pandas - Reading Excel files.ipynb

{
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  {
   "cell_type": "markdown",
   "id": "c2338c0d-a206-4c20-b63e-fe953627558f",
   "metadata": {},
   "source": [
    "****Reading Excel files****"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "06837c50-5eca-457b-9e7b-17206e64c99d",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fab5d94-842b-4844-8090-a43199e62a23",
   "metadata": {},
   "source": [
    "***The read_excel method***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f5c4efe1-2f51-4551-bd4c-85a943918307",
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       "\u001b[1;31mDocstring:\u001b[0m\n",
       "Read an Excel file into a pandas DataFrame.\n",
       "\n",
       "Supports `xls`, `xlsx`, `xlsm`, `xlsb`, `odf`, `ods` and `odt` file extensions\n",
       "read from a local filesystem or URL. Supports an option to read\n",
       "a single sheet or a list of sheets.\n",
       "\n",
       "Parameters\n",
       "----------\n",
       "io : str, bytes, ExcelFile, xlrd.Book, path object, or file-like object\n",
       "    Any valid string path is acceptable. The string could be a URL. Valid\n",
       "    URL schemes include http, ftp, s3, and file. For file URLs, a host is\n",
       "    expected. A local file could be: ``file://localhost/path/to/table.xlsx``.\n",
       "\n",
       "    If you want to pass in a path object, pandas accepts any ``os.PathLike``.\n",
       "\n",
       "    By file-like object, we refer to objects with a ``read()`` method,\n",
       "    such as a file handle (e.g. via builtin ``open`` function)\n",
       "    or ``StringIO``.\n",
       "sheet_name : str, int, list, or None, default 0\n",
       "    Strings are used for sheet names. Integers are used in zero-indexed\n",
       "    sheet positions. Lists of strings/integers are used to request\n",
       "    multiple sheets. Specify None to get all sheets.\n",
       "\n",
       "    Available cases:\n",
       "\n",
       "    * Defaults to ``0``: 1st sheet as a `DataFrame`\n",
       "    * ``1``: 2nd sheet as a `DataFrame`\n",
       "    * ``\"Sheet1\"``: Load sheet with name \"Sheet1\"\n",
       "    * ``[0, 1, \"Sheet5\"]``: Load first, second and sheet named \"Sheet5\"\n",
       "      as a dict of `DataFrame`\n",
       "    * None: All sheets.\n",
       "\n",
       "header : int, list of int, default 0\n",
       "    Row (0-indexed) to use for the column labels of the parsed\n",
       "    DataFrame. If a list of integers is passed those row positions will\n",
       "    be combined into a ``MultiIndex``. Use None if there is no header.\n",
       "names : array-like, default None\n",
       "    List of column names to use. If file contains no header row,\n",
       "    then you should explicitly pass header=None.\n",
       "index_col : int, list of int, default None\n",
       "    Column (0-indexed) to use as the row labels of the DataFrame.\n",
       "    Pass None if there is no such column.  If a list is passed,\n",
       "    those columns will be combined into a ``MultiIndex``.  If a\n",
       "    subset of data is selected with ``usecols``, index_col\n",
       "    is based on the subset.\n",
       "usecols : int, str, list-like, or callable default None\n",
       "    * If None, then parse all columns.\n",
       "    * If str, then indicates comma separated list of Excel column letters\n",
       "      and column ranges (e.g. \"A:E\" or \"A,C,E:F\"). Ranges are inclusive of\n",
       "      both sides.\n",
       "    * If list of int, then indicates list of column numbers to be parsed.\n",
       "    * If list of string, then indicates list of column names to be parsed.\n",
       "    * If callable, then evaluate each column name against it and parse the\n",
       "      column if the callable returns ``True``.\n",
       "\n",
       "    Returns a subset of the columns according to behavior above.\n",
       "squeeze : bool, default False\n",
       "    If the parsed data only contains one column then return a Series.\n",
       "dtype : Type name or dict of column -> type, default None\n",
       "    Data type for data or columns. E.g. {'a': np.float64, 'b': np.int32}\n",
       "    Use `object` to preserve data as stored in Excel and not interpret dtype.\n",
       "    If converters are specified, they will be applied INSTEAD\n",
       "    of dtype conversion.\n",
       "engine : str, default None\n",
       "    If io is not a buffer or path, this must be set to identify io.\n",
       "    Supported engines: \"xlrd\", \"openpyxl\", \"odf\", \"pyxlsb\".\n",
       "    Engine compatibility :\n",
       "\n",
       "    - \"xlrd\" supports old-style Excel files (.xls).\n",
       "    - \"openpyxl\" supports newer Excel file formats.\n",
       "    - \"odf\" supports OpenDocument file formats (.odf, .ods, .odt).\n",
       "    - \"pyxlsb\" supports Binary Excel files.\n",
       "\n",
       "    .. versionchanged:: 1.2.0\n",
       "        The engine `xlrd <https://xlrd.readthedocs.io/en/latest/>`_\n",
       "        now only supports old-style ``.xls`` files.\n",
       "        When ``engine=None``, the following logic will be\n",
       "        used to determine the engine:\n",
       "\n",
       "       - If ``path_or_buffer`` is an OpenDocument format (.odf, .ods, .odt),\n",
       "         then `odf <https://pypi.org/project/odfpy/>`_ will be used.\n",
       "       - Otherwise if ``path_or_buffer`` is an xls format,\n",
       "         ``xlrd`` will be used.\n",
       "       - Otherwise if ``path_or_buffer`` is in xlsb format,\n",
