTASIEVITCH     1  0.0002  HCTIVEISATORP   RU\n",
       "PUCHEVITCH        1  0.0002     HCTIVEHCUP   RU"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == RUSSIA].head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>QTDE</th>\n",
       "      <th>PERC</th>\n",
       "      <th>REV</th>\n",
       "      <th>PAIS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UNOME</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>BONDARCZUK</th>\n",
       "      <td>6</td>\n",
       "      <td>0.0009</td>\n",
       "      <td>KUZCRADNOB</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RUSZCZYK</th>\n",
       "      <td>4</td>\n",
       "      <td>0.0006</td>\n",
       "      <td>KYZCZSUR</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MICHALCZUK</th>\n",
       "      <td>3</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>KUZCLAHCIM</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LUKASZCZYK</th>\n",
       "      <td>3</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>KYZCZSAKUL</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LINCZUK</th>\n",
       "      <td>3</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>KUZCNIL</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADAMCZUK</th>\n",
       "      <td>3</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>KUZCMADA</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POLANCZYK</th>\n",
       "      <td>3</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>KYZCNALOP</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TOMCZYK</th>\n",
       "      <td>3</td>\n",
       "      <td>0.0005</td>\n",
       "      <td>KYZCMOT</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>GRACZYK</th>\n",
       "      <td>2</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>KYZCARG</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>KOWALCZUK</th>\n",
       "      <td>2</td>\n",
       "      <td>0.0003</td>\n",
       "      <td>KUZCLAWOK</td>\n",
       "      <td>UA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            QTDE    PERC         REV PAIS\n",
       "UNOME                                    \n",
       "BONDARCZUK     6  0.0009  KUZCRADNOB   UA\n",
       "RUSZCZYK       4  0.0006    KYZCZSUR   UA\n",
       "MICHALCZUK     3  0.0005  KUZCLAHCIM   UA\n",
       "LUKASZCZYK     3  0.0005  KYZCZSAKUL   UA\n",
       "LINCZUK        3  0.0005     KUZCNIL   UA\n",
       "ADAMCZUK       3  0.0005    KUZCMADA   UA\n",
       "POLANCZYK      3  0.0005   KYZCNALOP   UA\n",
       "TOMCZYK        3  0.0005     KYZCMOT   UA\n",
       "GRACZYK        2  0.0003     KYZCARG   UA\n",
       "KOWALCZUK      2  0.0003   KUZCLAWOK   UA"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['PAIS'] == UCRANIA].head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Geração do arquivo de depuração (não identificados)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df2 = (df[df['PAIS'] == 'XX'])[['QTDE', 'REV']].sort_values(['REV', 'QTDE'])[['QTDE']]\n",
    "#df2.head(30)\n",
    "df2.to_csv(BASE + '-sobrenomes-pais-XX.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Geração do arquivo final"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df['PAIS'].isnull(), 'PAIS'] = 'XX'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "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>QTDE</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PAIS</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>XX</th>\n",
       "      <td>41381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT</th>\n",
       "      <td>4490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>JP</th>\n",
       "      <td>1324</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DE</th>\n",
       "      <td>1295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FR</th>\n",
       "      <td>817</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PL</th>\n",
       "      <td>556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ES</th>\n",
       "      <td>371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PT</th>\n",
       "      <td>104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>UA</th>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RU</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       QTDE\n",
       "PAIS       \n",
       "XX    41381\n",
       "IT     4490\n",
       "JP     1324\n",
       "DE     1295\n",
       "FR      817\n",
       "PL      556\n",
       "ES      371\n",
       "PT      104\n",
       "UA       47\n",
       "RU       18"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['QTDE', 'PAIS']].groupby(['PAIS']).count().sort_values(['QTDE'], ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "df['PAIS'].to_csv(BASE + '-sobrenomes-pais.csv', float_format='%.4f')"
   ]
  }
 ],
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