conditionals statements and loops/Control Structure If else statements (2).ipynb

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    "<h6><div style=\"font-family: Trebuchet MS; background-color: #1b191d; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\">🅶🆄 🆁🅰🅽🅽🅰 🅶🅾🆄🅳🅰--🅳🅰🆃🅰🆂🅲🅸🅴🅽🆃 👨‍💻</div> </h6>"
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    "<h1 style=\"font-family: Trebuchet MS; padding: 12px; font-size: 48px; color: #19AADE; text-align: center; line-height: 1.25;\"><b>🏬🔧<span style=\"color: #000000\"> Today Let's Discusss about what? Any Idea 🔫 </span></b><br><span style=\"color: #19AADE; font-size: 24px\"></span></h1>\n",
    "<hr>"
   ]
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   "source": [
    "# Control Structure"
   ]
  },
  {
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   "execution_count": null,
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   "source": [
    "Control --- Controlling the flow of execution in the program\n",
    "\n",
    "structure--- Nature of flow\n",
    "\n",
    "1. sequence control structure\n",
    "\n",
    "2. Selection/Condition control structure\n",
    "\n",
    "3. Loop/Iteration control structure"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1. A control structure (or flow of control) is a block of programming that analyses variables and chooses a direction in which to go based on given parameters.\n",
    "\n",
    "2. In simple sentence, a control structure is just a decision that the computer makes."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Control = Flow of Execution Instruction\n",
    "\n",
    "Structure = List of instrcutions= Programs = Task"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1.sequence\n",
    "\n",
    "2. Condition/Selection\n",
    "\n",
    "3. Iteration/looping"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# What are Conditional Statements in Python?"
   ]
  },
  {
   "cell_type": "raw",
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   "source": [
    "Conditional Statement in Python perform different computations or actions depending on whether a specific Boolean constraint evaluates to true or false. Conditional statements are handled by IF statements in Python."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python Conditions and If statements\n"
   ]
  },
  {
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   "source": [
    "# Comparison Operators¶"
   ]
  },
  {
   "cell_type": "raw",
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   "source": [
    "Comparison operations compare some value or operand and, based on a condition, they produce a Boolean. When comparing two values you can use these operators:\n",
    "\n",
    "equal: ==\n",
    "\n",
    "not equal: !=\n",
    "\n",
    "greater than: >\n",
    "\n",
    "less than: <\n",
    "\n",
    "greater than or equal to: >=\n",
    "\n",
    "less than or equal to: <="
   ]
  },
  {
   "cell_type": "raw",
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   "source": [
    "Python supports the usual logical conditions from mathematics:\n",
    "\n",
    "Equals: a == b\n",
    "Not Equals: a != b\n",
    "Less than: a < b\n",
    "Less than or equal to: a <= b\n",
    "Greater than: a > b\n",
    "Greater than or equal to: a >= b\n",
    "These conditions can be used in several ways, most commonly in \"if statements\" and loops.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Condition Equal\n",
    "\n",
    "a = 6\n",
    "a == 5"
   ]
  },
  {
   "cell_type": "raw",
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   "source": [
    "The result is False, as 5 does not equal to 6.\n",
    "\n",
    "Consider the following equality comparison operator i > 5. If the value of the left operand, in this case the variable i, is greater than the value of the right operand, in this case 5, then the statement is True. Otherwise, the statement is False. If i is equal to 6, because 6 is larger than 5, the output is True."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Greater than Sign\n",
    "\n",
    "i = 6\n",
    "i > 5\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Set i = 2. The statement is false as 2 is not greater than 5:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "# Greater than Sign\n",
    "\n",
    "i = 2\n",
    "i > 5"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Let's display some values for i in the figure. Set the values greater than 5 in green and the rest in red. The green region represents where the condition is True, the red where the statement is False. If the value of i is 2, we get False as the 2 falls in the red region. Similarly, if the value for i is 6 we get a True as the condition falls in the green region."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/Chapter%203/Images/CondsIneq.gif\" width=\"650\" />"
   ]