       "         ``pyxlsb`` will be used.\n",
       "\n",
       "         .. versionadded:: 1.3.0\n",
       "       - Otherwise ``openpyxl`` will be used.\n",
       "\n",
       "         .. versionchanged:: 1.3.0\n",
       "\n",
       "converters : dict, default None\n",
       "    Dict of functions for converting values in certain columns. Keys can\n",
       "    either be integers or column labels, values are functions that take one\n",
       "    input argument, the Excel cell content, and return the transformed\n",
       "    content.\n",
       "true_values : list, default None\n",
       "    Values to consider as True.\n",
       "false_values : list, default None\n",
       "    Values to consider as False.\n",
       "skiprows : list-like, int, or callable, optional\n",
       "    Line numbers to skip (0-indexed) or number of lines to skip (int) at the\n",
       "    start of the file. If callable, the callable function will be evaluated\n",
       "    against the row indices, returning True if the row should be skipped and\n",
       "    False otherwise. An example of a valid callable argument would be ``lambda\n",
       "    x: x in [0, 2]``.\n",
       "nrows : int, default None\n",
       "    Number of rows to parse.\n",
       "na_values : scalar, str, list-like, or dict, default None\n",
       "    Additional strings to recognize as NA/NaN. If dict passed, specific\n",
       "    per-column NA values. By default the following values are interpreted\n",
       "    as NaN: '', '#N/A', '#N/A N/A', '#NA', '-1.#IND', '-1.#QNAN', '-NaN', '-nan',\n",
       "    '1.#IND', '1.#QNAN', '<NA>', 'N/A', 'NA', 'NULL', 'NaN', 'n/a',\n",
       "    'nan', 'null'.\n",
       "keep_default_na : bool, default True\n",
       "    Whether or not to include the default NaN values when parsing the data.\n",
       "    Depending on whether `na_values` is passed in, the behavior is as follows:\n",
       "\n",
       "    * If `keep_default_na` is True, and `na_values` are specified, `na_values`\n",
       "      is appended to the default NaN values used for parsing.\n",
       "    * If `keep_default_na` is True, and `na_values` are not specified, only\n",
       "      the default NaN values are used for parsing.\n",
       "    * If `keep_default_na` is False, and `na_values` are specified, only\n",
       "      the NaN values specified `na_values` are used for parsing.\n",
       "    * If `keep_default_na` is False, and `na_values` are not specified, no\n",
       "      strings will be parsed as NaN.\n",
       "\n",
       "    Note that if `na_filter` is passed in as False, the `keep_default_na` and\n",
       "    `na_values` parameters will be ignored.\n",
       "na_filter : bool, default True\n",
       "    Detect missing value markers (empty strings and the value of na_values). In\n",
       "    data without any NAs, passing na_filter=False can improve the performance\n",
       "    of reading a large file.\n",
       "verbose : bool, default False\n",
       "    Indicate number of NA values placed in non-numeric columns.\n",
       "parse_dates : bool, list-like, or dict, default False\n",
       "    The behavior is as follows:\n",
       "\n",
       "    * bool. If True -> try parsing the index.\n",
       "    * list of int or names. e.g. If [1, 2, 3] -> try parsing columns 1, 2, 3\n",
       "      each as a separate date column.\n",
       "    * list of lists. e.g.  If [[1, 3]] -> combine columns 1 and 3 and parse as\n",
       "      a single date column.\n",
       "    * dict, e.g. {'foo' : [1, 3]} -> parse columns 1, 3 as date and call\n",
       "      result 'foo'\n",
       "\n",
       "    If a column or index contains an unparsable date, the entire column or\n",
       "    index will be returned unaltered as an object data type. If you don`t want to\n",
       "    parse some cells as date just change their type in Excel to \"Text\".\n",
       "    For non-standard datetime parsing, use ``pd.to_datetime`` after ``pd.read_excel``.\n",
       "\n",
       "    Note: A fast-path exists for iso8601-formatted dates.\n",
       "date_parser : function, optional\n",
       "    Function to use for converting a sequence of string columns to an array of\n",
       "    datetime instances. The default uses ``dateutil.parser.parser`` to do the\n",
       "    conversion. Pandas will try to call `date_parser` in three different ways,\n",
       "    advancing to the next if an exception occurs: 1) Pass one or more arrays\n",
       "    (as defined by `parse_dates`) as arguments; 2) concatenate (row-wise) the\n",
       "    string values from the columns defined by `parse_dates` into a single array\n",
       "    and pass that; and 3) call `date_parser` once for each row using one or\n",
       "    more strings (corresponding to the columns defined by `parse_dates`) as\n",
       "    arguments.\n",
       "thousands : str, default None\n",
       "    Thousands separator for parsing string columns to numeric.  Note that\n",
       "    this parameter is only necessary for columns stored as TEXT in Excel,\n",
       "    any numeric columns will automatically be parsed, regardless of display\n",
       "    format.\n",
       "comment : str, default None\n",
       "    Comments out remainder of line. Pass a character or characters to this\n",
       "    argument to indicate comments in the input file. Any data between the\n",
       "    comment string and the end of the current line is ignored.\n",
       "skipfooter : int, default 0\n",
       "    Rows at the end to skip (0-indexed).\n",
       "convert_float : bool, default True\n",
