{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "3213a9fe",
   "metadata": {},
   "source": [
    "# 1. 🐍 Introduction to Python: Basics\n",
    "\n",
    "![Status](https://img.shields.io/static/v1.svg?label=Status&message=Finished&color=green)\n",
    "\n",
    "**Filled notebook:** \n",
    "[![View filled on Github](https://img.shields.io/static/v1.svg?logo=github&label=Repo&message=View%20On%20Github&color=lightgrey)](https://github.com/bfortuno/Surgical-Phase-Recognition/blob/main/docs/tutorial_notebooks/tutorial1/python_basics_1.ipynb)\n",
    "[![Open filled In Collab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/bfortuno/Surgical-Phase-Recognition/blob/main/docs/tutorial_notebooks/tutorial1/python_basics_1.ipynb)    \n",
    "**Author:** Benjamin I. Fortuno\n",
    "\n",
    "**📌 Learning Objectives:**\n",
    "- Understand Python fundamentals\n",
    "- Work with lists and dictionaries\n",
    "- Read and process CSV files\n",
    "- Compute basic statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "45f5ecc8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Not running on CoLab\n"
     ]
    }
   ],
   "source": [
    "# Setup the environment for the tutorial notebook to run on CoLab\n",
    "# This script will clone the repository and change the working directory to the tutorial notebook directory\n",
    "if 'google.colab' in str(get_ipython()):\n",
    "  print('Running on CoLab')\n",
    "  !git clone https://github.com/bfortuno/Surgical-Phase-Recognition.git         # Clone the repository\n",
    "  %cd Surgical-Phase-Recognition/docs/tutorial_notebooks/tutorial1\n",
    "else:\n",
    "  print('Not running on CoLab')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2d885f5e",
   "metadata": {},
   "source": [
    "## **1 Python Basics**\n",
    "### **1.1 Variables & Data Types**\n",
    "\n",
    "In Python, variables store values. Let's look at some common data types:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "df8880d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10 3.14 Hello, AI! True\n"
     ]
    }
   ],
   "source": [
    "# Integer\n",
    "a = 10\n",
    "\n",
    "# Float\n",
    "b = 3.14\n",
    "\n",
    "# String\n",
    "c = 'Hello, AI!'\n",
    "\n",
    "# Boolean\n",
    "d = True\n",
    "\n",
    "# Print values\n",
    "print(a, b, c, d)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9e0d95e8",
   "metadata": {},
   "source": [
    "👉 **Task**: Try defining your own variables and print them."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "70481563",
   "metadata": {},
   "source": [
    "### **1.2 Conditionals and Loops**\n",
    "\n",
    "**If-else statements** allow decision-making:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "2226bbcb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Positive number\n"
     ]
    }
   ],
   "source": [
    "x = 5\n",
    "if x > 0:\n",
    "    print('Positive number')\n",
    "else:\n",
    "    print('Negative number')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c43eb7b1",
   "metadata": {},
   "source": [
    "Loops allow us to execute a block of code multiple times. Python has two main types of loops:  \n",
    "1. **`for` loop** – Used when the number of iterations is known.\n",
    "2. **`while` loop** – Used when the number of iterations depends on a condition.\n",
    "\n",
    "---\n",
    "\n",
    "### 🌀 For Loop\n",
    "\n",
    "```python\n",
    "# For loop\n",
    "for i in range(5):\n",
    "    print(i)\n",
    "```\n",
    "#### 🔍 Explanation:\n",
    "- `range(5)` generates numbers from **0 to 4** (not including 5).\n",
    "- The loop runs **5 times**, each time printing the current value of `i`.\n",
    "- The loop automatically increments `i` in each iteration.\n",
    "\n",
    "#### ⚠️ Things to Be Careful About:\n",
    "- **Indexing Issues**: `range(n)` starts from **0** and goes up to **n-1**, not `n`.\n",
    "- **Skipping Values**: To loop from **1 to 5**, use `range(1, 6)`.\n",
    "  ```python\n",
    "  for i in range(1, 6):  # Generates 1, 2, 3, 4, 5\n",
    "      print(i)\n",
    "  ```\n",
    "- **Step Size**: Use a third argument for step size.\n",
    "  ```python\n",
    "  for i in range(0, 10, 2):  # Prints even numbers 0, 2, 4, 6, 8\n",
    "      print(i)\n",
    "  ```\n",
    "\n",
    "---\n",
    "\n",
    "### 🔄 While Loop\n",
    "```python\n",
    "# While loop\n",
    "count = 0\n",
    "while count < 3:\n",
    "    print('Count:', count)\n",
    "    count += 1\n",
    "```\n",
    "#### 🔍 Explanation:\n",
    "- The loop **executes as long as** `count < 3`.\n",
    "- The variable `count` starts at **0** and increases by **1** in each iteration.\n",
    "- When `count == 3`, the loop condition (`count < 3`) becomes **False**, and the loop stops.\n",
    "\n",
    "#### ⚠️ Things to Be Careful About:\n",
    "- **Infinite Loops**: If `count` is not incremented inside the loop, it will run forever.\n",
    "  ```python\n",
    "  while True:  # ⚠️ Infinite loop\n",
    "      print(\"This will run forever!\")\n",
    "  ```\n",
    "- **Proper Condition**: Ensure the loop will eventually stop. A faulty condition may cause the program to hang.\n",
