day1Lecture.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <br><br><span style=\"color:rebeccapurple\">Python Fundamentals Bootcamp - Day 1</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br>This is a Jupyter Notebook. \n",
    "To run a gray code cell, click in the cell and either click on the \"play\" arrow, or type shift+enter (or shift+return on a Mac)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>When you type in the gray code cell and hit shift+enter, you **run** the code.\n",
    "<br>If something gets printed out to the screen after you run the code, we say it is **returned**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Text cells like this one don't contain code. They are written in a language called Markdown. If you accidentally double click in a markdown cell, it won't cause any problems. Go ahead and double click on this text. Then you can run the cell, just like you would with a code cell by hitting shift+enter, to return it to looking like nice formatted text."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Everyone's notebook might look a little different, depending on if you running it locally through Jupyter Lab, on Google Colab, on a Mac or a PC, or in different browsers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>As we work, you might feel like you need to reset your entire notebook. I don't expect you to remember this, but I'm putting this info here in case you need it later:\n",
    "- In Jupyter Lab: Click on Kernel in the menu and choose Restart Kernel and Clear Outputs of All Cells.\n",
    "- In Google Colab: Click on Runtime and choose Restart session. Then click on Edit and choose Clear all outputs."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>*If you are working on Google Colab:* \n",
    "- Some of the groups of cells may automatically be **collapsed**, requiring you to **expand** them as you go. If you want, you can click on the View menu and choose Expand sections to expand the entire notebook.\n",
    "\n",
    "<br>*AI coding assistants*\n",
    "<br>Both Colab and Jupyter Lab now give you the option to generate code with AI. You are welcome to try it out during breaks, but I think you are here to learn how to code, so you probably don't want to cheat on today's exercises. But your learning is in your hands!\n",
    "- If you want to hide the Google Colab AI suggestions for now: click on the gear icon on the top right to change your Settings and choose the AI Assistance sub menu on the left. Check the box to Hide the GAI features."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>Before we start coding, here are some things you should know that will make Python easier to learn..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">Python is a language."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Not a software program.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### How do we talk to our computer in Python?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- **Interactive programming**: through a **shell** (interpreter, console) one line at a time\n",
    "- **Batch programming**: running a whole **script** (a plain text file containing one to many lines of code)\n",
    "- With the help of a GUI (graphical user interface). GUIs for coding are called **IDEs (Integrated Development Environments)**.\n",
    "    - Some Python IDES: Spyder, PyCharm, Jupyter Lab, Google Colab, VS Code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*The Jupyter Notebook we're working in now can be used for both interactive (one line at a time) and batch programming (many lines at a time).*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">Python is:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**50% Syntax**\n",
    "- Which words to use\n",
    "- Punctuation\n",
    "- Order\n",
    "- Indentation\n",
    "- Shortcuts"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**50% Logic**\n",
    "- Which tools to use in which order\n",
    "- Creative\n",
    "- Specific to one problem"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Try not to worry if you don't understand everything today. You'll get more practice and time to think (and overthink!) this week. I will label some concepts we cover as **<span style=\"color:crimson\">LOGIC**. LOGIC skills are very helpful for piecing together your own code, but if you are struggling on a LOGIC section, don't worry too much - you can focus on learning the syntax and come back to thinking about logic when you are writing your own code."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>Python is a very different language than R.\n",
    "If you are an R coder, Python works very differently. R was originally written for statistical analysis and is primary a *functional* language. This means that you are often thinking \"How do I do what I want to do?\" and then look for the function or series of functions you will apply to your data. Python was originally written for software development and can be used as an *object-oriented* language, a *procedural* language, or a *functional* language. This means that you should think \"What exactly do I want to do?\" and then write code to do exactly what you want instead of looking for predefined functions.\n",
    "<br><br>The power of Python comes from lists, dictionaries, loops, and conditionals. Python is best for anything that comes close to software development, including automating tasks, complicated logic problems, coding new computational methods, and creating completely custom solutions. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>Python is a language, but you'll never have to speak it in front of anyone!\n",
    "You do not have to memorize everything you learn - Coders of all levels rely on searching the internet to help them recall the syntax for a particular task. Your search engine will point you to the official Python documentation or forums like Stack Overflow or blog tutorials. More and more, you can also use Large Language Models like ChatGPT to help you write code, but you should always be careful about the code you get from an LLM - there are ways it could introduce a virus to your computer or a bug in your code that you don't understand."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">Objects and Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The two main concepts of Python.\n",
    "- **Object**: a particular piece of data (like a noun)\n",
    "- **Function**: something you can do to/with an object (like a verb)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>You can use certain functions with certain classes of objects.\n",
    "<br>\n",
    "<br>Some functions are shared between classes of objects, and some are not."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>Let's consider this example. I have a dog named Molly, and I have a bicycle. There are some things I can do to both Molly and my bicycle, and some things I can't do to both:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 🐕 Molly\n",
    "\n",
    "- Feed Molly\n",
    "- Pet Molly\n",
    "- Draw Molly\n",
    "\n",
    "## 🚲 My bicycle\n",
    "- Pedal my bicycle\n",
    "- Pet my bicycle (limited use)\n",
    "- Draw my bicycle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>The things I can do to Molly are actually things I can do to any dog, and the things I can do to my bicycle are things I can do to any bicycle:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 🐕 Molly (class dog)\n",
    "\n",
    "- Feed a dog\n",
    "- Pet a dog\n",
    "- Draw a dog\n",
    "\n",
    "## 🚲 My bicycle (class bicycle)\n",
    "- Pedal a bicycle\n",
    "- Pet a bicycle (limited use)\n",
    "- Draw a bicycle"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>Python example: We can do different things to the number three, depending on which type of object it is."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 🔢 &nbsp; 3 (class integer)\n",
    "\n",
    "- Divide (3 / 3 = 1)\n",
    "- Convert 3 to 3.0\n",
    "- Add (3 + 3 = 6)\n",
    "\n",
    "## 📝 &nbsp; \"3\" (class string)\n",
    "- Replace (\"3\" becomes \"1\")\n",
    "- Convert \"3\" to 3.0\n",
    "- Add (\"3\" + \"3\" = \"33\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><br>Today's Objects\n",
    "- Integer (whole number) 3\n",
    "- Float (number with digits following a decimal point) 3.0\n",
    "- String (text or characters) “3” or “three”\n",
    "- Boolean (True or False)\n",
    "- *Assigning objects to variables*\n",