       "    Convert integral floats to int (i.e., 1.0 --> 1). If False, all numeric\n",
       "    data will be read in as floats: Excel stores all numbers as floats\n",
       "    internally.\n",
       "\n",
       "    .. deprecated:: 1.3.0\n",
       "        convert_float will be removed in a future version\n",
       "\n",
       "mangle_dupe_cols : bool, default True\n",
       "    Duplicate columns will be specified as 'X', 'X.1', ...'X.N', rather than\n",
       "    'X'...'X'. Passing in False will cause data to be overwritten if there\n",
       "    are duplicate names in the columns.\n",
       "storage_options : dict, optional\n",
       "    Extra options that make sense for a particular storage connection, e.g.\n",
       "    host, port, username, password, etc., if using a URL that will\n",
       "    be parsed by ``fsspec``, e.g., starting \"s3://\", \"gcs://\". An error\n",
       "    will be raised if providing this argument with a local path or\n",
       "    a file-like buffer. See the fsspec and backend storage implementation\n",
       "    docs for the set of allowed keys and values.\n",
       "\n",
       "    .. versionadded:: 1.2.0\n",
       "\n",
       "Returns\n",
       "-------\n",
       "DataFrame or dict of DataFrames\n",
       "    DataFrame from the passed in Excel file. See notes in sheet_name\n",
       "    argument for more information on when a dict of DataFrames is returned.\n",
       "\n",
       "See Also\n",
       "--------\n",
       "DataFrame.to_excel : Write DataFrame to an Excel file.\n",
       "DataFrame.to_csv : Write DataFrame to a comma-separated values (csv) file.\n",
       "read_csv : Read a comma-separated values (csv) file into DataFrame.\n",
       "read_fwf : Read a table of fixed-width formatted lines into DataFrame.\n",
       "\n",
       "Examples\n",
       "--------\n",
       "The file can be read using the file name as string or an open file object:\n",
       "\n",
       ">>> pd.read_excel('tmp.xlsx', index_col=0)  # doctest: +SKIP\n",
       "       Name  Value\n",
       "0   string1      1\n",
       "1   string2      2\n",
       "2  #Comment      3\n",
       "\n",
       ">>> pd.read_excel(open('tmp.xlsx', 'rb'),\n",
       "...               sheet_name='Sheet3')  # doctest: +SKIP\n",
       "   Unnamed: 0      Name  Value\n",
       "0           0   string1      1\n",
       "1           1   string2      2\n",
       "2           2  #Comment      3\n",
       "\n",
       "Index and header can be specified via the `index_col` and `header` arguments\n",
       "\n",
       ">>> pd.read_excel('tmp.xlsx', index_col=None, header=None)  # doctest: +SKIP\n",
       "     0         1      2\n",
       "0  NaN      Name  Value\n",
       "1  0.0   string1      1\n",
       "2  1.0   string2      2\n",
       "3  2.0  #Comment      3\n",
       "\n",
       "Column types are inferred but can be explicitly specified\n",
       "\n",
       ">>> pd.read_excel('tmp.xlsx', index_col=0,\n",
       "...               dtype={'Name': str, 'Value': float})  # doctest: +SKIP\n",
       "       Name  Value\n",
       "0   string1    1.0\n",
       "1   string2    2.0\n",
       "2  #Comment    3.0\n",
       "\n",
       "True, False, and NA values, and thousands separators have defaults,\n",
       "but can be explicitly specified, too. Supply the values you would like\n",
       "as strings or lists of strings!\n",
       "\n",
       ">>> pd.read_excel('tmp.xlsx', index_col=0,\n",
       "...               na_values=['string1', 'string2'])  # doctest: +SKIP\n",
       "       Name  Value\n",
       "0       NaN      1\n",
       "1       NaN      2\n",
       "2  #Comment      3\n",
       "\n",
       "Comment lines in the excel input file can be skipped using the `comment` kwarg\n",
       "\n",
       ">>> pd.read_excel('tmp.xlsx', index_col=0, comment='#')  # doctest: +SKIP\n",
       "      Name  Value\n",
       "0  string1    1.0\n",
       "1  string2    2.0\n",
       "2     None    NaN\n",
       "\u001b[1;31mFile:\u001b[0m      c:\\users\\lenovo\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\pandas\\io\\excel\\_base.py\n",
       "\u001b[1;31mType:\u001b[0m      function\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "pd.read_excel?"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6e2ffb4-016a-4fc2-973c-ef989064265d",
   "metadata": {},
   "source": [
    "***Reading our first Excel file***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3acdaa5f-17d7-4c4e-be5f-1c218e592308",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('data/products.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "65922ffc-9e41-488f-af01-330a2735f507",
   "metadata": {},
   "outputs": [
    {
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       "        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>product_id</th>\n",
       "      <th>price</th>\n",
       "      <th>merchant_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AVphzgbJLJeJML43fA0o</td>\n",
       "      <td>104.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>Sanus</td>\n",
       "      <td>Sanus VLF410B1 10-Inch Super Slim Full-Motion ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AVpgMuGwLJeJML43KY_c</td>\n",
       "      <td>69.00</td>\n",
       "      <td>1002</td>\n",
       "      <td>Boytone</td>\n",
       "      <td>Boytone - 2500W 2.1-Ch. Home Theater System - ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AVpe9FXeLJeJML43zHrq</td>\n",
       "      <td>23.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DENAQ</td>\n",
