Python Basics.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Python Basics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "30\n"
     ]
    }
   ],
   "source": [
    "a = 10\n",
    "b = 20\n",
    "\n",
    "print(a + b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "50\n"
     ]
    }
   ],
   "source": [
    "a = 50\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'int'>\n"
     ]
    }
   ],
   "source": [
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'str'>\n"
     ]
    }
   ],
   "source": [
    "a = \"hello\"\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'float'>\n"
     ]
    }
   ],
   "source": [
    "a = 5.5\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prateek\n",
      "Hello Prateek\n"
     ]
    }
   ],
   "source": [
    "name = input()\n",
    "print(\"Hello \"+name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10\n",
      "10\n",
      "<class 'int'>\n"
     ]
    }
   ],
   "source": [
    "number = int(input()) #Typecasting\n",
    "print(number)\n",
    "print(type(number))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i\n"
     ]
    }
   ],
   "source": [
    "sentence = \"This is a Machine Learning class\"\n",
    "print(sentence[2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'his i'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentence[1:6] #slicing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ass'"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentence[-3:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'s'"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sentence[-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_sent = sentence.split()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['This', 'is', 'a', 'Machine', 'Learning', 'class']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_sent"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n"
     ]
    }
   ],
   "source": [
    "print(type(new_sent))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Machine'"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_sent[3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'class'"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_sent[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['This', 'is', 'a', 'Machine', 'Learning', 'class']\n",
      "This+is+a+Machine+Learning+class\n"
     ]
    }
   ],
   "source": [
    "s = '+'.join(new_sent)\n",
    "print(new_sent)\n",
    "print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "s2 = 'hi'.join([\"1\",\"2\",\"3\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1hi2hi3\n"
     ]
    }
   ],
   "source": [
    "print(s2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'hello5'"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"hello\" + str(5) #Typecasting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'hellohellohellohellohello'"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\"hello\"*5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Read a List of Numbers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3\n",
      "['1', '2', '3']\n",
      "<class 'list'>\n"
     ]
    }
   ],
   "source": [
    "number_list = input().split()\n",
    "print(number_list)\n",
    "print(type(number_list))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'list'>\n"
     ]
    }
   ],
   "source": [
    "a = [1,2,3]\n",
    "print(type(a))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = [1,2,3,\"Hello\",[3,4,5]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3, 4, 5]\n"
     ]
    }
   ],
   "source": [
    "print(b[-1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello\n"
     ]
    }
   ],
   "source": [
    "print(b[-2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "2\n",
      "3\n",
      "14\n",
      "5\n",
      "6\n"
     ]
    }
   ],
   "source": [
    "s1 = [1,2,3,14,5]\n",
    "s1.append(6)\n",
    "\n",
    "for x in s1:\n",
    "    print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3 4\n",
      "['1', '2', '3', '4']\n",
      "[1, 2, 3, 4]\n"
     ]
    }
   ],
   "source": [
    "number_list = input().split()\n",
    "print(number_list)\n",
    "\n",
    "l = []\n",
    "for n in number_list:\n",
    "    l.append(int(n))\n",
    "\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 4, 9, 16]\n"
     ]
    }
   ],
   "source": [
    "#List Comprehension\n",
    "squares = [i**2 for i in l]\n",
    "print(squares)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 2 3 4 5\n",
      "[1, 4, 9, 16, 25]\n"
     ]
    }
   ],
   "source": [
    "l = [int(i)**2 for i in input().split()]\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1, 4, 9, 16, 25],[1, 4, 9, 16, 25]+a+b?Hi\n"
     ]
    }
   ],
   "source": [
    "print(l,end=',')\n",
    "print(l,\"a\",\"b\",sep=\"+\",end=\"?\")\n",
    "print(\"Hi\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "11\n",
      "9\n",
      "7\n"
     ]
    }
   ],
   "source": [
    "for i in range(11,5,-2): #start #end+1 #jump\n",
    "    print(i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rWo\n"
     ]
    }
   ],
   "source": [
    "s = \"Hello World\"\n",
    "print(s[-3:2:-2])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Read N and Print the Star Pattern"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n",
      "    *\n",
      "   ***\n",
      "  *****\n",
      " *******\n",
      "*********\n"
     ]
    }
   ],
   "source": [
    "n = int(input())\n",
    "for i in range(1,n+1):\n",
    "    print(\" \"*(n-i),end=\"\")\n",
    "    print(\"*\"*(2*i-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n",
      "4\n",
      "9\n",
      "16\n",
      "25\n"
     ]
    }
   ],
   "source": [
    "i = 1\n",
    "while i<=5:\n",
    "    print(i*i)\n",
    "    i = i+1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [],
   "source": [
    "lang = \"C++\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "its C++\n"
     ]
    }
   ],
   "source": [
    "if lang=='python':\n",
    "    print(\"Python\")\n",