    "- *Indexing to get only part of an object*\n",
    "\n",
    "### Today's Functions\n",
    "- Basic operators: + - * /\n",
    "- Functions to convert between data types\n",
    "- String functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><br><span style=\"color:magenta\">**LET'S CODE!**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br>Arithmetic operators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "4 + 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "6 - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "100 * 35"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 / 6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To calculate an exponential:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "4 ** 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>You might notice that I've included spaces around the operators: \n",
    "<br>`4 + 2`\n",
    "<br>instead of\n",
    "<br>`4+2`\n",
    "<br><br>This is best practice in Python because it is more readable. The math would work without spaces, but it's a good idea to get into the habit of writing \"Pythonic\" code now!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br><br>More division operators:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 / 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We gave it **integers** (whole number objects) and it returned a **float**. The `/` division operator always returns a float."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Get just the integer, without the remainder:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 // 6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get just the remainder:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 % 6 "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><span style=\"color:crimson\">Like many things you'll learn this week, I'm not expecting you to memorize the operator for returning a remainder. If this is something you use a lot already in your research, you might memorize it now. But if not, I just want you to hear about it so that if you ever need it months from now, you might remember that there is a way to do it so that you can google it and find the right code.</span>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>More practice:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 / 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 // 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 % 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br><br>Python follows the PEMDAS order of operations: (https://thehelloworldprogram.com/python/python-operators-order-precedence/)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 / 5 + 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "40 + 2 * 6 - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "(40 + 2) * (6 - 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Why did some lines of code return integers (51, 210) and one returned a float (10.0)? <br><br><br><br>The first line of code included division `/`, which you may remember always returns a float."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: Arithmetic Operators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Try out some math of your own:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you ever want to add another code cell to you notebook, you can. Click in the cell *above* where you want to add a cell, and then click the **+** sign in the menu at the top of the page. (On Google Colab it will say **+ Code**). Let's try it now. Click in this cell and then click on the **+** button above (or **+ Code**)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br>Comparison operators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These return a **boolean** object: True or False."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 > 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 < 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 >= 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 <= 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To check if two things are **equal**, Python uses a double equals sign:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 == 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To check if two things are **not equal**, Python uses `!=`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 != 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 != 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: Comparison Operators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write code to find out if 1.00486 is greater than 1.000918."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write code to find out if 6 is equal to 6.0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br>Logical operators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These also return a **boolean**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`and` means both sides must be True to return True:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 < 4 and 4 == 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`or` means only one side must be True to return True:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 < 4 or 4 == 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`not` is another logical operator. It reverses the boolean that follows it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "not 2 == 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: Logical Operators"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before running these cells, try to guess if they will return True or False:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "not 2 > 3 and not 2 == 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "not 2 > 3 or not 2 == 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "3 == 3 and not 3 != 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br>String objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A **string** is an object kind of like text. \n",
    "<br><br>It is contained in double `\"` or single `'` quotes (you can choose which you want to use, but I use double quotes, so that is what we will use for this bootcamp)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Hello World\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>Let's use our first **function**! The `print()` function can be used on almost all classes of objects:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Strings can contain digits:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World 2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br><br>Special Characters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Strings can contain **special characters**. These start with a backslash (on my keyboard, the backslash key is found above my return key). The backslash can also be called the **escape character**. <br><br>The most commonly used special characters are new lines `\\n`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World\\nHow are you?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>...and tabs `\\t`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World\\tHow are you?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>If you simply **run** the string, it will return the string how it looks to the computer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Hello World\\nHow are you?\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>...but if you use the `print()` function, it **interprets** the special characters and returns the string like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World\\nHow are you?\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>You can include single and double quotation marks in your strings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Here's an example.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('Hello \"World\"')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the first example, we used a single quotation mark (apostrophe) inside double quotation marks. In the second example, we used double quotation marks inside single quotation marks."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>What if you want to include both single and double quotation marks in a string? You can use the escape character (the backslash) to let the computer know to interpret the following character as part of the string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Here's the \\\"example\\\".\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>If you ever need to include an actual backslash in your string and you don't want it to be interpreted as a special character, you can use a double backslash:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"always\\never\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"always\\\\never\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: Strings and Special Characters"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write code to print out the following message (it should look exactly as it is shown here):\n",
