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gpt-sugg/Datasaurus_Lab_Instructor_Intro.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4e23ea39",
+   "metadata": {},
+   "source": [
+    "\n",
+    "# 📘 Instructor Version – Introductory EDA Lab\n",
+    "\n",
+    "## Learning Objectives\n",
+    "\n",
+    "Students should:\n",
+    "\n",
+    "- Understand what a dataset structure looks like\n",
+    "- Identify variable types\n",
+    "- Compute descriptive statistics\n",
+    "- Recognize the limits of summary statistics\n",
+    "- Appreciate visualization as a fundamental step in EDA\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "38ebe89c",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Teaching Strategy\n",
+    "\n",
+    "This is NOT a technical coding lab.\n",
+    "\n",
+    "It is conceptual:\n",
+    "- Data structure awareness\n",
+    "- Reading metadata\n",
+    "- Interpreting statistics\n",
+    "- Understanding why visualization matters\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ecee2660",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "import pyreadr\n",
+    "import pandas as pd\n",
+    "import sweetviz as sv\n",
+    "import dtale\n",
+    "\n",
+    "result = pyreadr.read_r(\"datasaurus_dozen.rda\")\n",
+    "df = list(result.values())[0]\n",
+    "df.head()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ca5dfd49",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Discussion Prompts\n",
+    "\n",
+    "### After df.info():\n",
+    "- What is categorical?\n",
+    "- What is numerical?\n",
+    "- Why does data type matter?\n",
+    "\n",
+    "### After df.describe():\n",
+    "Important insight:\n",
+    "Different datasets may have nearly identical summary statistics.\n",
+    "\n",
+    "Ask:\n",
+    "Would you trust the numbers without visualization?\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7c61c04b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "df.describe()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5093ed70",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Sweetviz Discussion\n",
+    "\n",
+    "Use the report to show:\n",
+    "\n",
+    "- Similar means and standard deviations\n",
+    "- Very different visual distributions\n",
+    "- The importance of scatter plots\n",
+    "\n",
+    "Key message:\n",
+    "📌 \"Statistics describe. Visualization reveals.\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8ae6139f",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "report = sv.analyze(df)\n",
+    "report.show_html(\"sweetviz_report.html\")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d3a3d619",
+   "metadata": {},
+   "source": [
+    "\n",
+    "## Key Concept to Emphasize\n",
+    "\n",
+    "EDA is:\n",
+    "- Understanding structure\n",
+    "- Understanding distributions\n",
+    "- Detecting anomalies\n",
+    "- Preparing for cleaning\n",
+    "\n",
+    "Next lab:\n",
+    "Students receive messy datasets with:\n",
+    "- Missing values\n",
+    "- Wrong types\n",
+    "- Outliers\n",
+    "- Inconsistent categories\n"
+   ]
+  }
+ ],
+ "metadata": {},
+ "nbformat": 4,
+ "nbformat_minor": 5
+}