    "- **Changing Condition Inside the Loop**: If the value of `count` is not updated properly, the loop may behave unexpectedly."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6f49372f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "Count: 0\n",
      "Count: 1\n",
      "Count: 2\n"
     ]
    }
   ],
   "source": [
    "# For loop\n",
    "for i in range(5):\n",
    "    print(i)\n",
    "\n",
    "# While loop\n",
    "count = 0\n",
    "while count < 3:\n",
    "    print('Count:', count)\n",
    "    count += 1"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "76cfd4d6",
   "metadata": {},
   "source": [
    "👉 **Task**: Modify the loops to print numbers from 1 to 10."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8860a99a",
   "metadata": {},
   "source": [
    "## **2 Functions in Python**\n",
    "\n",
    "Functions help organize code into reusable blocks:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "429a0748",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n"
     ]
    }
   ],
   "source": [
    "def add_numbers(x, y):\n",
    "    return x + y\n",
    "\n",
    "print(add_numbers(3, 5))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b18cd385",
   "metadata": {},
   "source": [
    "👉 **Task**: Write a function that multiplies two numbers."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7b931b8a",
   "metadata": {},
   "source": [
    "## **3 Lists and Dictionaries**\n",
    "\n",
    "### **3.1 Lists (Arrays in Python)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7def08b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "1\n",
      "2\n",
      "3\n",
      "4\n",
      "5\n"
     ]
    }
   ],
   "source": [
    "numbers = [1, 2, 3, 4, 5]\n",
    "\n",
    "# Access elements\n",
    "print(numbers[0])\n",
    "\n",
    "# Loop through list\n",
    "for num in numbers:\n",
    "    print(num)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4c32749a",
   "metadata": {},
   "source": [
    "### **3.2 Dictionaries (Key-Value Pairs)**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "be9573f4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Alice\n"
     ]
    }
   ],
   "source": [
    "student = {'name': 'Alice', 'age': 22, 'grade': 'A'}\n",
    "\n",
    "print(student['name'])  # Output: Alice"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "68086a57",
   "metadata": {},
   "source": [
    "👉 **Task**: Create a dictionary storing information about yourself and print it."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e73c2fb3",
   "metadata": {},
   "source": [
    "## **4 File Handling & CSV Processing**\n",
    "\n",
    "Let's read a CSV file using Python!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7999fee6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['Time', 'Temperature (C)']\n",
      "['08:00', '22.5']\n",
      "['09:00', '24.1']\n",
      "['10:00', '25.3']\n",
      "['11:00', '26.7']\n",
      "['12:00', '27.8']\n"
     ]
    }
   ],
   "source": [
    "import csv\n",
    "\n",
    "# Read a CSV file\n",
    "with open('data1.csv', 'r') as file:\n",
    "    reader = csv.reader(file)\n",
    "    for row in reader:\n",
    "        print(row)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1c847f9b",
   "metadata": {},
   "source": [
    "Now, let's compute basic statistics:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "096da635",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "         Math  Science  English\n",
      "Student                        \n",
      "Alice      85       89       75\n",
      "Bob        90       85       80\n",
      "Charlie    78       80       85\n",
      "David      92       95       90\n",
      "Eve        88       90       78\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "# Load CSV into a DataFrame, considering first row as header and first column as index\n",
    "df = pd.read_csv('data2.csv', header=0, index_col=0)\n",
    "\n",
    "# Display DataFrame head\n",
    "print(df.head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "e93a2c1c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mean: Math       86.6\n",
      "Science    87.8\n",
      "English    81.6\n",
      "dtype: float64\n",
      "Max: Math       92\n",
      "Science    95\n",
      "English    90\n",
      "dtype: int64\n",
      "Min: Math       78\n",
      "Science    80\n",
      "English    75\n",
      "dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# Compute statistics\n",
    "print('Mean:', df.mean())\n",
    "print('Max:', df.max())\n",
    "print('Min:', df.min())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e35949a4",
   "metadata": {},
   "source": [
    "👉 **Task**: Load a CSV file and compute its mean, max, and min values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b5968fc4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "b448b029",
   "metadata": {},
   "source": [
    "## **Final Task**\n",
    "1. Read a CSV file called `Surgical-deepnet.csv`\n",
    "2. Compute the mean, max, and min of each column.\n",
    "3. Print the results.\n",
    "\n",
    "💡 **Hint**: Use Pandas (`pd.read_csv()`) for easy CSV handling."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b99dcbf0",
   "metadata": {},
   "source": []
  }
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