Annotations of Pandas DataFrame

escola.xlsx

gen_names_xlsx.ipynb

gen_random_values.ipynb

import_xlsx_to_django_database.ipynb

import_xlsx_to_django_database2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import timeit\n",
    "from django.contrib.auth.models import User"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "max_value = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "tic = timeit.default_timer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "filename = '/tmp/example.xlsx'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NOME</th>\n",
       "      <th>EMAIL</th>\n",
       "      <th>CPF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alex Swartz Wertz</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Valerie Berry Mattlin</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Brooke Coley Roy</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Joe Levin Collins</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Lynn Alford Timmons</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                    NOME                            EMAIL             CPF\n",
       "0      Alex Swartz Wertz      [email protected]  00000000000000\n",
       "1  Valerie Berry Mattlin  [email protected]  00000000000000\n",
       "2       Brooke Coley Roy       [email protected]  00000000000000\n",
       "3      Joe Levin Collins      [email protected]  00000000000000\n",
       "4    Lynn Alford Timmons    [email protected]  00000000000000"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "email = df['EMAIL']\n",
    "# Retornando os itens duplicados\n",
    "# df[email.isin(email[email.duplicated()])]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style>\n",
       "    .dataframe thead tr:only-child th {\n",
       "        text-align: right;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: left;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>NOME</th>\n",
       "      <th>EMAIL</th>\n",
       "      <th>CPF</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>49991</th>\n",
       "      <td>49995</td>\n",
       "      <td>Warren Stowell Young</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49992</th>\n",
       "      <td>49996</td>\n",
       "      <td>Patricia Cheek Mitchell</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49993</th>\n",
       "      <td>49997</td>\n",
       "      <td>Linda Denton Breton</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49994</th>\n",
       "      <td>49998</td>\n",
       "      <td>Clyde Lopes Leonard</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49995</th>\n",
       "      <td>49999</td>\n",
       "      <td>Josefina Wilkinson Graves</td>\n",
       "      <td>[email protected]</td>\n",
       "      <td>00000000000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       index                       NOME                                EMAIL  \\\n",
       "49991  49995       Warren Stowell Young       [email protected]   \n",
       "49992  49996    Patricia Cheek Mitchell    [email protected]   \n",
       "49993  49997        Linda Denton Breton        [email protected]   \n",
       "49994  49998        Clyde Lopes Leonard        [email protected]   \n",
       "49995  49999  Josefina Wilkinson Graves  [email protected]   \n",
       "\n",
       "                  CPF  \n",
       "49991  00000000000000  \n",
       "49992  00000000000000  \n",
       "49993  00000000000000  \n",
       "49994  00000000000000  \n",
       "49995  00000000000000  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Removendo os itens duplicados\n",
    "dffinal = df.drop_duplicates('EMAIL').reset_index()\n",
    "dffinal.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "49996"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dffinal)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_user2(new_users):\n",
    "    # Separa full_name em first_name e last_name\n",
    "    users = []\n",
    "    for new_user in new_users:\n",
    "        full_name = new_user['full_name']\n",
    "        email = new_user['email']\n",
    "        first_name = full_name.split()[0]\n",
    "        last_name = full_name.split()[1:]\n",
    "        last_name = ' '.join(last_name)\n",
    "        username = email\n",
    "        sha_password = 'kkkkkkkkkkkkkkkkkkkk'\n",
    "        user = User(\n",
    "            first_name=first_name,\n",
    "            last_name=last_name,\n",
    "            email=email,\n",
    "            username=username,\n",
    "            password=sha_password\n",
    "        )\n",
    "        users.append(user)\n",
    "    return users"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def import_users2(new_users):\n",
    "    User.objects.bulk_create(new_users)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_users = []\n",
    "emails = []\n",
    "emails = dffinal['EMAIL'].values.tolist()\n",
    "exist_users = User.objects.filter(email__in=emails).values_list('email', flat=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# for row in dffinal.head().itertuples():\n",
    "#     print(row.NOME, row.EMAIL, row.CPF)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "for row in dffinal.head(max_value).itertuples():\n",
    "    full_name = row.NOME\n",
    "    email = row.EMAIL\n",
    "    cpf = row.CPF\n",
    "    if email not in exist_users:\n",
    "        data = dict(full_name=full_name, email=email, cpf=cpf)\n",
    "        new_users.append(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_users_ = create_user2(new_users)\n",
    "import_users2(new_users_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0, 'existentes')\n",
      "(5, 'novos')\n"
     ]
    }
   ],
   "source": [
    "print(len(exist_users), 'existentes')\n",
    "print(len(new_users), 'novos')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "toc = timeit.default_timer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.6345059871673584"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toc - tic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "users_query_list = User.objects.filter(email__in=new_users_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# users_query_list[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simpleuser = Group.objects.get(name='simpleuser')\n",