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  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "We can apply the same methods on strings. For example, use an equality operator on two different strings. As the strings are not equal, we get a False."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use Equality sign to compare the strings\n",
    "\n",
    "\"ACDC\" == \"Michael Jackson\""
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "If we use the inequality operator, the output is going to be True as the strings are not equal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Use Inequality sign to compare the strings\n",
    "\n",
    "\"ACDC\" != \"Michael Jackson\"\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "\n",
    "Inequality operation is also used to compare the letters/words/symbols according to the ASCII value of letters. The decimal value shown in the following table represents the order of the character:\n",
    "\n",
    "For example, the ASCII code for ! is 21, while the ASCII code for + is 43. Therefore + is larger than ! as 43 is greater than 21.Inequality operation is also used to compare the letters/words/symbols according to the ASCII value of letters. The decimal value shown in the following table represents the order of the character:\n",
    "\n",
    "Similarly, the value for A is 101, and the value for B is 102 therefore:\n",
    "\n",
    "Here we have used ord() function to convert a character to an integer (ASCII value). This function returns the Unicode code point of that character.\n",
    "\n",
    "Unicode is also an encoding technique that provides a unique number to a character. While ASCII only encodes 128 characters, the current Unicode has more than 100,000 characters from hundreds of scripts."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
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     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The ASCII value of 'p' is 112\n"
     ]
    }
   ],
   "source": [
    "# Program to find the ASCII value of the given character\n",
    "\n",
    "c = 'p'\n",
    "print(\"The ASCII value of '\" + c + \"' is\", ord(c))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'B'>'A'"
   ]
  },
  {
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   "execution_count": 10,
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    {
     "data": {
      "text/plain": [
       "66"
      ]
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     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "ord('B')"
   ]
  },
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       "65"
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   "source": [
    "ord('A')"
   ]
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   "source": [
    "<h3 style=\"font-family: Trebuchet MS; padding: 12px; font-size: 40px; color: #19AADE; text-align: center; line-height: 1.;\"><b><span style=\"color: #000000\"> What is Python If Statement </span> </b></h3>"
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   "source": [
    "Decision making is the most important aspect of almost all the programming languages. As the name implies, decision making allows us to run a particular block of code for a particular decision. Here, the decisions are made on the validity of the particular conditions. Condition checking is the backbone of decision making.\n",
    "\n",
    "In python, decision making is performed by the following statements."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1. There comes situations in real life when we need to make some decisions and based on these decisions, we decide what should we do next. \n",
    "\n",
    "2. Similar situations arise in programming also where we need to make some decisions and based on these decisions we will execute the next block of code. \n",
    "\n",
    "3. Decision-making statements in programming languages decide the direction of the flow of program execution. \n",
    "\n",
    "4. Python if Statement is used for decision-making operations. \n",
    "\n",
    "5. It contains a body of code which runs only when the condition given in the if statement is true. \n",
    "\n",
    "6. If the condition is false, then the optional else statement runs which contains some code for the else condition."
   ]
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   "source": [
    "Statement\tDescription\n",
    "\n",
    "1. If Statement\tThe if statement is used to test a specific condition. If the condition is true, a block of code (if-block) will be executed.\n",
    "\n",
    "\n",
    "2. If - else Statement\tThe if-else statement is similar to if statement except the fact that, it also provides the block of the code for the false case of the condition to be checked. If the condition provided in the if statement is false, then the else statement will be executed.\n",
    "\n",
    "3. Nested if Statement\tNested if statements enable us to use if ? else statement inside an outer if statement."
