Day_02.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "VG6wE0Q9U17m"
      },
      "source": [
        "\n",
        "This note book cover the following concepts\n",
        "1. Arithmetic Operators\n",
        "2. Logical Operators"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KdzvZ6NAqHcG"
      },
      "source": [
        "# **RECAP the Day_01 **\n",
        "# **Difference between List, Tuple, Sets and Dictionay**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GqFrvLfsry92"
      },
      "source": [
        "![difference details.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7sRR0aMSr39f"
      },
      "source": [
        "![difference .png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "DIJ5Ae5GyEUE"
      },
      "source": [
        "## **What are Operators?**\n",
        "\n",
        "Python operators are symbols that perform an operation on one or more operands. An operand is a variable or a value on which we perform the operation\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "peHHjerTyeBM"
      },
      "source": [
        "## **Why use Operators?**\n",
        "\n",
        "Operators can manipulate individual items and return a result. Operators manipulate individual items by conducting mathematical operations and/or returning a Boolean value (True or False)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Um_1CwNszSYH"
      },
      "source": [
        "## **What are Mathematical Operators?**\n",
        "\n",
        "\n",
        "Mathematical Operators are basic arithmetic symbol used to perform adition, subtraction, multiplication, and more"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6lJ-5RCgeVuh"
      },
      "source": [
        "Mathematical operators are basic arithmetic symbols used to perform addition, subtraction, multiplication, and more.\n",
        "\n",
        "|Operator                  |Description                                                                        |Example |\n",
        "|-------------------------|-------------------------------------------------------------------------------|-------------|\n",
        "|Assignment (=)        |Assigns a variable a value. |(x = 5)       |\n",
        "|+       | Addition.                   |(1 + 2) |\n",
        "|-         | Subtraction. | (2 - 1)\n",
        "|* | Multiplication. |(1 * 2) |\n",
        "|/             |Division. |(10 / 5)|\n",
        "|% | Modulus. |(15 % 2)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TD7k-cj7zzxn"
      },
      "source": [
        "## **Operators on Numbers**\n",
        "\n",
        "Numerical operations in Python are similar to Excel or any other programming language.\n",
        "You can use these operations to do basic arithmetic"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2hxnaToxSdxN",
        "outputId": "d5983dab-5e76-4d81-8cd5-a876e30345b2"
      },
      "outputs": [],
      "source": [
        "# Multiply two numbers and display using print\n",
        "# print(3*4)\n",
        "3*4"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "4*5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Fk3QPLeMSilp",
        "outputId": "29157e6b-99f9-4995-9b6a-7cc0dda401d2"
      },
      "outputs": [],
      "source": [
        "# Display calculate square of number\n",
        "print(3**2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "print(4**2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iugWReYhSn3k",
        "outputId": "766cc785-cbd3-4b28-b66a-0df2efc70659"
      },
      "outputs": [],
      "source": [
        "# Calculate the Remainder\n",
        "print(16%5)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OwwQOjbStzbQ"
      },
      "source": [
        "![image.png](data:image/png;base64,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)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6qx9THMsSrHt",
        "outputId": "9abc74ce-e9d4-4962-e198-fff99fd93427"
      },
      "outputs": [],
      "source": [
        "# Divide two numbers\n",
        "a = 5.0/10.0\n",
        "a"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "b = 15/3\n",
        "b"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u9ButsXpStBY",
        "outputId": "3ea18204-9ee1-4e70-ff16-741897416077"
      },
      "outputs": [],
      "source": [
        "# Calculate the Quotient of two numbers\n",
        "b= 11//4\n",
        "b"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "c = 20 // 5\n",
        "c"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "d = 20 % 5\n",
        "d"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MQPAUAXISwuz"
      },
      "source": [
        "### Adding two integers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jD3uGZ7OS1RB",
        "outputId": "8996d10b-dc37-478a-b387-38d6f394d14f"
      },
      "outputs": [],
      "source": [
        "# Assigning a value of 5 to the variable num1\n",
        "num1 = 5\n",
        "\n",
        "# Assigning a value of 2 to the variable num2\n",
        "num2 = 2\n",
        "\n",
        "# Calculating the sum of num1 and num2 and storing it in the variable 'sum'\n",
        "sum = num1 + num2\n",
        "\n",
        "# Printing the calculated sum\n",
        "print(sum)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "30"
            ]
          },
          "execution_count": 1,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "## adding three numbers \n",
        "\n",
        "num1 = 5\n",
        "num2 = 10 \n",
        "num3 = 15\n",
        "\n",
        "sum_of_num = num1 + num2 + num3\n",
        "sum_of_num"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sKzqOVqdS6cY"
      },
      "source": [
        "## simple program to calculate the area of Rectangle\n",
        "area of rectangle = length * height\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4g6MBTUcS_Bf",
        "outputId": "5335a2cf-def6-4895-ee64-91108f394a70"
      },
      "outputs": [],
      "source": [
        "# Defining the length of the rectangle\n",
        "length = 2.5\n",
        "\n",
        "# Defining the height of the rectangle\n",
        "height = 3.5\n",
        "\n",
