Exercise

src/2-bar-plot.ipynb

@@ -2,27 +2,72 @@
  "cells": [
   {
    "cell_type": "markdown",
+   "id": "6d5ca570",
    "metadata": {},
    "source": [
-    "### Exercise 2: Bar Plot with Colors"
+    "Exercise 2: Bar Chart With Colors"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
+   "id": "9fdc712a",
    "metadata": {},
    "outputs": [],
    "source": [
     "# TASK: Create a bar plot with the following data: categories = ['A', 'B', 'C', 'D'] and values = [5, 7, 3, 9].\n",
     "# Use different colors for each bar and add a title to the plot."
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "dd6b197b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "categories = ['A', 'B', 'C', 'D']\n",
+    "values = [5, 7, 3, 9]\n",
+    "colors = ['red', 'green', 'blue', 'orange']\n",
+    "\n",
+    "plt.bar(categories, values, color=colors)\n",
+    "plt.title(\"Bar Plot of Categories\")\n",
+    "plt.show()\n"
+   ]
   }
  ],
  "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
   "language_info": {
-   "name": "python"
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 5
 }