Created on Cognitive Class Labs

PY0101EN-1.1_notebook_quizz_v2.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3 align=center>Hello World</h3>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's say Hello to the world with a <code>PRINT</code> statement. E.g. <code>print(\"Hello World\")</code>. Why not give it a try put in a print statement in the cell bellow. Don't forget to do <kbd>shift</kdb>+<kbd>enter</kbd> to run the cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello World\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello World\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3 align=center>Say Hello World on two lines</h3> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's print Hello and World on two separate lines. Hint: \\n in the middle of the string acts as a new line character. E.g. <code>print(\"line 1\\nline 2\")</code>. Let's try it now. Type in a print statement in the cell bellow. Don't forget to do <kbd>shift</kdb>+<kbd>enter</kbd> to run the cell:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Hello\n",
      "World\n"
     ]
    }
   ],
   "source": [
    "print(\"Hello\\nWorld\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<h3 align=center>Comments are key to good coding</h3> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In python, comments are created by putting a hash mark <code>#</code> in front of the text of the comment. E.g. <code># this is a comment</code>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [],
   "source": [
    "#This is a comment"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<hr>\n",
    "<small>Copyright &copy; 2018 IBM Cognitive Class. This notebook and its source code are released under the terms of the [MIT License](https://cognitiveclass.ai/mit-license/).</small>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python",
   "language": "python",
   "name": "conda-env-python-py"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}