    "simpleuser.id"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_groups_list = []\n",
    "# https://stackoverflow.com/a/34093544\n",
    "for user in users_query_list:\n",
    "    user_groups = User.groups.through(user_id=user.pk, group_id=simpleuser.pk)\n",
    "    user_groups_list.append(user_groups)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<User_groups: User_groups object>,\n",
       " <User_groups: User_groups object>,\n",
       " <User_groups: User_groups object>,\n",
       " <User_groups: User_groups object>,\n",
       " <User_groups: User_groups object>]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "User.groups.through.objects.bulk_create(user_groups_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "toc = timeit.default_timer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3.3119399547576904"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toc - tic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# UserCPF\n",
    "exist_usercpfs = UserCPF.objects.filter(user__email__in=emails).values_list('user__email', flat=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[email protected]\n",
      "[email protected]\n",
      "[email protected]\n",
      "[email protected]\n",
      "[email protected]\n"
     ]
    }
   ],
   "source": [
    "new_usercpfs = []\n",
    "for row in dffinal.head(max_value).itertuples():\n",
    "    email = row.EMAIL\n",
    "    cpf = row.CPF\n",
    "    # Verifica se UserCPF ja existe\n",
    "    if email not in exist_usercpfs:\n",
    "        print(email)\n",
    "        user = User.objects.get(email=email)\n",
    "        data = dict(user=user, cpf=cpf)\n",
    "        new_usercpfs.append(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# função create_usercpf(new_usercpfs)\n",
    "new_usercpfs2 = []\n",
    "for user in new_usercpfs:\n",
    "    new_usercpfs2.append(UserCPF(user=user['user'], cpf=user['cpf']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<UserCPF: Alex Swartz Wertz>,\n",
       " <UserCPF: Valerie Berry Mattlin>,\n",
       " <UserCPF: Brooke Coley Roy>,\n",
       " <UserCPF: Joe Levin Collins>,\n",
       " <UserCPF: Lynn Alford Timmons>]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "UserCPF.objects.bulk_create(new_usercpfs2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "toc = timeit.default_timer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4.112852096557617"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toc - tic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Employee\n",
    "firm = Company.objects.get(name='Empresa')\n",
    "exist_employees = Employee.objects.filter(user__email__in=emails).values_list('user__email', flat=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Company: Empresa>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "firm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_employees = []\n",
    "for row in dffinal.head(max_value).itertuples():\n",
    "    email = row.EMAIL\n",
    "    if email not in exist_employees:\n",
    "        user = User.objects.get(email=email)\n",
    "        data = dict(user=user, firm=firm, department='14')\n",
    "        new_employees.append(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'department': '14', 'firm': <Company: Empresa>, 'user': <User: [email protected]>}\n",
      "{'department': '14', 'firm': <Company: Empresa>, 'user': <User: [email protected]>}\n",
      "{'department': '14', 'firm': <Company: Empresa>, 'user': <User: [email protected]>}\n",
      "{'department': '14', 'firm': <Company: Empresa>, 'user': <User: [email protected]>}\n",
      "{'department': '14', 'firm': <Company: Empresa>, 'user': <User: [email protected]>}\n"
     ]
    }
   ],
   "source": [
    "# função create_employee(new_employees)\n",
    "new_employees2 = []\n",
    "for user in new_employees:\n",
    "    print(user)\n",
    "    new_employees2.append(Employee(user=user['user'], firm=user['firm'], department=user['department']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<Employee: Alex Swartz Wertz>,\n",
       " <Employee: Valerie Berry Mattlin>,\n",
       " <Employee: Brooke Coley Roy>,\n",
       " <Employee: Joe Levin Collins>,\n",
       " <Employee: Lynn Alford Timmons>]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Employee.objects.bulk_create(new_employees2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Permissões\n",
    "def create_permissions():\n",
    "    # Criando permissão view_manage_career_pages\n",
    "    content_type = ContentType.objects.get_for_model(Company)\n",
    "    permission = Permission.objects.get(\n",
    "        content_type=content_type,\n",
    "        codename='view_manage_career_pages'\n",
    "    )\n",
    "    # Habilitando permissão para simpleuser\n",
    "    g = Group.objects.get(name='simpleuser')\n",
    "    g.permissions.add(permission)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_permissions_quiz():\n",
    "    # Criando permissão add_quiz\n",
    "    content_type = ContentType.objects.get_for_model(Quiz)\n",
    "    permission = Permission.objects.get(\n",
    "        content_type=content_type,\n",
    "        codename='add_quiz'\n",
    "    )\n",
    "    # Habilitando permissão para simpleuser\n",
    "    g = Group.objects.get(name='simpleuser')\n",
    "    g.permissions.add(permission)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "create_permissions()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "create_permissions_quiz()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "toc = timeit.default_timer()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.437417984008789"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "toc - tic"
   ]
  }
 ],
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pandas.ipynb

remove_duplicated.ipynb

separe_email.ipynb