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: red; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\">Indentation in Python 🤔</div> "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1. Python relies on indentation (whitespace at the beginning of a line) to define scope in the code. Other programming languages often use curly-brackets for this purpose.\n",
    "\n",
    "2. For the ease of programming and to achieve simplicity, python doesn't allow the use of parentheses for the block level code. In Python, indentation is used to declare a block. If two statements are at the same indentation level, then they are the part of the same block.\n",
    "\n",
    "3. Generally, four spaces are given to indent the statements which are a typical amount of indentation in python.\n",
    "\n",
    "\n",
    "4. Indentation is the most used part of the python language since it declares the block of code. \n",
    "\n",
    "5. All the statements of one block are intended at the same level indentation. We will see how the actual indentation takes place in decision making and other stuff in python.\n",
    "\n"
   ]
  },
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   "cell_type": "markdown",
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   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: #176BA0;; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\">🅸🅵--🆂🆃🅰🆃🅴🅼🅴🅽🆃🧨💥</div> "
   ]
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  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "The if statement is used to test a particular condition and if the condition is true, it executes a block of code known as if-block.\n",
    "\n",
    "The condition of if statement can be any valid logical expression which can be either evaluated to true or false."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "The syntax of the if-statement is given below.\n",
    "if condition:\n",
    "   # Statements to execute if\n",
    "   # condition is true\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: #176BA0;; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\"> Flow Chart📈 </div> "
   ]
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "attachments": {
    "1.gif": {
     "image/gif": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![1.gif](attachment:1.gif)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](1.gif)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](2.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# python program to illustrate If statement\n",
    "\n",
    "i = 10\n",
    "\n",
    "if (i > 15):\n",
    "\tprint(\"10 is less than 15\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# python program to illustrate If statement\n",
    "\n",
    "i = 10\n",
    "\n",
    "if (i > 15):\n",
    "\tprint(\"10 is less than 15\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "enter the number?9\n"
     ]
    }
   ],
   "source": [
    "#Example 2\n",
    "num = int(input(\"enter the number?\"))  \n",
    "if num%2 == 0:  \n",
    "    print(\"Number is even\",num)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter a? 4\n",
      "Enter b? 6\n",
      "Enter c? 8\n",
      "c is largest\n"
     ]
    }
   ],
   "source": [
    "#Example 2 : Program to print the largest of the three numbers.\n",
    "a = int(input(\"Enter a? \"));  \n",
    "b = int(input(\"Enter b? \"));  \n",
    "c = int(input(\"Enter c? \"));  \n",
    "if a>b and a>c:  \n",
    "    print(\"a is largest\");  \n",
    "if b>a and b>c:  \n",
    "    print(\"b is largest\");  \n",
    "if c>a and c>b:  \n",
    "    print(\"c is largest\");  \n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "if condition:\n",
    "   statement1\n",
    "statement2\n",
    "\n",
    "# Here if the condition is true, if block \n",
    "# will consider only statement1 to be inside \n",
    "# its block."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I am Not in if\n"
     ]
    }
   ],
   "source": [
    "# python program to illustrate If statement\n",
    "\n",
    "i = 10\n",
    "\n",
    "if (i > 15):\n",
    "\tprint(\"10 is less than 15\")\n",
    "print(\"I am Not in if\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nagpur\n"
     ]
    }
   ],
   "source": [
    "a = 333\n",
    "b = 300\n",
    "if b > a:\n",
    "    print(\"b is greater than a\") # you will get an error\n",
    "    print(\"India\")\n",
    "print('Nagpur')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "The number is less than 20\n",
      "\n",
      "Kunal\n",
      "\n",
      "b\n",
      "India\n"
     ]
    }
   ],
   "source": [