       "      <td>DENAQ - AC Adapter for TOSHIBA SATELLITE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AVpfVJXu1cnluZ0-iwTT</td>\n",
       "      <td>290.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DreamWave</td>\n",
       "      <td>DreamWave - Tremor Portable Bluetooth Speaker ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AVphUeKeilAPnD_x3-Be</td>\n",
       "      <td>244.01</td>\n",
       "      <td>1004</td>\n",
       "      <td>Yamaha</td>\n",
       "      <td>NS-SP1800BL 5.1-Channel Home Theater System (B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
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       "             product_id   price  merchant_id      brand  \\\n",
       "0  AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "1  AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "2  AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "3  AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "4  AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                name  \n",
       "0  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "1  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "2           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "3  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "4  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "df.head()"
   ]
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  {
   "cell_type": "markdown",
   "id": "4ffc061c-0a32-49be-b0cd-23f957a3d717",
   "metadata": {},
   "source": [
    "***First row behaviour with*** *header* ***parameter***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "65e11af2-5b7e-45fb-8bd5-132ade305590",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "             product_id   price  merchant_id      brand  \\\n",
       "0  AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "1  AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "2  AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "3  AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "4  AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                name  \n",
       "0  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "1  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "2           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "3  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "4  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
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     "execution_count": 6,
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    "pd.read_excel('data/products.xlsx').head()"
   ]
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   "cell_type": "code",
   "execution_count": 7,
   "id": "3cb45be3-edba-4582-bf6a-f2f0e72f3ed6",
   "metadata": {},
   "outputs": [
    {
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       "                      0       1            2          3  \\\n",
       "0            product_id   price  merchant_id      brand   \n",
       "1  AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "2  AVpgMuGwLJeJML43KY_c      69         1002    Boytone   \n",
       "3  AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "4  AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "\n",
       "                                                   4  \n",
       "0                                               name  \n",
       "1  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "2  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "3           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "4  DreamWave - Tremor Portable Bluetooth Speaker ...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
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   ],
   "source": [
    "pd.read_excel('data/products.xlsx',\n",
    "              header=None).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0dbcad51-ed20-4924-abcf-e36992871286",
   "metadata": {},
   "source": [
    "***Adding index to our data using*** *index_col* ***parameter***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f1143ecd-1981-4744-a2ed-badbf34c8746",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_excel('data/products.xlsx',\n",
    "                   index_col=[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3c065e72-84a3-4ebe-bbf2-ce2d50424c4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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      ],
      "text/plain": [
       "                       price  merchant_id      brand  \\\n",
       "product_id                                             \n",
       "AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                                   name  \n",
       "product_id                                                               \n",
       "AVphzgbJLJeJML43fA0o  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "AVpgMuGwLJeJML43KY_c  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "AVpe9FXeLJeJML43zHrq           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "AVpfVJXu1cnluZ0-iwTT  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "AVphUeKeilAPnD_x3-Be  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e6438fc3-4115-4996-ae02-54723c04fbc7",
   "metadata": {},
   "source": [
    "***Selecting specific sheets***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c480e9dc-b7c0-4395-b671-0f13914681d0",
   "metadata": {},
   "outputs": [],
   "source": [
    "products = pd.read_excel('data/products.xlsx',\n",
    "                         sheet_name='Products',\n",
    "                         index_col='product_id')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "333ad2e6-59d3-40a1-b625-3af1a536b287",
   "metadata": {},
   "source": [