        "# Calculating the area of the rectangle using length and height\n",
        "area = length * height\n",
        "\n",
        "# Printing the calculated area of the rectangle\n",
        "print(area)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "# are_of_rectangle = length * height\n",
        "\n",
        "height = 2\n",
        "length = 3\n",
        "are_of_rectangle = height * length\n",
        "are_of_rectangle"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EfHOAtkevQ3w"
      },
      "source": [
        "Comparison operators are used to compare values, they either return True or False.\n",
        "\n",
        "|Operator                  |Description                                                                        |Example |\n",
        "|-------------------------|-------------------------------------------------------------------------------|-------------|\n",
        "|Equal to (==)        |If the values of the two operands are equal, then the condition becomes true. |(a == a) is True.       |\n",
        "|Not Equal to (!=)       |If the values of the two operands are not equal, then the condition becomes true.                    |(a != b) is True.|\n",
        "|Greater Than, Greater than or Equal to (>, >=)          |If the value of the left operand is greater than the value of the right operand then the condition becomes true. | (2>1) is True.\n",
        "|Less Than, Less than or Equal to (<, <=) |If the value of the left operand is less than the value of the right operand then the condition becomes true. |(1<2) is True.|\n",
        "|and              |Returns True if all statements are True. |(1<2 and 2>1) is True.|\n",
        "|or | Returns True if one of the statements is True. |(1<2 or 2<4) is True.\n",
        "|not | Reverse the result, returns False if the statement is True.| not(1<5 and 5>3) is not True.\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IFxC76I6Oy4b",
        "outputId": "c64ab5eb-e282-4444-e02b-db2bd7e70b48"
      },
      "outputs": [],
      "source": [
        "# Assigning a value of 330 to variable a\n",
        "a = 330\n",
        "\n",
        "# Assigning a value of 200 to variable b\n",
        "b = 200\n",
        "\n",
        "# Checking if a is equal to b using the equality operator (==)\n",
        "# The result of this comparison will be False since a (330) is not equal to b (200)\n",
        "result = a == b\n",
        "\n",
        "# Printing the result of the comparison\n",
        "print(\"Is a equal to b?\", result)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "a = 500\n",
        "b = 300\n",
        "\n",
        "result = a == b\n",
        "result"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "result = a != b\n",
        "result"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "result = a != b\n",
        "result "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NnTquilkwTgh",
        "outputId": "2817009b-63e8-4f21-c39f-70a6cd6847f4"
      },
      "outputs": [],
      "source": [
        "# Checking if a is not equal to b using the inequality operator (!=)\n",
        "# The result of this comparison will be True since a (330) is not equal to b (200)\n",
        "result = a != b\n",
        "\n",
        "# Printing the result of the comparison\n",
        "print(\"Is a not equal to b?\", result)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EVcy1NUAwVr3",
        "outputId": "0e269b8c-93b1-459f-dce0-fc4a3c74ab3e"
      },
      "outputs": [],
      "source": [
        "# Checking if a is greater than b using the greater than operator (>)\n",
        "# The result of this comparison will be True since a (330) is greater than b (200)\n",
        "result = a > b\n",
        "print(\"The value a is greater than b \", a, \"then b\",b, result)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "34j3xADUwZt5",
        "outputId": "ec8f7edd-dc7b-419a-f9a6-fce0378c7405"
      },
      "outputs": [],
      "source": [
        "# Checking if a is greater than b using the greater than operator (>)\n",
        "# The result of this comparison will be True since a (330) is greater than b (200)\n",
        "result = a < b\n",
        "\n",
        "# Printing the result of the comparison\n",
        "print(\"Is a greater than b?\", result)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "03CV-pP7wbNo",
        "outputId": "445c373c-bedf-416f-8147-c5cb73a47a57"
      },
      "outputs": [],
      "source": [
        "a >= b"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cxdJc0Hlwc7Z",
        "outputId": "6bd3fa28-f1d3-4bc5-ea69-e7d810e2c0af"
      },
      "outputs": [],
      "source": [
        "a <= b"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uvtrniNSvpo5",
        "outputId": "f9d46ff4-5aa1-45b3-efee-35375dd586dc"
      },
      "outputs": [],
      "source": [
        "a > 7"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Oefe_487Obpq"
      },
      "source": [
        "# **Logical Operators**\n",
        "\n",
        "\n",
        "AND\n",
        "OR\n",
        "NOT\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mEi7lnH9vyBZ",
        "outputId": "31b8da46-36cd-43a3-fbed-0689173bf4da"
      },
      "outputs": [],
      "source": [
        "a > b and a < 5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "a = 500\n",
        "b = 300"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "a > b and b == 500"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E6I6cN6Ov8Ii",
        "outputId": "e085a778-9425-4c1e-eeb6-770e59956cb4"
      },
      "outputs": [],
      "source": [
        "a > b or a < 5"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "a > b or a < 500"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Td8mEsM6aiPp"
      },
      "source": [
        "## not reverses the result, meaning it returns True if the statement is False."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4jCRbn0bahjW",
        "outputId": "5734c793-d0bd-4068-d3f2-4998912360b7"
      },
      "outputs": [],
      "source": [
        "not(1>2 and 3==4)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        " not(1>2 and 3==5)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5R3XqR5GjbL7"
