Getting Started with Python.ipynb

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   "source": [
    "________________________________________________________________________________________________________________________\n",
    "\n",
    "\n",
    "* Yuvraj Sutar \n",
    "* yuvrajsutar009@gmail.com\n",
    "_ _________________________________________________________________________________________________________________________\n",
    "_  _________________________________________________________________________________________________________________________"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Python Quickstart:\n",
    "- steps to write program\n",
    "- 1- Start Anaconda Prompt\n",
    "- 2- Open Jupyter Notebook by typing jupyter notebook in anaconda prompt\n",
    "- 3- Click on New button at right side corner\n",
    "- 4- Start writing on Notebook Dashboard\n",
    "- Let's write our first Python file, called helloworld.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, World!\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello, World!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Variable Declaration\n",
    "- Python uses a variable to store the information.\n",
    "- Variables can be declared by any name or even alphabets like a, aa, abc, etc.\n",
    "- Variables can be re-declared even after you have declared them for once\n",
    "- The equal sign (=) is used to assign values to variables.\n",
    "- The operand to the left of the = operator is the name of the variable \n",
    "- The operand to the right of the = operator is the value stored in the variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "x=\"AIS\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AIS\n"
     ]
    }
   ],
   "source": [
    "print(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    }
   ],
   "source": [
    "my_name=5\n",
    "print(my_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "_16446465454656=\"AIS\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "invalid syntax (Temp/ipykernel_2548/2954125549.py, line 2)",
     "output_type": "error",
     "traceback": [
      "\u001b[1;36m  File \u001b[1;32m\"C:\\Users\\Yuvraj\\AppData\\Local\\Temp/ipykernel_2548/2954125549.py\"\u001b[1;36m, line \u001b[1;32m2\u001b[0m\n\u001b[1;33m    1abc__xyz = 5\u001b[0m\n\u001b[1;37m     ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
     ]
    }
   ],
   "source": [
    "#Creating Variable\n",
    "1abc__xyz = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    }
   ],
   "source": [
    "print(_1215AIS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "AI\n"
     ]
    }
   ],
   "source": [
    "_56465465654646464_5y='AI'\n",
    "print(_56465465654646464_5y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Rules for Variable Names \n",
    "- A variable name must start with a letter or the underscore character\n",
    "- A variable name cannot start with a number\n",
    "- A variable name can only contain alpha-numeric characters and underscores (A-z, 0-9, and _ )\n",
    "- Variable names are case-sensitive (age, Age and AGE are three different variables)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Declare a variable & initialise it\n",
    "c='arya'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'arya'"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Re-declaring the variable \n",
    "c=2892"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2892"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Multiple Assignment\n",
    "a = b = c = 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1\n"
     ]
    }
   ],
   "source": [
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Comments:\n",
    "- Python has commenting capability for the purpose of in-code documentation.\n",
    "\n",
    "- Comments start with a #, and Python will render the rest of the line as a comment:\n",
    "\n",
    "e.g."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello, World!\n"
     ]
    }
   ],
   "source": [
    "#This is a comment.\n",
    "print(\"Hello, World!\") #my code"
   ]
  },
  {
   "attachments": {
    "Python%20Keywords.png": {
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Keywords in Python\n",
    "- Keywords are the reserved words in Python. \n",
    "- We cannot use a keyword as variable name, function name or any other identifier.\n",
    "![Python%20Keywords.png](attachment:Python%20Keywords.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['False', 'None', 'True', 'and', 'as', 'assert', 'async', 'await', 'break', 'class', 'continue', 'def', 'del', 'elif', 'else', 'except', 'finally', 'for', 'from', 'global', 'if', 'import', 'in', 'is', 'lambda', 'nonlocal', 'not', 'or', 'pass', 'raise', 'return', 'try', 'while', 'with', 'yield']\n"
     ]
    }
   ],
   "source": [
    "import keyword\n",
    "print(keyword.kwlist)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "* Yuvraj Sutar \n",
    "* yuvrajsutar009@gmail.com"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "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": "3.9.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}