webscraping_ht0_5_today.ipynb

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        {
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          "data": {
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [Matches, Over HT 1.5 local, Over HT 1.5 visitante, Over HT 1.5 total]\n",
              "Index: []"
            ],
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              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Matches</th>\n",
              "      <th>Over HT 1.5 local</th>\n",
              "      <th>Over HT 1.5 visitante</th>\n",
              "      <th>Over HT 1.5 total</th>\n",
              "    </tr>\n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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      "source": [
        "# Importar las librerías necesarias\n",
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "import datetime as dt\n",
        "from datetime import timedelta\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "# Definir la URL de la página web a scrapear\n",
        "url = \"https://www.fctables.com/todays-match-predictions/\"\n",
        "\n",
        "# Obtener el contenido de la página web\n",
        "response = requests.get(url)\n",
        "\n",
        "# Crear un objeto BeautifulSoup\n",
        "soup = BeautifulSoup(response.content, \"html.parser\")\n",
        "\n",
        "# Buscar los elementos de la página web que queremos extraer\n",
        "elementos = soup.find_all(class_=\"table table-striped table-bordered stage-table table-condensed\")\n",
        "\n",
        "df = pd.DataFrame({\"Matches\":[],\n",
        "                    \"Over HT 1.5 local\":[],\n",
        "                    \"Over HT 1.5 visitante\":[],\n",
        "                    \"Over HT 1.5 total\":[]})\n",
        "\n",
        "if elementos[0]:\n",
        "  tbody = elementos[0].find(\"tbody\")\n",
        "  trs =tbody.find_all(\"tr\")\n",
        "  for tr in trs:\n",
        "    url_match = tr.find_all(\"td\")[2].find(\"a\")[\"href\"]\n",
        "    matchh = tr.find_all(\"td\")[2].find(\"a\").text\n",
        "    #print(url_match)\n",
        "    response = requests.get(\"https://www.fctables.com\"+url_match)\n",
        "    soup = BeautifulSoup(response.content, \"html.parser\")\n",
        "    tablas = soup.find_all(id=\"team_stats_vs\")\n",
        "\n",
        "    for tabla in tablas:\n",
        "      tbody = tabla.find(\"tbody\")\n",
        "      trs =tbody.find_all(\"tr\")\n",
        "      for tr in trs:\n",
        "        #print(tr)\n",
        "        if \"Over HT 1.5\" in tr.text:\n",
        "          tds = tr.find_all(\"td\")\n",
        "          if tds[0].text:\n",
        "            local = tds[0].text\n",
        "            valor = local[local.find(\"(\") + 1:local.find(\")\")]\n",
        "            valor = valor.replace(\"%\",\"\")\n",
        "            local = int(valor)\n",
        "          else:\n",
        "            local = 0\n",
        "          if tds[2].text:\n",
        "            visitante = tds[2].text\n",
        "            valor = visitante[visitante.find(\"(\") + 1:visitante.find(\")\")]\n",
        "            valor = valor.replace(\"%\",\"\")\n",
        "            visitante = int(valor)\n",
        "          else:\n",
        "            visitante = 0\n",
        "          if local > 50 and visitante > 50 :\n",
        "            df = df.append( pd.DataFrame({\"Matches\":[matchh],\n",
        "                    \"Over HT 1.5 local\":[local],\n",
        "                    \"Over HT 1.5 visitante\":[visitante],\n",
        "                    \"Over HT 1.5 total\":[ (local*visitante) / 2]}) )\n",
        "            dic = {'encuentro':matchh,'local':local,'visitante':visitante , 'total': local+visitante }\n",
        "\n",
        "display(df)\n",
        "current_date = dt.date.today()\n",
        "today = current_date.strftime(\"%w_%B_%Y\")\n",
        "df.to_excel(\"over15_\"+today+\".xlsx\")\n"
      ]
    }
  ]
}