    "some_num = 10\n",
    "if some_num < 20:\n",
    "    print()\n",
    "    print(\"The number is less than 20\")\n",
    "    print()\n",
    "    print(\"Kunal\")\n",
    "    print()\n",
    "    print('b')\n",
    "\n",
    "print(\"India\")\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: #176BA0;; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\"> 🅸🅵--🅴🅻🆂🅴--🆂🆃🅰🆃🅴🅼🅴🅽🆃 ➖📝</div> "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "1. The if statement alone tells us that if a condition is true it will execute a block of statements and if the condition is false it won’t. \n",
    "\n",
    "2. But what if we want to do something else if the condition is false. Here comes the else statement. \n",
    "\n",
    "3. We can use the else statement with if statement to execute a block of code when the condition is false. \n",
    "\n",
    "4. The if-else statement provides an else block combined with the if statement which is executed in the false case of the condition.\n",
    "\n",
    "5. If the condition is true, then the if-block is executed. Otherwise, the else-block is executed."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "#The syntax of the if-else statement is given below.\n",
    "\n",
    "\n",
    "if condition:  \n",
    "    #block of statements   \n",
    "else:   \n",
    "    #another block of statements (else-block)   \n",
    "    \n",
    "    \n",
    "    if (condition):\n",
    "    # Executes this block if\n",
    "    # condition is true\n",
    "else:\n",
    "    # Executes this block if\n",
    "    # condition is false\n",
    "    \n",
    "    \n",
    "    or\n",
    "\n",
    "if condition:  \n",
    "    #block of statements   \n",
    "else:   \n",
    "    #another block of statements (else-block)   "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: #176BA0;; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\"> Flow Chart📈 </div> "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](3.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example 1 : Program to check whether a person is eligible to vote or not.¶"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter your age? 4\n",
      "Sorry! you have to wait !!\n"
     ]
    }
   ],
   "source": [
    "#Example 1 : Program to check whether a person is eligible to vote or not.\n",
    "age = int (input(\"Enter your age? \"))  \n",
    "if age>=18:  \n",
    "    print(\"You are eligible to vote !!\") \n",
    "else:  \n",
    "    print(\"Sorry! you have to wait !!\") "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Example 2: Program to check whether a number is even or not.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "enter the number?66\n",
      "Number is even...\n"
     ]
    }
   ],
   "source": [
    "num = int(input(\"enter the number?\"))  \n",
    "\n",
    "if num%2 == 0:  \n",
    "    print(\"Number is even...\")  \n",
    "else:  \n",
    "    print(\"Number is odd...\")  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i is greater than 15\n",
      "i'm in else Block\n",
      "i'm not in if and not in else Block\n"
     ]
    }
   ],
   "source": [
    "# python program to illustrate If else statement\n",
    "#!/usr/bin/python\n",
    "\n",
    "i = 20\n",
    "if (i < 15):\n",
    "\tprint(\"i is smaller than 15\")\n",
    "\tprint(\"i'm in if Block\")\n",
    "else:\n",
    "\tprint(\"i is greater than 15\")\n",
    "\tprint(\"i'm in else Block\")\n",
    "print(\"i'm not in if and not in else Block\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: #176BA0;; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\">  🅴🅻🅸🅵--🆂🆃🅰🆃🅴🅼🅴🅽🆃</div> "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Elif\n",
    "The elif keyword is pythons way of saying \"if the previous conditions were not true, then try this condition\"."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "The elif statement enables us to check multiple conditions and execute the specific block of statements depending upon the true condition among them. We can have any number of elif statements in our program depending upon our need. However, using elif is optional.\n",
    "\n",
    "The elif statement works like an if-else-if ladder statement in C. It must be succeeded by an if statement.\n",
    "\n",
    "The syntax of the elif statement is given below."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "if expression 1:   \n",
    "    # block of statements   \n",
    "  \n",
    "elif expression 2:   \n",
    "    # block of statements   \n",
    "  \n",
    "elif expression 3:   \n",
    "    # block of statements   \n",