    "products.head("
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "aee26fac-567a-4e85-84f4-32e03173b716",
   "metadata": {},
   "outputs": [],
   "source": [
    "merchants = pd.read_excel('data/products.xlsx',\n",
    "                          sheet_name='Merchants',\n",
    "                          index_col='merchant_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b7579851-1df3-4b87-a57f-95e4c072cda9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th>merchant</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1001</th>\n",
       "      <td>Bestbuy.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>Walmart.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1003</th>\n",
       "      <td>Bestbuy.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1004</th>\n",
       "      <td>Growkart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>bhphotovideo.com</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     merchant\n",
       "merchant_id                  \n",
       "1001              Bestbuy.com\n",
       "1002              Walmart.com\n",
       "1003              Bestbuy.com\n",
       "1004                 Growkart\n",
       "1005         bhphotovideo.com"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merchants.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8ad98863-1cd5-4add-ba3f-b2808393e2ba",
   "metadata": {},
   "source": [
    "***The ExcelFile class***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "cc3f1a39-baef-44ef-836e-7cfcc2476f8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "excel_file = pd.ExcelFile('data/products.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "99d93025-8df1-49a3-9391-b9ad5def44d7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Products', 'Descriptions', 'Merchants']"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "excel_file.sheet_names"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9fe31c95-be81-4deb-b4dd-414e7a98b016",
   "metadata": {},
   "source": [
    "Everytime we call parse() method, we'll need to pass an explicit sheet_name parameter indicating which sheet from the Excel file we want to be parsed. First sheet will be parsed by default."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "924ab569-9c2d-43fa-9dac-49250ee5b6f4",
   "metadata": {},
   "outputs": [],
   "source": [
    "products = excel_file.parse('Products')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "17c96aec-b0e6-4532-ac0d-64578851f779",
   "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",
       "        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>product_id</th>\n",
       "      <th>price</th>\n",
       "      <th>merchant_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AVphzgbJLJeJML43fA0o</td>\n",
       "      <td>104.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>Sanus</td>\n",
       "      <td>Sanus VLF410B1 10-Inch Super Slim Full-Motion ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AVpgMuGwLJeJML43KY_c</td>\n",
       "      <td>69.00</td>\n",
       "      <td>1002</td>\n",
       "      <td>Boytone</td>\n",
       "      <td>Boytone - 2500W 2.1-Ch. Home Theater System - ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AVpe9FXeLJeJML43zHrq</td>\n",
       "      <td>23.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DENAQ</td>\n",
       "      <td>DENAQ - AC Adapter for TOSHIBA SATELLITE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AVpfVJXu1cnluZ0-iwTT</td>\n",
       "      <td>290.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DreamWave</td>\n",
       "      <td>DreamWave - Tremor Portable Bluetooth Speaker ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AVphUeKeilAPnD_x3-Be</td>\n",
       "      <td>244.01</td>\n",
       "      <td>1004</td>\n",
       "      <td>Yamaha</td>\n",
       "      <td>NS-SP1800BL 5.1-Channel Home Theater System (B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             product_id   price  merchant_id      brand  \\\n",
       "0  AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "1  AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "2  AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "3  AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "4  AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                name  \n",
       "0  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "1  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "2           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "3  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "4  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "59909f23-4a5c-4054-8ec3-92e332b900fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "products = excel_file.parse(sheet_name='Products',\n",
    "                            header=0,\n",
    "                            index_col='product_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "7f15ee39-572a-4bf9-9f06-a7867738740e",
   "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",
       "    .dataframe thead th {\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>price</th>\n",
       "      <th>merchant_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AVphzgbJLJeJML43fA0o</th>\n",
       "      <td>104.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>Sanus</td>\n",
       "      <td>Sanus VLF410B1 10-Inch Super Slim Full-Motion ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVpgMuGwLJeJML43KY_c</th>\n",
       "      <td>69.00</td>\n",
       "      <td>1002</td>\n",
       "      <td>Boytone</td>\n",
       "      <td>Boytone - 2500W 2.1-Ch. Home Theater System - ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVpe9FXeLJeJML43zHrq</th>\n",