      },
      "source": [
        "#### What are Membership Operators?####\n",
        "\n",
        "Membership operators are used to test whether a value or a variable is found in a sequence (string, tuple, list, set or dictionary). These operators become essential when we discuss loops.\n",
        "\n",
        "|Operator                  |Description                                                                        |Example |\n",
        "|-------------------------|-------------------------------------------------------------------------------|-------------|\n",
        "|in| Returns True if a sequence with the specified value is present in the object. | 3 in [1,2,3] is True.\n",
        "|not in| Returns True if a sequence with the specified value is not present in the object. | 4 not in [1,2,3] is True."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "vlxTiDE1kSaz"
      },
      "source": [
        "## in returns True if a sequence with the specified value is present in the object."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Pq8g4IlZkKeb",
        "outputId": "288ce470-8d0d-4a3c-c063-754d96194e17"
      },
      "outputs": [],
      "source": [
        "'cat' in ['dog','cat','mouse']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "'waseem' in ['Waseem','ahmed','tariq']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "name_list = ['Waseem','ahmed','tariq']\n",
        "'Waseem' in name_list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "\n",
        "\n",
        "name_list = ['Waseem','ahmed','tariq']\n",
        "\n",
        "lowercase_name_list = list(map(str.lower, name_list))\n",
        "print(type(lowercase_name_list))\n",
        "'waseem' in lowercase_name_list\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "name_subject_list = ['English', 'math','data_science'] \n",
        "'English' in name_subject_list\n",
        "lower_name_subject_name_list = list(map(str.lower, name_subject_list))\n",
        "'english' in lower_name_subject_name_list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "## Upper the subject list \n",
        "\n",
        "name_subject_list = ['ENGLISH', 'math','data_science']\n",
        "upper_name_subject_name_list = list(map(str.upper, name_subject_list))\n",
        "'ENGLISH' in name_subject_list"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "## Not in Reverse functions \n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "## Upper the subject list \n",
        "\n",
        "name_subject_list = ['ENGLISH', 'math','data_science']\n",
        "upper_name_subject_name_list = list(map(str.upper, name_subject_list))\n",
        "'ENGLISH' not in name_subject_list"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "E1q6-S1VaaMh"
      },
      "source": [
        "## not in returns True if a sequence with the specified value is not present in the object."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "056hdsDeaY46",
        "outputId": "50dde5c3-ef72-4a2b-a4d5-119ecf67465e"
      },
      "outputs": [],
      "source": [
        "'geese' not in ['dog','cat','mouse']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qPaAYG7Yz4JQ"
      },
      "source": [
        "## **Operators on Strings**\n",
        "\n",
        "we can also use these operators on strings"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UP2QwzaC0CoQ"
      },
      "source": [
        "The Addition sign (+) will concatenate a string"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qMSk0nrVwBcQ",
        "outputId": "93330eac-5de4-423e-ad9b-32cf0915fc7f"
      },
      "outputs": [],
      "source": [
        "sentence = 'Hello' + ' ' + 'World'\n",
        "\n",
        "print(sentence)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "sentence_1 = 'Hello' + ' ' + 'World' + ' ' + '!'\n",
        "sentence_1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "sentence_2 = 'Hello' + ' ' + 'Waseem' + ' ' + 'Hassan' + ' ' + 'Shaikh', '  + Sb'\n",
        "sentence_2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "k = 'hello'\n",
        "# break the line \n",
        "\n",
        "print(k * 5  + '!')\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "j = 'hello'\n",
        "\n",
        "print(j * 6 +  '!')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5yDNcxC20Tk_",
        "outputId": "18f2c0e6-e006-413b-9eef-ffa0508fca46"
      },
      "outputs": [],
      "source": [
        "k = 'Ha'\n",
        "print(k * 5 + '!')"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kIgLKiZd0li_"
      },
      "source": [
        "You can also use the double equal sign (==) to check if two strings are identical."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pv3sV-I60lJZ",
        "outputId": "f4aaf769-7c9d-442b-d9f0-9f626308849d"
      },
      "outputs": [],
      "source": [
        "'ABCD' == 'ABCE'"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Ssi6jW5vXjAw"
      },
      "source": [
        "##  > and < will check if one string has more characters than the other"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Udqs_Wi4XnBK",
        "outputId": "d8afa347-50e5-438d-c30b-8115a6d39613"
      },
      "outputs": [],
      "source": [
        "'1234567' > '12345'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "'abcdefgh' > 'abcdef'"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kPOCusZi08bY"
      },
      "source": [
        "The double equal sign is case sensitive"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "E06k_g3TjjED",
        "outputId": "f3b2459f-8680-4a45-d942-2531c6431f2a"
      },
      "outputs": [],
      "source": [
        "'ABC' == 'ABc'"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "'ABCDE' > \"ABCDEFG\""
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6cE0hLN1i4ur"
      },
      "source": []
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3",
      "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": "3.11.4"
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  "nbformat": 4,
  "nbformat_minor": 0
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