    "  \n",
    "else:   \n",
    "    # block of statements  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: #176BA0;; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\"> Flow Chart📈 </div> "
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": 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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](4.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    ">90  -- a+\n",
    "\n",
    "75-90 -- a\n",
    "\n",
    "60-75-- b+\n",
    "50-60 b\n",
    "\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter the number?50\n",
      "number is equal to 50\n"
     ]
    }
   ],
   "source": [
    "#Example 1\n",
    "number = int(input(\"Enter the number?\"))  \n",
    "if number==10:  \n",
    "    print(\"number is equals to 10\")  \n",
    "elif number==50:  \n",
    "    print(\"number is equal to 50\");  \n",
    "elif number==100:  \n",
    "    print(\"number is equal to 100\");  \n",
    "else:  \n",
    "    print(\"number is not equal to 10, 50 or 100\");  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Enter the marks? 5\n",
      "Sorry you are fail ?\n"
     ]
    }
   ],
   "source": [
    "#Example 2\n",
    "marks = int(input(\"Enter the marks? \"))  \n",
    "if marks > 85 and marks <= 100:  \n",
    "   print(\"Congrats ! you scored grade A ...\")  \n",
    "elif marks > 60 and marks <= 85:  \n",
    "   print(\"You scored grade B + ...\")  \n",
    "elif marks > 40 and marks <= 60:  \n",
    "   print(\"You scored grade B ...\")  \n",
    "elif (marks > 30 and marks <= 40):  \n",
    "   print(\"You scored grade C ...\")  \n",
    "else:  \n",
    "   print(\"Sorry you are fail ?\")  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a and b are equal\n"
     ]
    }
   ],
   "source": [
    "a = 33\n",
    "b = 33\n",
    "if b > a:\n",
    "  print(\"b is greater than a\")\n",
    "elif a == b:\n",
    "  print(\"a and b are equal\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Else\n",
    "The else keyword catches anything which isn't caught by the preceding conditions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a is greater than b\n"
     ]
    }
   ],
   "source": [
    "a = 200\n",
    "b = 33\n",
    "if b > a:\n",
    "  print(\"b is greater than a\")\n",
    "elif a == b:\n",
    "  print(\"a and b are equal\")\n",
    "else:\n",
    "  print(\"a is greater than b\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The number is between 0 and 50\n"
     ]
    }
   ],
   "source": [
    "some_num = 34\n",
    "if some_num >= 0 and some_num < 50:\n",
    "    print(\"The number is between 0 and 50\")\n",
    "elif some_num >= 50 and some_num < 100:\n",
    "    print(\"The number is between 50 and 100\")\n",
    "elif some_num >= 100 and some_num < 200:\n",
    "    print(\"The number is between 100 and 200\")\n",
    "elif some_num >= 200 and some_num < 300:\n",
    "    print(\"The number is between 200 and 300\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: #176BA0;; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\">  🅽🅴🆂🆃🅴🅳--🅸🅵--🆂🆃🅰🆃🅴🅼🅴🅽🆃</div> "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "A nested if is an if statement that is the target of another if statement. Nested if statements mean an if statement inside another if statement. Yes, Python allows us to nest if statements within if statements. i.e, we can place an if statement inside another if statement."
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Syntax: \n",
    "\n",
    "if (condition1):\n",
    "   # Executes when condition1 is true\n",
    "   if (condition2): \n",
    "      # Executes when condition2 is true\n",
    "   # if Block is end here\n",
    "# if Block is end here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Above ten,\n",
      "but not above 20.\n"
     ]
    }
   ],
   "source": [
    "x = 15\n",
    "\n",
    "if x > 10:\n",
    "  print(\"Above ten,\")\n",
    "  if x > 20:\n",
    "    print(\"and also above 20!\")\n",
    "  else:\n",
    "    print(\"but not above 20.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "i = 13\n",
    "if (i == 10): \n",
    "    #  First if statement \n",
    "    if (i < 15): \n",
    "        print (\"i is smaller than 15\") \n",
    "    # Nested - if statement \n",
    "    # Will only be executed if statement above \n",
    "    # it is true \n",
    "    if (i < 12): \n",
    "        print (\"i is smaller than 12 too\") \n",
    "    else: \n",
    "        print (\"i is greater than 15\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i is smaller than 15\n",
