Add notebooks

01_data_exploration.ipynb

@@ -0,0 +1,103 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 📊 Myanmar Ghost - Data Exploration\n",
+    "\n",
+    "This notebook explores the Myanmar Ghost dataset."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import sys\n",
+    "sys.path.insert(0, '..')\n",
+    "\n",
+    "import pandas as pd\n",
+    "import matplotlib.pyplot as plt\n",
+    "import seaborn as sns\n",
+    "\n",
+    "sns.set_style('whitegrid')\n",
+    "%matplotlib inline"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load sample data\n",
+    "df = pd.read_csv('../data/processed/splits/train.csv')\n",
+    "df.head()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Label distribution\n",
+    "plt.figure(figsize=(8, 5))\n",
+    "df['label'].value_counts().plot(kind='bar', color='steelblue')\n",
+    "plt.title('Sentiment Label Distribution')\n",
+    "plt.xlabel('Sentiment')\n",
+    "plt.ylabel('Count')\n",
+    "plt.xticks(rotation=45)\n",
+    "plt.tight_layout()\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Text length distribution\n",
+    "df['text_length'] = df['text'].str.len()\n",
+    "\n",
+    "plt.figure(figsize=(10, 5))\n",
+    "sns.histplot(data=df, x='text_length', hue='label', kde=True)\n",
+    "plt.title('Text Length Distribution by Sentiment')\n",
+    "plt.xlabel('Text Length (characters)')\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Sample texts\n",
+    "print(\"=== Positive Examples ===\")\n",
+    "for text in df[df['label']=='positive']['text'].head(3):\n",
+    "    print(f\"- {text}\")\n",
+    "\n",
+    "print(\"\\n=== Negative Examples ===\")\n",
+    "for text in df[df['label']=='negative']['text'].head(3):\n",
+    "    print(f\"- {text}\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.10.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}