       "      <td>23.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DENAQ</td>\n",
       "      <td>DENAQ - AC Adapter for TOSHIBA SATELLITE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVpfVJXu1cnluZ0-iwTT</th>\n",
       "      <td>290.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DreamWave</td>\n",
       "      <td>DreamWave - Tremor Portable Bluetooth Speaker ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVphUeKeilAPnD_x3-Be</th>\n",
       "      <td>244.01</td>\n",
       "      <td>1004</td>\n",
       "      <td>Yamaha</td>\n",
       "      <td>NS-SP1800BL 5.1-Channel Home Theater System (B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       price  merchant_id      brand  \\\n",
       "product_id                                             \n",
       "AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                                   name  \n",
       "product_id                                                               \n",
       "AVphzgbJLJeJML43fA0o  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "AVpgMuGwLJeJML43KY_c  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "AVpe9FXeLJeJML43zHrq           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "AVpfVJXu1cnluZ0-iwTT  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "AVphUeKeilAPnD_x3-Be  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "8797792e-00d9-4139-9666-a3ab9988167d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "price          float64\n",
       "merchant_id      int64\n",
       "brand           object\n",
       "name            object\n",
       "dtype: object"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "61fa4380-0f31-446c-bb93-e1007fb5d743",
   "metadata": {},
   "outputs": [],
   "source": [
    "merchants = excel_file.parse('Merchants',\n",
    "                             index_col='merchant_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "07a9beb4-59d8-4ba2-817e-40dc33ec7932",
   "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>merchant</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>merchant_id</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1001</th>\n",
       "      <td>Bestbuy.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1002</th>\n",
       "      <td>Walmart.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1003</th>\n",
       "      <td>Bestbuy.com</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1004</th>\n",
       "      <td>Growkart</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1005</th>\n",
       "      <td>bhphotovideo.com</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     merchant\n",
       "merchant_id                  \n",
       "1001              Bestbuy.com\n",
       "1002              Walmart.com\n",
       "1003              Bestbuy.com\n",
       "1004                 Growkart\n",
       "1005         bhphotovideo.com"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merchants.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "f4171ef0-b25b-47e7-bf78-d4078e82e7d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "merchant    object\n",
       "dtype: object"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merchants.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ea7bc1f1-fe0b-45a5-a91f-4c2076a1c763",
   "metadata": {},
   "source": [
    "***Save to Excel file***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "1d1bb7fb-d3b0-45a7-b0fc-e5540c362534",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>price</th>\n",
       "      <th>merchant_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>product_id</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AVphzgbJLJeJML43fA0o</th>\n",
       "      <td>104.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>Sanus</td>\n",
       "      <td>Sanus VLF410B1 10-Inch Super Slim Full-Motion ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVpgMuGwLJeJML43KY_c</th>\n",
       "      <td>69.00</td>\n",
       "      <td>1002</td>\n",
       "      <td>Boytone</td>\n",
       "      <td>Boytone - 2500W 2.1-Ch. Home Theater System - ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVpe9FXeLJeJML43zHrq</th>\n",
       "      <td>23.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DENAQ</td>\n",
       "      <td>DENAQ - AC Adapter for TOSHIBA SATELLITE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVpfVJXu1cnluZ0-iwTT</th>\n",
       "      <td>290.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DreamWave</td>\n",
       "      <td>DreamWave - Tremor Portable Bluetooth Speaker ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AVphUeKeilAPnD_x3-Be</th>\n",
       "      <td>244.01</td>\n",
       "      <td>1004</td>\n",
       "      <td>Yamaha</td>\n",
       "      <td>NS-SP1800BL 5.1-Channel Home Theater System (B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       price  merchant_id      brand  \\\n",
       "product_id                                             \n",
       "AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                                   name  \n",
       "product_id                                                               \n",
       "AVphzgbJLJeJML43fA0o  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "AVpgMuGwLJeJML43KY_c  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "AVpe9FXeLJeJML43zHrq           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "AVpfVJXu1cnluZ0-iwTT  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "AVphUeKeilAPnD_x3-Be  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "products.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "95c770d1-4127-4825-b574-77f573d6122a",
