{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Bar Graph"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1. Basic Bar Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Step 1: Import Libraries\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Step 2: Create Sample Data\n",
    "x = np.arange(24)\n",
    "\n",
    "np.random.seed(42)\n",
    "noise = np.random.uniform(-1, 1.5, size=x.shape)\n",
    "y = 20 + 8 * np.sin((x - 9) * np.pi / 12) + noise\n",
    "\n",
    "y_error = np.random.uniform(0.5, 0.75, size=x.shape)\n",
    "\n",
    "# Step 3: Plotting the bar graph with error bars\n",
    "plt.figure(figsize=(12, 6))\n",
    "plt.bar(x, y, yerr=y_error, capsize=5, color='skyblue', edgecolor='black')\n",
    "plt.title('Basic Bar Chart')\n",
    "plt.xlabel('X-axis')\n",
    "plt.ylabel('Y-axis')\n",
    "plt.ylim(10,30)\n",
    "plt.xticks(x)\n",
    "plt.grid(axis='y', linestyle='--', alpha=0.7)\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "myenv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}