{
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  {
   "cell_type": "markdown",
   "id": "ce23b3df",
   "metadata": {},
   "source": [
    "# Excel\n",
    "\n",
    "pandas unterstützt auch das Lesen von Tabellendaten, die in Dateien von Excel 2003 (und höher) gespeichert sind, entweder mit der Klasse `ExcelFile` oder der Funktion `pandas.read_excel`. Intern verwenden diese Werkzeuge die Zusatzpakete [xlrd](https://xlrd.readthedocs.io/en/latest/) und [openpyxl](https://openpyxl.readthedocs.io/en/stable/), um XLS- bzw. XLSX-Dateien zu lesen. Diese müssen separat von pandas mit uv installiert werden.\n",
    "\n",
    "Um `ExcelFile` zu verwenden, erstellt eine Instanz, indem ihr einen Pfad zu einer xls- oder xlsx-Datei übergebt:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "3c32b5bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "26a00ac1",
   "metadata": {},
   "outputs": [],
   "source": [
    "xlsx = pd.ExcelFile(\"library.xlsx\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d1efbe82",
   "metadata": {},
   "source": [
    "Ihr könnt dann die Sheets der Datei anzeigen mit:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8d4d6a79",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['books']"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xlsx.sheet_names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e3c46b3a",
   "metadata": {},
   "outputs": [
    {
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       "      <th>Titel</th>\n",
       "      <th>Sprache</th>\n",
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       "      <th>Lizenz</th>\n",
       "      <th>Veröffentlichungsdatum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
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       "      <th>0</th>\n",
       "      <td>Python basics</td>\n",
       "      <td>en</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2021-10-28</td>\n",
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       "      <td>BSD-3-Clause</td>\n",
       "      <td>2019-06-27</td>\n",
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       "      <td>2020-10-26</td>\n",
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       "      <th>3</th>\n",
       "      <td>PyViz Tutorial</td>\n",
       "      <td>en</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2020-04-13</td>\n",
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       "              Titel Sprache   Autor*innen        Lizenz Veröffentlichungsdatum\n",
       "0     Python basics      en  Veit Schiele  BSD-3-Clause             2021-10-28\n",
       "1  Jupyter Tutorial      en  Veit Schiele  BSD-3-Clause             2019-06-27\n",
       "2  Jupyter Tutorial      de  Veit Schiele  BSD-3-Clause             2020-10-26\n",
       "3    PyViz Tutorial      en  Veit Schiele  BSD-3-Clause             2020-04-13"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books = pd.read_excel(xlsx, \"books\")\n",
    "\n",
    "books"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "385c4a7c",
   "metadata": {},
   "source": [
    "Wenn ihr mehrere Sheets einer Datei einlest, ist es schneller, die Excel-Datei zu erstellen, aber ihr könnt auch einfach den Dateinamen an `pandas.read_excel` übergeben:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f726919f",
   "metadata": {},
   "outputs": [
    {
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       "    .dataframe thead th {\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Titel</th>\n",
       "      <th>Sprache</th>\n",
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       "      <th>Lizenz</th>\n",
       "      <th>Veröffentlichungsdatum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Python basics</td>\n",
       "      <td>en</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2021-10-28</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Jupyter Tutorial</td>\n",
       "      <td>en</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2019-06-27</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Jupyter Tutorial</td>\n",
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       "      <td>PyViz Tutorial</td>\n",
       "      <td>en</td>\n",
       "      <td>Veit Schiele</td>\n",
       "      <td>BSD-3-Clause</td>\n",
       "      <td>2020-04-13</td>\n",
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      "text/plain": [
       "              Titel Sprache   Autor*innen        Lizenz Veröffentlichungsdatum\n",
       "0     Python basics      en  Veit Schiele  BSD-3-Clause             2021-10-28\n",
       "1  Jupyter Tutorial      en  Veit Schiele  BSD-3-Clause             2019-06-27\n",
       "2  Jupyter Tutorial      de  Veit Schiele  BSD-3-Clause             2020-10-26\n",
       "3    PyViz Tutorial      en  Veit Schiele  BSD-3-Clause             2020-04-13"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "books = pd.read_excel(\"library.xlsx\", \"books\")\n",
    "\n",
    "books"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a04fd24e",
   "metadata": {},
   "source": [
    "Um pandas-Daten im Excel-Format zu schreiben, müsst ihr zunächst einen `ExcelWriter` erstellen und dann mit [pandas.DataFrame.to_excel](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.to_excel.html) Daten in diesen schreiben:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "4f85f0cd",
   "metadata": {},
   "outputs": [],
   "source": [
    "writer = pd.ExcelWriter(\"library.xlsx\")\n",
    "\n",
    "books.to_excel(writer, \"books\")\n",
    "writer.close()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5ebdf730",
   "metadata": {},
   "source": [
    "Ihr könnt auch einen Dateipfad an `to_excel` übergeben und so den `ExcelWriter` umgehen:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2dc2a960",
   "metadata": {},
   "outputs": [],
   "source": [
    "books.to_excel(\"library.xlsx\")"
   ]
  }
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