   "metadata": {},
   "outputs": [],
   "source": [
    "products.to_excel('out.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "e383eeef-8a44-4d6a-a717-2e81683ca20b",
   "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",
       "        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>product_id</th>\n",
       "      <th>price</th>\n",
       "      <th>merchant_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AVphzgbJLJeJML43fA0o</td>\n",
       "      <td>104.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>Sanus</td>\n",
       "      <td>Sanus VLF410B1 10-Inch Super Slim Full-Motion ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AVpgMuGwLJeJML43KY_c</td>\n",
       "      <td>69.00</td>\n",
       "      <td>1002</td>\n",
       "      <td>Boytone</td>\n",
       "      <td>Boytone - 2500W 2.1-Ch. Home Theater System - ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AVpe9FXeLJeJML43zHrq</td>\n",
       "      <td>23.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DENAQ</td>\n",
       "      <td>DENAQ - AC Adapter for TOSHIBA SATELLITE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AVpfVJXu1cnluZ0-iwTT</td>\n",
       "      <td>290.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DreamWave</td>\n",
       "      <td>DreamWave - Tremor Portable Bluetooth Speaker ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AVphUeKeilAPnD_x3-Be</td>\n",
       "      <td>244.01</td>\n",
       "      <td>1004</td>\n",
       "      <td>Yamaha</td>\n",
       "      <td>NS-SP1800BL 5.1-Channel Home Theater System (B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             product_id   price  merchant_id      brand  \\\n",
       "0  AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "1  AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "2  AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "3  AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "4  AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                name  \n",
       "0  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "1  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "2           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "3  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "4  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_excel('out.xlsx').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "ca38268a-34c8-43ff-b918-a89252dacde8",
   "metadata": {},
   "outputs": [],
   "source": [
    "products.to_excel('out.xlsx',\n",
    "                  sheet_name='Products')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "b21689ba-02c2-4871-83f9-23df1ad65d28",
   "metadata": {},
   "outputs": [],
   "source": [
    "products.to_excel('out.xlsx',\n",
    "                  index=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "d6b960ca-9ff9-4ad0-8c73-c275bac55bc8",
   "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>price</th>\n",
       "      <th>merchant_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>104.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>Sanus</td>\n",
       "      <td>Sanus VLF410B1 10-Inch Super Slim Full-Motion ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>69.00</td>\n",
       "      <td>1002</td>\n",
       "      <td>Boytone</td>\n",
       "      <td>Boytone - 2500W 2.1-Ch. Home Theater System - ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>23.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DENAQ</td>\n",
       "      <td>DENAQ - AC Adapter for TOSHIBA SATELLITE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>290.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DreamWave</td>\n",
       "      <td>DreamWave - Tremor Portable Bluetooth Speaker ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>244.01</td>\n",
       "      <td>1004</td>\n",
       "      <td>Yamaha</td>\n",
       "      <td>NS-SP1800BL 5.1-Channel Home Theater System (B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    price  merchant_id      brand  \\\n",
       "0  104.99         1001      Sanus   \n",
       "1   69.00         1002    Boytone   \n",
       "2   23.99         1001      DENAQ   \n",
       "3  290.99         1001  DreamWave   \n",
       "4  244.01         1004     Yamaha   \n",
       "\n",
       "                                                name  \n",
       "0  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "1  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "2           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "3  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "4  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_excel('out.xlsx').head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "73f7fcea-b897-43a8-b68a-fb67afc8b3c5",
   "metadata": {},
   "source": [
    "***Positioning Data with*** *startrow* ***and*** *startcol*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "63ec23c5-2ed3-4a4e-baea-3e84ec79ec4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "products.to_excel('out.xlsx',\n",
    "                  sheet_name='Products',\n",
    "                  startrow=1,\n",
    "                  startcol=2)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "88468231-9f9d-4d97-93b7-e97f3b632e09",
   "metadata": {},
   "source": [
    "***Saving multiple sheets***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "058e2fec-1e86-4f44-ad16-c44cfbc870a4",
   "metadata": {},
   "outputs": [],
   "source": [
