Upload Excel_guide.ipynb

Excel_guide.ipynb

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+{
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+   "id": "7e2a8960-f41d-40fc-a8e7-43c7e938e759",
+   "metadata": {},
+   "source": [
+    "# Excel"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7ea74fc9-f615-4214-a2a0-da948feb484e",
+   "metadata": {},
+   "source": [
+    "## (a) What It Is\n",
+    "- Excel is a spreadsheet application developed by Microsoft, widely used for organizing, analyzing, and storing structured data in tabular form.\n",
+    "\n",
+    "## Common file extensions: \n",
+    "- .xlsx (current standard) and .xls (older versions).\n",
+    "\n",
+    "## Features:\n",
+    "- Rows and columns for data organization.\n",
+    "- Built-in formulas and functions for calculations.\n",
+    "- Support for charts and data visualization.\n",
+    "- Capability to handle multiple sheets in a single file."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "fd26d0c4-3772-46f3-9bcc-18a7aedeb4cc",
+   "metadata": {},
+   "source": [
+    "## (b) How to Read These Files\n",
+    "- In Python, the pandas library provides a simple and efficient way to read Excel files."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "06ae061f-6c3e-4b3c-8e33-8bf8dda50c88",
+   "metadata": {},
+   "source": [
+    "## Code Example:\n",
+    "import pandas as pd\n",
+    "\n",
+    "### Reading an Excel file\n",
+    "df = pd.read_excel(\"example.xlsx\")\n",
+    "\n",
+    "### Display the first few rows\n",
+    "print(df.head())"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d6b0b4b3-7514-4b8e-9887-51fd25b4bacf",
+   "metadata": {},
+   "source": [
+    "## Explanation:\n",
+    "### read_excel():\n",
+    "- Reads data from the specified Excel file.\n",
+    "- Automatically detects the first sheet unless specified."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bcb8595c-b0f0-47a6-b8e4-5d9d42dd797d",
+   "metadata": {},
+   "source": [
+    "## (c) What Are the Issues Encountered When Handling These Files?\n",
+    "1. Missing Data\n",
+    "Cells may be empty, causing errors or skewed analysis.\n",
+    "2. Encoding Problems\n",
+    "Older Excel files or files saved with non-standard encodings may raise errors.\n",
+    "3. Corrupted Files\n",
+    "Excel files can get corrupted, becoming unreadable.\n",
+    "4. Large Files\n",
+    "Excel struggles with large datasets (e.g., millions of rows).\n",
+    "5. Unsupported Features\n",
+    "Some advanced Excel features (like macros) may not be accessible in Python.\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6d2e0ab1-61bb-40a3-a232-ab94fa5669a8",
+   "metadata": {},
+   "source": [
+    "## (d) How to Overcome These Errors/Issues?\n",
+    "1. Missing Data\n",
+    "- Use pandas methods to handle missing values:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a4366681-0738-49dd-8f06-34f4e3bdec03",
+   "metadata": {},
+   "source": [
+    "## code:\n",
+    "### df.fillna(value=\"Unknown\", inplace=True)  # Fill missing values with a placeholder\n",
+    "### df.dropna(inplace=True)  # Remove rows with missing values"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cd4081ed-3060-4a90-95d6-0ebcbca45439",
+   "metadata": {},
+   "source": [
+    "## 2. Corrupted Files\n",
+    "- Open the file in Excel and repair it manually or save it as a CSV file for processing."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8b23e35a-911e-4673-8b2d-1a25e38ef756",
+   "metadata": {},
+   "source": [
+    "## 3. Large Files\n",
+    "- Read data in chunks using pandas:"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "141a2aba-4ce1-48e6-af2e-5102b927dcca",
+   "metadata": {},
+   "source": [
+    "## code:\n",
+    "### for chunk in pd.read_excel(\"large_file.xlsx\", chunksize=1000):\n",
+    " ### process(chunk)  # Replace `process` with your function"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cc730499-3610-406c-8b1c-8b7fc39805fd",
+   "metadata": {},
+   "source": [
+    "## 5. Unsupported Features\n",
+    "- Avoid saving files with unsupported features if they need to be processed programmatically.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
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