    "<br><br>This is line 1.\n",
    "<br>This is line 2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><br>Python errors"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What happens if you forget the quotes around a string?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(Hello World)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>Our first error!! This is a common error - the `SyntaxError`. It often means that we forgot to type something."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>What happens if you spell a function wrong?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pint(\"Hello World!\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>A `NameError` is another common error - it often means we've mispelled a function or variable."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>What error do you think we will get if we run this line of code?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br>Combining strings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some arithmetic operators work with strings. To combine two strings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello\" + \"World\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello \" + \"World\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br>Converting between data types"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>The `type()` function tells us the data type of an object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "type(\"Hello World\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "type(9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "type(9.9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "type(\"9.9\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>We can convert objects from one type to another, using the appropriate function:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "float(9)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "float(\"5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "int(\"5\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "int(5.7)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Notice it doesn't round when it converts a float to an integer, it just drops off everything after the decimal. You can use the `round()` function to round, but we'll cover that a bit later.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "str(5.005)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "float(\"Hello World\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Our third type of error! This error usually means you passed an argument to a function that it doesn't recognize. But don't spend any brainpower trying to memorize this error. Luckily the error message gives us information about what we did wrong."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br>Data types interacting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before running each of these cells, try to guess what they will return:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "4 * 4.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "int(4 * 4.0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Hello World\" * 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "5 + True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "5 + False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note: True evaluates to 1, False evaluates to 0*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: Data Types Interacting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the next line of code:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World\" + 4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>A TypeError means you tried to do something that doesn't work with the type of object you gave it. Sometimes ValueErrors and TypeErrors get thrown for similar errors."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Use a function to modify the code below to create a string that says \"Hello World4\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World\" + 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><br>Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Variables allow you to store an object to use it later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nothing is returned when you assign a variable. You can see the value of a variable by running the variable name or using the `print()` function"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(x)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>The single `=` is called an **assignment operator**.\n",
    "<br>Everything on the right side of the assignment operator is calculated first, and then that value is stored as the variable on the left of the assignment operator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = 3 - 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = x**y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rabbit = 50"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Variables can be used just like the objects they represent:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rabbit - 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "rabbit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greeting = \"Hello you!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greeting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(greeting)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: Creating Variables"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a variable called `favorite_color` and assign it to a string that contains your favorite color. Then write code to print the string you saved as `favorite_color`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br>Variable names"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Python Rules\n",
    "- No spaces\n",
    "- Case matters: x is not X\n",
    "- Must start with a letter\n",
    "- Should be meaningful (don't save your number as `rabbit` unless it represents the number of rabbits)\n",
    "- For longer variable names: separate_with_underscores"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">Functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We've been learning a lot about objects. Let's learn more about functions!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>**Parentheses immediately follow a function name (no space).**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"Hello World\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The information inside the parentheses is called an **argument**.\n",
    "<br>We say we **passed** the argument \"Hello World\" to the print function."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>Some functions take multiple arguments. The arguments must be separated by a comma:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "round(4.5874, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We'll learn more about the round() function later today. It takes two arguments: an integer or a float to be rounded, and the number of places after the decimal point that the first number should be rounded to."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br>Two types of functions in Python"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. A true **function**. \n",
    "- Stands on its own. \n",
    "- Takes an object as an **argument**. \n",
    "- These types of functions usually do something **with** the object.\n",
    "- Can usually be used on multiple object classes."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_name = \"Colby\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(my_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(1045)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(my_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>2. **Method**\n",
    "- Always follows an object. \n",
    "- Some take arguments and some don't. \n",
    "- These types of functions usually do something **to** the object.\n",