      "i is smaller than 12 too\n"
     ]
    }
   ],
   "source": [
    "# python program to illustrate nested If statement\n",
    "#!/usr/bin/python\n",
    "i = 10\n",
    "if (i == 10):\n",
    "\n",
    "\t# First if statement\n",
    "\tif (i < 15):\n",
    "\t\tprint(\"i is smaller than 15\")\n",
    "\t\t\n",
    "\t# Nested - if statement\n",
    "\t# Will only be executed if statement above\n",
    "\t# it is true\n",
    "\tif (i < 12):\n",
    "\t\tprint(\"i is smaller than 12 too\")\n",
    "\telse:\n",
    "\t\tprint(\"i is greater than 15\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examples"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# if Statement\n",
    "# Next to girl in exam hall "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hold the fort, mama! Destiny has paired me with a girl. It's like having a study superhero by my side. Whenever I'm in doubt, I'll just glance over, and she'll unleash her super intellect!\n"
     ]
    }
   ],
   "source": [
    "# Exam hall scenario with humor\n",
    "sitting_next_to_girl = True\n",
    "\n",
    "if sitting_next_to_girl:\n",
    "    print(\"Hold the fort, mama! Destiny has paired me with a girl. It's like having a study superhero by my side. Whenever I'm in doubt, I'll just glance over, and she'll unleash her super intellect!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# If-Else Statement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hold on, mama! Destiny has placed me next to a girl. It's like having a personal 'answer sheet whisperer.' If in doubt, I'll just follow her lead. Teamwork makes the dream work!\n"
     ]
    }
   ],
   "source": [
    "# Exam hall scenario with humor\n",
    "sitting_next_to_girl = True\n",
    "\n",
    "if sitting_next_to_girl:\n",
    "    print(\"Hold on, mama! Destiny has placed me next to a girl. It's like having a personal 'answer sheet whisperer.' If in doubt, I'll just follow her lead. Teamwork makes the dream work!\")\n",
    "else:\n",
    "    print(\"No girl-next-to-me excitement today. But no worries. I'm a lone wolf in the exam wilderness. Just me, my thoughts, and the constant battle against the urge to doodle in the margins.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Oh, mama mia! Destiny's playing matchmaker in the exam hall. I'm sitting next to a girl, and it feels like we're co-piloting the spaceship of knowledge. Buckle up, it's an intergalactic exam adventure!\n"
     ]
    }
   ],
   "source": [
    "# Exam hall scenario with humor\n",
    "sitting_next_to_girl = True\n",
    "\n",
    "if sitting_next_to_girl:\n",
    "    print(\"Oh, mama mia! Destiny's playing matchmaker in the exam hall. I'm sitting next to a girl, and it feels like we're co-piloting the spaceship of knowledge. Buckle up, it's an intergalactic exam adventure!\")\n",
    "else:\n",
    "    print(\"No girl-next-to-me blockbuster today. But fear not, I'm the lone explorer navigating the vast sea of exam questions. It's like a solo mission to the academic moon.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Elif Statement\n",
    "# Pickeupline Example"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "user_input = input(\"What's the occasion? (e.g., date, party, casual conversation) \")\n",
    "\n",
    "if \"date\" in user_input.lower():\n",
    "    print(\"Are you a magician? Because whenever I look at you, everyone else disappears.\")\n",
    "elif \"party\" in user_input.lower():\n",
    "    print(\"Do you have a sunburn, or are you always this hot?\")\n",
    "elif \"casual\" in user_input.lower():\n",
    "    print(\"Are you a camera? Because every time I see you, I smile.\")\n",
    "elif \"work\" in user_input.lower():\n",
    "    print(\"Are you a project manager? Because you've got everything scheduled in my heart.\")\n",
    "elif \"travel\" in user_input.lower():\n",
    "    print(\"Are you a passport? Because I want to take you everywhere with me.\")\n",
    "elif \"gym\" in user_input.lower():\n",
    "    print(\"Are you a squat? Because you've got my heart doing reps.\")\n",
    "elif \"bookstore\" in user_input.lower():\n",
    "    print(\"Are you a bestseller? Because you've written yourself into my story.\")\n",
    "elif \"beach\" in user_input.lower():\n",
    "    print(\"Are you a seashell? Because I'd love to pick you up on the beach.\")\n",
    "elif \"cooking\" in user_input.lower():\n",
    "    print(\"Are you a chef? Because you've added spice to my life.\")\n",
    "elif \"gardening\" in user_input.lower():\n",
    "    print(\"Are you a flower? Because you've blossomed in my heart.\")\n",