    "elif lang==\"C++\":\n",
    "    print(\"its C++\")\n",
    "else:\n",
    "    print(\"whatever!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 126,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fun(a,b=10,*X,**kwargs):\n",
    "    print(\"Having fun!\")\n",
    "    print(X)\n",
    "    print(a,b)\n",
    "    s = a + b + sum(X)\n",
    "    print(kwargs)\n",
    "    print(s)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Having fun!\n",
      "(30, 40, 50)\n",
      "10 20\n",
      "{'fruit': 'Mango', 'shake': 'Oreo'}\n",
      "150\n"
     ]
    }
   ],
   "source": [
    "fun(10,20,30,40,50,fruit=\"Mango\",shake=\"Oreo\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Structures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 129,
   "metadata": {},
   "outputs": [],
   "source": [
    "# List\n",
    "# Tuple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'tuple'>\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 134,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = (10,20,30,40,\"Hello\")\n",
    "print(type(a))\n",
    "a[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[10, 20, 30, 40, 'Hello']\n",
      "[100, 20, 30, 40, 'Hello']\n"
     ]
    }
   ],
   "source": [
    "b = list(a)\n",
    "print(b)\n",
    "b[0] =100\n",
    "print(b)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 136,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dictionary\n",
    "\n",
    "d = {\n",
    "    \"pavbhaji\":100,\n",
    "    \"golgappa\":50,\n",
    "    \"idlisambhar\":[40,80],\n",
    "    \"maggi\":{\"regular\":20,\"cheese\":30}\n",
    "}\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['pavbhaji', 'golgappa', 'idlisambhar', 'maggi']"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(d.keys())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[100, 50, [40, 80], {'regular': 20, 'cheese': 30}]"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "list(d.values())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "50"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['golgappa']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "20"
      ]
     },
     "execution_count": 141,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "d['maggi']['regular']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "not present\n"
     ]
    }
   ],
   "source": [
    "if d.get('Tea') is None:\n",
    "    print(\"not present\")\n",
    "else:\n",
    "    print(d['Tea'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('pavbhaji', 100)\n",
      "('golgappa', 50)\n",
      "('idlisambhar', [40, 80])\n",
      "('maggi', {'regular': 20, 'cheese': 30})\n"
     ]
    }
   ],
   "source": [
    "for item in d.items():\n",
    "    print(item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "metadata": {},
   "outputs": [],
   "source": [
    "d.update?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = list([1,2,3])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 150,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = tuple(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1, 2, 3)\n"
     ]
    }
   ],
   "source": [
    "print(t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
   "metadata": {},
   "outputs": [],
   "source": [
    "countries = tuple([\"India\",\"US\",\"South Africa\"])\n",
    "capitals = [\"Delhi\",\"Washington\",\"Cape Town\"]\n",
    "\n",
    "d = dict(zip(countries,capitals))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'India': 'Delhi', 'US': 'Washington', 'South Africa': 'Cape Town'}\n"
     ]
    }
   ],
   "source": [
    "print(d)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Class and Object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Student:\n",
    "    \n",
    "    class_marks = []\n",
    "    def __init__(self,name,school):\n",
    "        self.name = name\n",
    "        self.school = school\n",
    "        self.marks = []\n",
    "        \n",
    "    def show(self):\n",
    "        print(self.name,self.school)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = Student(\"Prateek\",\"DTU\")\n",
    "s2 = Student(\"Sharad\",\"DCE\")\n",
    "s.marks.append(10)\n",
    "s2.marks.append(20)\n",
    "s.class_marks.append(10)\n",
    "s2.class_marks.append(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prateek DTU\n",
      "Sharad DCE\n",
      "[10, 20]\n",
      "[10, 20]\n",
      "[10]\n",
      "[20]\n"
     ]
    }
   ],
   "source": [
    "s.show()\n",
    "s2.show()\n",
    "print(s.class_marks)\n",
    "print(s2.class_marks)\n",
    "print(s.marks)\n",
    "print(s2.marks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [],
   "source": [
    "import random"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "random.randint(10,20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "metadata": {},
   "outputs": [],
   "source": [
    "random.seed(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n"
     ]
    }
   ],
   "source": [
    "l = [i for i in range(10)]\n",
    "print(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [],
   "source": [
    "random.shuffle(l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[3, 2, 4, 6, 0, 1, 9, 5, 7, 8]\n"
     ]
    }
   ],
   "source": [
    "print(l)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Numpy"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```pip install numpy```  for Mathematical Computations  \n",
    "```pip install pandas``` for Data preprocessing    \n",
    "```pip install matplotlib``` for Graph Plotting  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: numpy in c:\\python\\lib\\site-packages (1.16.3)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "You are using pip version 19.0.3, however version 19.1.1 is available.\n",
      "You should consider upgrading via the 'python -m pip install --upgrade pip' command.\n"
     ]
    }
   ],
   "source": [
    "!pip install numpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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