    "- Methods are specific to one object class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_name = \"Colby\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_name.upper()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Here we can see that methods are specific to one object class. A **string** can be turned into uppercase, but an **integer** cannot:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "1045.upper()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Here is an example of a method function that takes multiple arguments, separated by a comma:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_name.replace(\"C\", \"c\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will learn more about the `.replace()` method after the next exercise."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: String functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Create a new variable called `full_name`. It should store the string of your own full name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(full_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write code to find out the length of your full name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Did the length function count spaces when it calculated the length of your name?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*When Python developers create Python functions, they have to make choices about how the functions will work. For example, should the `len()` function count spaces or not? It's important to test out functions to see how they work if you are unsure or if you are getting unexpected results.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br>String functions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greeting = \"Hello you!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(greeting)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "len(greeting)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greeting.replace(\"!\", \".\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greeting.replace(\" \", \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`\"\"` is referred to as an **empty string**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(greeting)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Even though we ran code to change our greeting, the greeting variable still **points** to the original greeting. `greeting` did not change when we used the method functions even though a changed version of `greeting` was **returned**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>To change the greeting, we would have to **reassign** the variable name:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greeting = greeting.replace(\"!\", \".\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(greeting)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "big_greeting = greeting.upper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(big_greeting)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "small_greeting = greeting.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(small_greeting)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_name = \"Colby\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greetMe = greeting.replace(\"you\", my_name)\n",
    "print(greetMe)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Note: You might have noticed that I included two lines of code in that code cell. Jupyter Noteboooks can run multiple lines of code in a single code cell.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>**You will learn more string functions and get practice with string functions in the afternoon session.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">Indexing strings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can **index** strings to return a **substring**. A substring can be one or more characters long."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br><span style=\"color:magenta\">**In Python indexing, we start counting with 0.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### H &nbsp; &nbsp; E &nbsp; &nbsp; L &nbsp; &nbsp; L &nbsp; &nbsp; O &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; W &nbsp; &nbsp; O &nbsp; &nbsp; R &nbsp; &nbsp; L &nbsp; &nbsp; D &nbsp; &nbsp; !\n",
    "#### 0 &nbsp; &nbsp; 1 &nbsp; &nbsp; 2 &nbsp; &nbsp; 3 &nbsp; &nbsp; 4 &nbsp; &nbsp; 5 &nbsp; &nbsp; 6 &nbsp; &nbsp; 7 &nbsp; &nbsp; 8 &nbsp; &nbsp; 9 &nbsp; &nbsp; 10 &nbsp; &nbsp; 11"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>To return a single character, we type our string followed immediately by square brackets (no space). Inside the brackets, we pass the index position for the character."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Hello World!\"[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Hello World!\"[4]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br><br>H &nbsp; &nbsp; E &nbsp; &nbsp; L &nbsp; &nbsp; L &nbsp; &nbsp; O &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; W &nbsp; &nbsp; O &nbsp; &nbsp; R &nbsp; &nbsp; L &nbsp; &nbsp; D &nbsp; &nbsp; !\n",
    "#### 0 &nbsp; &nbsp; 1 &nbsp; &nbsp; 2 &nbsp; &nbsp; 3 &nbsp; &nbsp; 4 &nbsp; &nbsp; 5 &nbsp; &nbsp; 6 &nbsp; &nbsp; 7 &nbsp; &nbsp; 8 &nbsp; &nbsp; 9 &nbsp; &nbsp; 10 &nbsp; &nbsp; 11"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To take a longer **substring**, you start with the position of the first character you want included, then a colon, and end with the position *1 past* the last character you want."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To index \"Hello\":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Hello World!\"[0:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>If this seems strange, it might help you to know what is happening behind the scenes. Python is actually labeling the invisible spot *between* each character in our string:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### &nbsp; &nbsp; H &nbsp; &nbsp; E &nbsp; &nbsp; L &nbsp; &nbsp; L &nbsp; &nbsp; O &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; W &nbsp; &nbsp; O &nbsp; &nbsp; R &nbsp; &nbsp; L &nbsp; &nbsp; D &nbsp; &nbsp; !\n",
    "#### 0 &nbsp; &nbsp; 1 &nbsp; &nbsp; 2 &nbsp; &nbsp; 3 &nbsp; &nbsp; 4 &nbsp; &nbsp; 5 &nbsp; &nbsp; 6 &nbsp; &nbsp; 7 &nbsp; &nbsp; 8 &nbsp; &nbsp; 9 &nbsp; &nbsp; 10 &nbsp; &nbsp; 11 &nbsp; 12"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So now it's easier to see why \"Hello\" would be indexed with [0:5].<br><br><br><br>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greeting = \"Hello you!\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "greeting[0:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello = greeting[0:5]\n",
    "print(hello)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello[2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Remember, in Python we start indexing at 0, so the third letter in our string is indexed as 2.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>We can also start indexing from the right end of the string. The character in the farthest right position can be indexed as -1. We call this **negative indexing**."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello[-2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello[0:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Remember, our variable is `hello`, but the string it has stored is \"Hello\" with a capital \"H\".*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>If we don't give any number after the `:`, Python will continue to the end of the string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello[3:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If we don't give any number before the `:`, Python will start at the beginning of the string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello[:2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>We can also use negative numbers to index substrings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello[2:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "hello[-3:-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"Hello\"[-3:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: Index a string"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the line of code below to store the variable `movie`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "movie = \"TENET\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write code to index the first character in the variable `movie`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Use negative indexing to return the last character in the variable `movie`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Bonus exercise**\n",