    "writer = pd.ExcelWriter('out.xlsx')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "56d9777d-35c7-4ac9-8e64-f8b35eabcdd2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.io.excel._openpyxl.OpenpyxlWriter at 0x1d8c15908d0>"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "writer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "352e0900-569d-4895-9874-ed942c7d14c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "with writer:\n",
    "    products.to_excel(writer, sheet_name='Products')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "e9865f82-9e3f-45ca-a097-76483d664a9d",
   "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",
       "    .dataframe thead th {\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>product_id</th>\n",
       "      <th>price</th>\n",
       "      <th>merchant_id</th>\n",
       "      <th>brand</th>\n",
       "      <th>name</th>\n",
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       "      <td>AVphzgbJLJeJML43fA0o</td>\n",
       "      <td>104.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>Sanus</td>\n",
       "      <td>Sanus VLF410B1 10-Inch Super Slim Full-Motion ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AVpgMuGwLJeJML43KY_c</td>\n",
       "      <td>69.00</td>\n",
       "      <td>1002</td>\n",
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       "    </tr>\n",
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       "      <th>2</th>\n",
       "      <td>AVpe9FXeLJeJML43zHrq</td>\n",
       "      <td>23.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DENAQ</td>\n",
       "      <td>DENAQ - AC Adapter for TOSHIBA SATELLITE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AVpfVJXu1cnluZ0-iwTT</td>\n",
       "      <td>290.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DreamWave</td>\n",
       "      <td>DreamWave - Tremor Portable Bluetooth Speaker ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AVphUeKeilAPnD_x3-Be</td>\n",
       "      <td>244.01</td>\n",
       "      <td>1004</td>\n",
       "      <td>Yamaha</td>\n",
       "      <td>NS-SP1800BL 5.1-Channel Home Theater System (B...</td>\n",
       "    </tr>\n",
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       "             product_id   price  merchant_id      brand  \\\n",
       "0  AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "1  AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "2  AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "3  AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "4  AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                name  \n",
       "0  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "1  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "2           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "3  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "4  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_excel('out.xlsx', sheet_name='Products').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "0b6ad353-4578-4efd-b885-ce1afd1c3a4f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>product_id</th>\n",
       "      <th>price</th>\n",
       "      <th>merchant_id</th>\n",
       "      <th>brand</th>\n",
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       "      <td>Sanus</td>\n",
       "      <td>Sanus VLF410B1 10-Inch Super Slim Full-Motion ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AVpgMuGwLJeJML43KY_c</td>\n",
       "      <td>69.00</td>\n",
       "      <td>1002</td>\n",
       "      <td>Boytone</td>\n",
       "      <td>Boytone - 2500W 2.1-Ch. Home Theater System - ...</td>\n",
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       "      <td>DENAQ</td>\n",
       "      <td>DENAQ - AC Adapter for TOSHIBA SATELLITE</td>\n",
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       "      <th>3</th>\n",
       "      <td>AVpfVJXu1cnluZ0-iwTT</td>\n",
       "      <td>290.99</td>\n",
       "      <td>1001</td>\n",
       "      <td>DreamWave</td>\n",
       "      <td>DreamWave - Tremor Portable Bluetooth Speaker ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AVphUeKeilAPnD_x3-Be</td>\n",
       "      <td>244.01</td>\n",
       "      <td>1004</td>\n",
       "      <td>Yamaha</td>\n",
       "      <td>NS-SP1800BL 5.1-Channel Home Theater System (B...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             product_id   price  merchant_id      brand  \\\n",
       "0  AVphzgbJLJeJML43fA0o  104.99         1001      Sanus   \n",
       "1  AVpgMuGwLJeJML43KY_c   69.00         1002    Boytone   \n",
       "2  AVpe9FXeLJeJML43zHrq   23.99         1001      DENAQ   \n",
       "3  AVpfVJXu1cnluZ0-iwTT  290.99         1001  DreamWave   \n",
       "4  AVphUeKeilAPnD_x3-Be  244.01         1004     Yamaha   \n",
       "\n",
       "                                                name  \n",
       "0  Sanus VLF410B1 10-Inch Super Slim Full-Motion ...  \n",
       "1  Boytone - 2500W 2.1-Ch. Home Theater System - ...  \n",
       "2           DENAQ - AC Adapter for TOSHIBA SATELLITE  \n",
       "3  DreamWave - Tremor Portable Bluetooth Speaker ...  \n",
       "4  NS-SP1800BL 5.1-Channel Home Theater System (B...  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_excel('out.xlsx', sheet_name='Products').head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "b663b633-40e8-4e03-b492-ca6af17c3555",
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.ExcelWriter('out.xlsx') as writer:\n",
    "    products.to_excel(writer, sheet_name='Products')\n",
    "    merchants.to_excel(writer, sheet_name='Merchants')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d708e779-65b3-4dda-8d24-f4aa7a4c25e2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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