    "else:\n",
    "    print(\"I'm not sure about the occasion, but here's a classic: Are you a parking ticket? Because you've got 'FINE' written all over you.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Nested If statement\n",
    "# How to impress Girl "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Step 1: Dress well and maintain personal hygiene.\n",
      "Step 2: Engage in interesting and meaningful conversations.\n",
      "Step 3: Make her laugh with your sense of humor.\n",
      "Congratulations! You've successfully impressed her!\n"
     ]
    }
   ],
   "source": [
    "looks_good = True\n",
    "good_conversation = True\n",
    "sense_of_humor = True\n",
    "\n",
    "if looks_good:\n",
    "    print(\"Step 1: Dress well and maintain personal hygiene.\")\n",
    "\n",
    "    if good_conversation:\n",
    "        print(\"Step 2: Engage in interesting and meaningful conversations.\")\n",
    "        \n",
    "        if sense_of_humor:\n",
    "            print(\"Step 3: Make her laugh with your sense of humor.\")\n",
    "            print(\"Congratulations! You've successfully impressed her!\")\n",
    "        else:\n",
    "            print(\"Work on adding a touch of humor to your conversations.\")\n",
    "    else:\n",
    "        print(\"Improve your conversation skills. Ask open-ended questions and actively listen.\")\n",
    "else:\n",
    "    print(\"Take care of your appearance. First impressions matter.\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h2><div style=\"font-family: Trebuchet MS; background-color: #176BA0;; color: #FFFFFF; padding: 12px; font-size: 35px; line-height: 1.5;text-align: center; line-height: 1.;\"> 🅿🅰🆂🆂--🆂🆃🅰🆃🅴🅼🅴🅽🆃</div> "
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "\n",
    "if statements cannot be empty, but if you for some reason have an if statement with no content, put in the pass statement to avoid getting an error."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Example\n",
    "a = 33\n",
    "b = 200\n",
    "\n",
    "if b > a:\n",
    "  pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>🆂🅷🅾🆁🆃--🅷🅰🅽🅳--🅸🅵--🆂🆃🅰🆃🅴🅼🅴🅽🆃</h1>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you have only one statement to execute, you can put it on the same line as the if statement.\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Whenever there is only a single statement to be executed inside the if block then shorthand if can be used. The statement can be put on the same line as the if statement. \n",
    "\n",
    "Syntax: \n",
    "\n",
    "if condition: statement"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i is less than 15\n"
     ]
    }
   ],
   "source": [
    "# Python program to illustrate short hand if\n",
    "i = 10\n",
    "if i < 15: \n",
    "    print(\"i is less than 15\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a is greater than b\n"
     ]
    }
   ],
   "source": [
    "a=15\n",
    "b=13\n",
    "#Example: One line if statement:\n",
    "\n",
    "if a > b: print(\"a is greater than b\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h1>🆂🅷🅾🆁🆃....🅷🅰🅽🅳...🅸🅵.....🅴🅻🆂🅴......🆂🆃🅰🆃🅴🅼🅴🅽🆃</h1>"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "If you have only one statement to execute, one for if, and one for else, you can put it all on the same line:\n",
    "\n"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "Short Hand if-else statement\n",
    "This can be used to write the if-else statements in a single line where there is only one statement to be executed in both if and else block. \n",
    "\n",
    "Syntax:\n",
    "\n",
    "statement_when_True if condition else statement_when_False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "# Python program to illustrate short hand if-else\n",
    "i = 10\n",
    "print(True) if i < 15 else print(False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "B\n"
     ]
    }
   ],
   "source": [
    "#Example: One line if else statement:\n",
    "\n",
    "a = 2\n",
    "b = 330\n",
    "print(\"A\") if a > b else print(\"B\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This technique is known as Ternary Operators, or Conditional Expressions.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "=\n"
     ]
    }
   ],
   "source": [
    "#You can also have multiple else statements on the same line:\n",
    "\n",
    "#Example: One line if else statement, with 3 conditions:\n",
    "\n",
    "a = 330\n",
    "b = 330\n",