    "<br>Is the first letter of `movie` the same as the last letter of `movie`? Combine the indexing statements you just wrote with a comparison operator to see if the two letters are equal."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Your code should return a boolean: True or False.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">Modules (aka packages or libraries)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default, only a handful of the most commonly used functions and object classes are loaded when you start Python.\n",
    "<br><br>This saves memory so that your Python scripts can run as quickly as possible.\n",
    "<br><br>The object classes and functions that are loaded automatically with Python are called **built-in**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>Modules\n",
    "- Modules are groups of related functions and object classes\n",
    "- They are not automatically loaded when you start Python\n",
    "- You must **import** the module every time you start Python (or in every Jupyter Notebook)\n",
    "- If you do not have the module on your computer, you must first **install** it (only once)\n",
    "- If you are working in Google Colab, many of the most popular Python packages are ready to **import** (they are pre-installed in Colab). To use other packages, you must **install** the package first, and then **import**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>Where to find modules\n",
    "- It is usually best to install packages from one of the big, trusted package **repositories** (we'll talk more about this in a few minutes)\n",
    "- The Anaconda distribution of Python comes with many of the most common modules pre-installed (we'll talk more about Anaconda in a few minutes)\n",
    "- Many other modules can be installed from the command line\n",
    "- Some must be downloaded from the creator (such as from their GitHub site). This happens sometimes with packages developed by academics that you might find in a journal article. Note that these packages have not been checked for malware or bugs by a trusted package repository and should be used with care.\n",
    "- There are modules for every field and use"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Today we'll learn how to **import** packages and work with a couple functions from a package that is included in every installation of Python but isn't automatically loaded when you start Python.\n",
    "<br><br>Later this week we'll talk briefly about **installing** packages."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We are going to use some functions from the module `math`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You should usually import any modules at the top of your Jupyter notebook, even if you don't use them until much later in the notebook. This is so that people can see which modules they need as soon as they open the notebook, in case they need to **install** the module on their computer. *We're breaking this rule today and loading the module here.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run this cell to import the `math` module:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>To use a function from an imported module, you type the name of the module followed by `.` followed by the name of the function. Let's use `math.sqrt()` to find the square root of a number:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "math.sqrt(16)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "math.sqrt(15.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>The `math` module contains many mathematical functions. It also contains a few objects, like `math.pi`, which is the value of pi, so that you don't have to memorize it. You know it's an object and not a function because it doesn't have parentheses at the end."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "radius = 6\n",
    "area_of_a_circle = math.pi * radius**2\n",
    "print(area_of_a_circle)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Remember that `**` is used to find an exponent like a square.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Exercise: Use an object from a module"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The equation for calculating the circumference of a circle is 2 x pi x radius. Write code to calculate the circumference of a circle with a radius of 10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "radius = 10\n",
    "circumference = \n",
    "print(circumference)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">All about snakes!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's talk about the tools that we're working with, and other tools that have been mentioned."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Python\n",
    "Python is an **open source** programming language. This means the source code is public, which means the language is free for anyone to use. It means anyone can develop their own Python package. \n",
    "<br><br>Python is **maintained** (made available, checked for bugs) and improved (adding new features, changing fundamental operations) by a non-profit at Python.org called the Python Software Foundation (PSF). PSF is sponsored by all the major tech companies who rely on Python, which means those companies often pay a staff member some amount of time to help maintain Python. Volunteers are also a big support.\n",
    "<br><br>Python runs behind the scenes in many tech tools (like your Macbook) and software programs, without you even knowing. To use Python yourself, you can:\n",
    "- install it on your computer\n",
    "- connect to a lab server or the university's HPC system\n",
    "- use a cloud tool\n",
    "\n",
    "We will talk more about these options below, as well as talk more about how Python packages work. First, we need to talk about Jupyter Notebooks."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>Jupyter Notebooks\n",
    "At the beginning of this notebook, we talked about how Python can be used in multiple ways. **Jupyter notebooks** (like this one) are coding notebooks for Python. Coding notebooks are a relatively new way to code, but they have become the norm for many fields. They allow you to combine code cells with text cells that can also contain links and images. You can run Jupyter Notebooks on your own computer, on the university's HPC system, or on the cloud (like we are doing now through Google Colab). If you will use Python to run computationally intensive code that takes more than a few minutes to run, you will need to learn how to write a **script**, but for writing new code, exploring data, or creating visualizations, Jupyter notebooks are great.\n",
    "<br><br>**Jupyter** is a data science non-profit that makes open source software. **Jupyter Notebook** is also the name of the original software program Jupyter created to run Jupyter notebooks, but now I recommend you use other means to run your notebooks, as Jupyter Notebook (the software program) is no longer receiving updates."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br>Installing Python on your computer"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>Anaconda\n",
    "Anaconda is a for-profit company. It makes money selling data science tools and support to companies. It also provides a free **distribution** of Python (that many of you downloaded) that includes Python, the most popular Python packages, and a suite of GUI software, including Jupyter Lab (my personal favorite IDE). **GUI** (Graphical User Interface) refers to software that lets you point and click, instead of just using code. You could have installed Python alone, then each package, and each software program separately, however, that would have taken hours of troubleshooting on the command line to link all the tools behind the scenes. Anaconda does all that for you.\n",
    "<br>The Anaconda distribution also contains the **conda** package manager and environment manager.\n",
    "<br><br>*The Anaconda distribution is only free for educational purposes (like this workshop) and research that is not for commercial profit.* **If your research is for commercial profit, or has any potential of profit, do not use the free distribution.**"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Python IDEs\n",
    "There are several great Python IDEs. Some are free and some aren't. You may need to install Python first (from the Python Software Foundation) and then link it behind the scenes to the IDE you've chosen. This can be tricky, but you can make a consult request with our team to get help.\n",
    "<br><br>Some IDEs we like:\n",
    "- Jupyter Lab\n",
    "- Spyder\n",
    "- VS Code\n",
    "- PyCharm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br>Using Python through Northwestern University's Quest High Performance Computing Cluster\n",
    "*This option is only for Northwestern University researchers.*\n",
    "<br><br>Quest is great if you:\n",
    "- Need more memory, power, speed, or GPUs than you have on your local machine\n",
    "- Have large data sets\n",
    "- Work with data shared by your whole lab\n",
    "- Work with private or restricted data\n",
    "- Don't want to install big packages or software on your own computer\n",
    "- Want to get remote support and advice from the Quest support team\n",
    "\n",
    "You can access Python in a Jupyter Notebook through Quest OnDemand or submit Python scripts to run through the job scheduler."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br>Python on the cloud\n",
    "#### Google Colab\n",
    "Google Colab is a cloud-based program that lets you run Jupyter notebooks. It provides free computing power and memory to Google users. You can access GPUs from Colab and you can pay for more memory. Google does have access to any code or files you work with on Google Colab (for training AI models, for example), so never use it for private or restricted data. Google could also put Colab behind a paywall at any time, but it is a nice free resource for now.\n",
    "\n",
    "#### GitHub Codespaces\n",
    "This is another cloud resource for running notebooks. We haven't tried it out much yet, but we plan to soon. GitHub is now owned by Microsoft."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br>Package repositories and Package managers\n",
    "Package **repositories** are collections of Python packages that are hosted online for you to use. \n",
    "<br><br>To download a package from a repository, you have to use a **package manager**, which is a software tool that does three things:\n",
    "- installs a package from the repository\n",
    "- connects the package to your version of Python behind the scenes\n",
    "- handles any **dependencies** (many packages are built on top of other packages, so the package manager will make sure you install those packages too)\n",
    "\n",
    "<br>There are a few big package repositories. **The big repositories all host packages that have already been checked for any malware.** This is important because packages are computer code - they are designed to run code on your computer - so you should only use a trusted source. Most packages on the big repositories have also been checked for bugs, but some repositories specifically host newer packages that are still in development. \n",
    "<br><br>There are currently three big package managers that we will discuss."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>PyPI (Python Package Index) and pip (Python Installs Packages)\n",
    "**PyPI** is a Python package repository, an online collection of free Python modules that are written and vetted by Python users. PyPI uses the **pip** package manager. \n",
    "<br><br>PyPI is maintained by Python.org. All of the most popular Python packages are available from the PyPI package repository. All packages available on PyPI should already be vetted and checked for bugs and malware. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>conda, conda-forge, and bioconda\n",
    "conda is the name of both a Python package **repository** and the name of the associated **package manager**. All packages on conda will have been vetted and checked for bugs and malware. conda-forge is another package repository for less developed packages that are still in development (but will have been checked for malware). Bioconda is yet another package repository for Biomedical packages. conda, conda-forge, and Bioconda are all maintained by Anaconda and all use the conda package manager for installations and updates. **Like the Anaconda distribution, the conda package repository is free only for educational uses and not-for-profit research.** mamba is a great alternative to conda."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br>mamba\n",
    "**mamba** is a package manager and an alternative to conda. It pulls packages from the conda-forge repository among others. Like conda, it is often better at solving dependencies than pip."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>*Both pip and conda are included in the Anaconda distribution of Python.* You can trust packages from these sources, but you should be careful about packages you download from other sources, like random GitHub sites. They could have code that damages your computer, or they could have incorrect calculations."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>conda and mamba also allow you to create **environments**. Environments allow you to set up different versions of Python and associated packages in different environments that you can switch between. This can be very helpful if you are working with an old piece of software that needs an older version of Python, or if you have different requirements for different projects."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# <br><br><span style=\"color:rebeccapurple\">LUNCH BREAK - meet back at 1 pm Central"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**If you're working in Colab**, you might need to refresh your page. You'll lose the work you did above - but if you'd like to save it you can either: <br>1. Click the button at the top Copy to Drive and save it in your personal Google Drive, or\n",
    "<br>2. Go to File>Download>Download .ipynb"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">More fun with integers and floats\n",
    "### <br><br>Let's turn some story problems into Python code."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*When running this code, don't forget to run every code cell. If you get a `NameError` it might be because you didn't run a cell where a variable was defined.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>I told the class I ate 12 bananas for lunch:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bananas = 12"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You saw me secretly eat 3 more bananas:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bananas = bananas + 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "How many bananas did I eat?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(bananas)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's add some strings together to print the answer out as a complete sentence:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "answer = \"Colby ate \" + bananas + \" bananas.\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Error! Let's check the type of the variable `bananas`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "type(bananas)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can change `bananas` to a string and save it as a new variable so that we can include it in our answer..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bananas_str = str(bananas)\n",
    "answer = \"Colby ate \" + bananas_str + \" bananas.\"\n",
    "print(answer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>...or we can change it to a string *inside* the code to create our answer:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "answer = \"Colby ate \" + str(bananas) + \" bananas.\"\n",
    "print(answer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>Our final code for this story problem looked like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bananas = 12\n",
    "bananas = bananas + 3\n",
    "answer = \"Colby ate \" + str(bananas) + \" bananas.\"\n",
    "print(answer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>I also could have written the code like this, creating a new variable in the second line instead of reusing the variable name `bananas`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bananas = 12\n",
    "real_bananas = bananas + 3\n",
    "answer = \"Colby ate \" + str(real_bananas) + \" bananas.\"\n",
    "print(answer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "<br>Or I could have written the code like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bananas = 12\n",
    "secret_bananas = 3\n",
    "real_bananas = bananas + secret_bananas\n",
    "answer = \"Colby ate \" + str(real_bananas) + \" bananas.\"\n",