    "print(\"A\") if a > b else print(\"=\") if a == b else print(\"B\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Logical operators¶"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sometimes you want to check more than one condition at once. For example, you might want to check if one condition and another condition is **True**. Logical operators allow you to combine or modify conditions.\n",
    "<ul>\n",
    "    <li><code>and</code></li>\n",
    "    <li><code>or</code></li>\n",
    "    <li><code>not</code></li>\n",
    "</ul>\n",
    "\n",
    "These operators are summarized for two variables using the following truth tables:  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"https://s3-api.us-geo.objectstorage.softlayer.net/cf-courses-data/CognitiveClass/PY0101EN/Chapter%203/Images/CondsTable.png\" width=\"650\" />"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# And\n",
    "The and keyword is a logical operator, and is used to combine conditional statements:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Both conditions are True\n"
     ]
    }
   ],
   "source": [
    "#Example: Test if a is greater than b, AND if c is greater than a:\n",
    "\n",
    "a = 200\n",
    "b = 33\n",
    "c = 500\n",
    "if a > b and c > a:\n",
    "  print(\"Both conditions are True\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Album year was in between 1980 and 1989\n",
      "\n",
      "Do Stuff..\n"
     ]
    }
   ],
   "source": [
    "# Condition statement example\n",
    "\n",
    "album_year = 1980\n",
    "\n",
    "if(album_year > 1979) and (album_year < 1990):\n",
    "    print (\"Album year was in between 1980 and 1989\")\n",
    "    \n",
    "print(\"\")\n",
    "print(\"Do Stuff..\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Or\n",
    "The or keyword is a logical operator, and is used to combine conditional statements:\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "At least one of the conditions is True\n"
     ]
    }
   ],
   "source": [
    "\n",
    "#Example: Test if a is greater than b, OR if a is greater than c:\n",
    "\n",
    "a = 200\n",
    "b = 33\n",
    "c = 500\n",
    "if a > b or a > c:\n",
    "  print(\"At least one of the conditions is True\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Album was not made in the 1980's\n"
     ]
    }
   ],
   "source": [
    "# Condition statement example\n",
    "\n",
    "album_year = 1990\n",
    "\n",
    "if(album_year < 1980) or (album_year > 1989):\n",
    "    print (\"Album was not made in the 1980's\")\n",
    "else:\n",
    "    print(\"The Album was made in the 1980's \")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# not operations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Album year is not 1984\n"
     ]
    }
   ],
   "source": [
    "# Condition statement example\n",
    "\n",
    "album_year = 1983\n",
    "\n",
    "if not (album_year == '1984'):\n",
    "    print (\"Album year is not 1984\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Boolean Operation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "active = True\n",
    "if not active:\n",
    "    print('This account is not active')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "if some_num > 50 or not active:\n",
    "    print('One of these conditions has to be true')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# If statements with lists and dictionaries¶"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "student_list = ['Ayaz', 'Athira', 'Deb', 'Priya']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'India' in student_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "if 'India' in student_list:\n",
    "    print('Yes he is a student at this school')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yes she is a student in this school\n"
     ]
    }
   ],
   "source": [
    "if 'Deb' in student_list:\n",
    "    print('Yes she is a student in this school')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# If Statement from Dictionary\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "math_scores = {\n",
    "    \"Ram\": 97, \n",
    "    \"Kumar\": 35,\n",
    "    \"Kishan\": 67,\n",
    "    \"Natasha\": 73\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'Ram' in math_scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Yes I do have scores for Ram\n"
     ]
    }
   ],
   "source": [
    "if 'Ram' in math_scores:\n",
    "    print('Yes I do have scores for Ram')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "if 'Ayoub' in math_scores:\n",
    "    print('Yes I do have scores for Ayoub')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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