    "print(answer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Or I could have written the code like this:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "bananas = 12\n",
    "print(\"Colby ate \" + str(bananas + 3) + \" bananas.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>These alternative ways of getting to the same answer are all acceptable. The difference between them involves when I decided to assign values to variables. There isn't always a right or wrong answer, but there are some guidelines to make your code more \"Pythonic\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>In general, you want your code to be succinct but readable. You don't want to store too many variables in your computer's memory at one time, especially if they contain large objects like whole files (we'll talk about files and memory on Day 3). If you will never use the object again in the code, you might not want to bother assigning that object to a variable. Then again, if it makes it more readable to assign it to a variable, you should."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>For now, just focus on writing code that works! All of the options above would be acceptable."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Integers and Floats Exercise 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "My kitchen is 10 feet long by 10 feet wide. How many square feet is my kitchen? (The equation for area is length multiplied by width.) Finish the code below by assigning the area equation to the variable `area`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "length = 10\n",
    "width = 10\n",
    "area = \n",
    "print(\"The kitchen is \" + str(area) + \" square feet.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Integers and Floats Exercise 2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I scored 80 points on my first test and 88.5 points on my second test. What is my average test grade? (The equation for average test grade is the sum of all test scores divided by the number of tests.) Fill in the appropriate code below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "test1 = \n",
    "test2 = \n",
    "average = \n",
    "print(\"Colby's average test grade is \" + str(average) + \".\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Integers and Floats Exercise 3"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Last week I ran 10 miles. This week I ran the same as last week, plus 6 extra miles. How many miles did I run in total over both weeks? Write the code below to calculate the total number of miles. As a bonus, write the code to print out a complete sentence that says how many miles I ran. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><br>Let's learn some new functions that work with integers and floats."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>The `abs()` function returns the absolute value of a number:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "abs(-19.6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>The `round()` function will round a float to a specified number of decimal places. It takes two arguments: the number to round and the number of decimal places."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "my_number = 631.890382720"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "round(my_number, 4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "round(my_number, 2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some function arguments have **default values**, so if you don't include the argument, it will use the default value. Let's try `round()` without specifying a value for the second argument:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "round(my_number)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So the default value is to round to the closest integer."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`round()` can also round to places to the left of the decimal point:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "round(18192948, -3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>You can also put functions inside other functions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "round(abs(-12.908))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "abs(round(-12.908))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "round(30 + 698, -1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Integers and Floats Exercise 4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I am ordering 3 tacos for lunch. Each taco is $3.55. I would like to round my total up to the nearest dollar to leave a small tip. How much should I pay? Write the code below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>Some functions have more than one argument that has a default value. To change the default value, you have to pass the function a **keyword argument**. Let's see how this works."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The function `isclose()` is in the `math` module. Let's import the math module again, in case you closed and reopened this notebook during lunch."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import math"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>`math.isclose()` will tell you if two numbers are close. It returns a boolean."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "math.isclose(4, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4 and 5 are not considered close."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "math.isclose(0.4, 0.5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Still not close."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "math.isclose(0.0004, 0.0005)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Still not close."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "math.isclose(.4999999999, .5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Relative tolerance* is the maximum allowed difference between a and b. The default relative tolerance is 1e-09.\n",
    "<br><br>We can change the relative tolerance by passing the keyword argument `rel_tol`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "math.isclose(4.03, 4.02, rel_tol=.01)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>We can get information about a function by looking it up in the documentation <https://docs.python.org/3/library/index.html> or by coding the function name without the `()` followed by `?`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "math.isclose?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><span style=\"color:teal\">More fun with strings"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>We already learned these string functions:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song = \"We are the world\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.lower()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.upper()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.replace(\"world\", \"weird\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_word = \"wind\"\n",
    "song.replace(\"world\", new_word)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>We also learned that these functions don't change the song:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(song)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "...and that we can save a changed version of the object by assigning a new variable, or reassigning the old variable:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song = song.upper()\n",
    "print(song)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br>More capitalization functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the code below to see what the `title()` and `capitalize()` methods do."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song = \"All along the watchtower\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.title()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song = song.lower()\n",
    "print(song)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.capitalize()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br>Removing characters from a string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(song)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>The `lstrip()` method will remove a character or set of characters if it is the first character on the left side of the string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.lstrip(\"a\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.lstrip(\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.lstrip(\"w\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\"w\" is not the first character on the left side of the string, so nothing was removed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Note that the `.lstrip()` method is not for removing exact patterns. It will take any of the characters you pass as an argument in any order. Let's apply the same method and argument to all these strings:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"all along the watchtower\".lstrip(\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"llama llama, red pajama\".lstrip(\"all\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"lalalalalatida\".lstrip(\"all\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>The `rstrip()` method will remove a character or set of characters if it is the first character on the right side of the string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.rstrip(\"er\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>I use `rstrip()` all the time to remove new line characters from the end of lines in a file, or to remove trailing whitespace:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"line in a file\\n\\n\".rstrip(\"\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\"line in a file      \".rstrip(\" \")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*Notice that it removed all the spaces on the right end of the string, even though we only passed it one space as the argument.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### <br><br>Removing a character everywhere it appears in a string\n",
    "Use the `replace()` method we already learned and replace the character with an empty string:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.replace(\" \", \"\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Strings Exercise 1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Run the next line of code to save the variable `book`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "book = \"The Three Musk-eteers\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Write code to remove the \"-\" in the middle of `book`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Bonus exercise:** Write code to remove the \"-\" in the middle of the word \"Musketeers\" in `book2`, but not the \"-\" that divides the title from the subtitle."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "book2 = \"The Three Musk-eteers - Part Two\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br>Stringing together method functions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can string multiple method functions on the end of an object. The functions will be executed from left to right."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song = \"Let It Go\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "different_song = song.replace(\"Go\", \"Be\").upper()\n",
    "print(different_song)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>The order of functions can change what is returned. Why do you think reversing the order of functions turns out the way it does?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "different_song = song.upper().replace(\"Go\", \"Be\")\n",
    "print(different_song)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br><br>Once you've made the song uppercase, \"Go\" does not exist in the string, so it won't be replaced. \"Go\" is already \"GO\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>*Side note, in case this ever happens to you, if you forget to put the parantheses on the end of your method function, you might not get an error, but you will see something like this:*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song.lower"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br>Indexing and function practice"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In this morning's lecture you learned how to index a string to return a substring. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "song_line = \"Row, row, row your boat\"\n",
    "what_to_row = song_line[-9:]\n",
    "print(what_to_row)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "what_to_do_with_your_boat = song_line[:3]\n",
    "print(what_to_do_with_your_boat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "whose_boat_it_is = song_line[14:18]\n",
    "print(whose_boat_it_is)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Strings Exercise 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "lyrics = \"Lean on me, when you're not strong\\nAnd I'll be your friend\\nI'll help you carry on\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print(lyrics)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Run the two lines of code above to see the string we'll be working with."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Use string indexing to write code to print each line of the song on its own:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "first_line = \n",
    "print(first_line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "second_line = \n",
    "print(second_line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "third_line = \n",
    "print(third_line)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Write code to replace the new line characters (`\\n`) in `lyrics` with a period and a space \". \":"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "lyrics_on_one_line = \n",
    "print(lyrics_on_one_line)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>Write code to capitalize the first letter of every word in `lyrics`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>*If this result looks strange to you, we will learn how to fix it on Day 3!*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### <br><br><span style=\"color:red\">Strings: Secret Message Exercise"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For this exercise, you are going to transform one string into another. First I will show you an example. Then you will write one of your own."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_message = \"I ate so many cookies now I feel sick.\"\n",
    "print(full_message)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_message[:-12]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_message[:-12].replace(\"ate so\", \"want\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_message[:-12].replace(\"ate so\", \"want\").replace(\"any\", \"ore\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_message[:-12].replace(\"ate so\", \"want\").replace(\"any\", \"ore\").title()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_message[:-12].replace(\"ate so\", \"want\").replace(\"any\", \"ore\").title().replace(\" \", \". \")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_message[:-12].replace(\"ate so\", \"want\").replace(\"any\", \"ore\").title().replace(\" \", \". \") + \"Please.\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br><br>**<span style=\"color:crimson\">LOGIC.** Now it is your turn. Think of a string that you want to turn into a different string. Use trial and error to build up a line of code that will transform your message."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<br>You can use indexing to take a substring, any of the string functions you've learned today (`rstrip()`, `lstrip()`, `replace()`, `upper()`, `lower()`, `capitalize()`, `title()`), as well as the addition operator `+` to add new characters at the end or beginning. Include at least 5 steps to get from your full message to your secret message."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_message = \"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## <br><br><br>Day 1 Quiz"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Test yourself on what you learned today by completing the Day 1 Quiz. The Jupyter Notebook file is called \"day1Quiz.ipynb\" and is in the same folder as this notebook. If you are using Colab, go to <https://colab.research.google.com/github/nuitrcs/pythonBootcamp_4Day/blob/main/day1Quiz.ipynb>."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will take some time now for you to complete the quiz, and we will review the quiz answers live after this period.\n",
    "<br><br>The quiz is self-graded - you do not need to turn anything in! The answer key is called \"day1Quiz-answers.ipynb\". For Colab users, the answer key is at <https://colab.research.google.com/github/nuitrcs/pythonBootcamp_4Day/blob/main/day1Quiz-answers.ipynb>."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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