self_assessment.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "reverse-assault",
   "metadata": {},
   "source": [
    "# Overview and Instructions\n",
    "\n",
    "This assessment covers the following topics:\n",
    "\n",
    "- **Datatypes**\n",
    "- **Math Operators**\n",
    "- **Data Structures**: Lists, Dictionaries\n",
    "- **Loops and Control Flow**\n",
    "- **Functions**\n",
    "- **Packages and Modules**\n",
    "\n",
    "Instructions:\n",
    "\n",
    "- Complete the problems in this notebook, then run the cell at the end to calculate your score and see which questions you got right and wrong.\n",
    "- There is no time limit, although this shouldn't take more than an hour.\n",
    "- Feel free to use any resources while completing this self-assessment.\n",
    "- You should get at least 5 of the 15 questions correct.\n",
    "- Be careful to type things exactly, as typos will cause you to miss questions."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "transparent-brother",
   "metadata": {},
   "source": [
    "<!-- Using the variables  `a`, `b`, and `c`, multiply 17 by 7, then divide by 5 and round down to the nearest integer. -->\n",
    "# 1. Simple Math\n",
    "Using the variables `a`, `b`, and `c`, perform the following operations:\n",
    "\n",
    "1. Multiply `a` by `b`.\n",
    "2. Divide the result by `c`.\n",
    "3. Round down to the nearest integer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dominican-regulation",
   "metadata": {},
   "outputs": [],
   "source": [
    "a = 17\n",
    "b = 7\n",
    "c = 5\n",
    "ans_1 = "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "becoming-mobile",
   "metadata": {},
   "source": [
    "# 2. Math and Strings\n",
    "Modify the code below so that it runs properly. We want the variable `ans_2` to contain a string with the average number of people per US state. The number of people should be a round number (integer) rounded down to the nearest integer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "connected-roommate",
   "metadata": {},
   "outputs": [],
   "source": [
    "ans_2 = 'The number of people per US state on average is ' + 400000000/50"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "freelance-marshall",
   "metadata": {},
   "source": [
    "<!-- # 3. Variables\n",
    "Create a new variable called `total_snowfall` that gets the average of the `day1` and `day2` values. -->\n",
    "\n",
    "# 3. Variables\n",
    "Calculate the average snowfall over two days. Create a new variable called `total_snowfall` that stores the average of the `day1` and `day2` values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "environmental-visitor",
   "metadata": {},
   "outputs": [],
   "source": [
    "day1 = 5.5\n",
    "day2 = 17.2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "sixth-marsh",
   "metadata": {},
   "source": [
    "<!-- # 4. Lists\n",
    "Create a list with the values of snowfall (from top to bottom) from the following table:\n",
    "\n",
    "| City          | Snowfall |\n",
    "|---------------|----------|\n",
    "| Denver        | 2.1      |\n",
    "| Boulder       | 3.2      |\n",
    "| Nederland     | 7.7      |\n",
    "| Phoenix       |   0      | -->\n",
    "\n",
    "# 4. Lists\n",
    "Create a list named `snowfall_list` with the snowfall (from top to bottom) values from the table below:\n",
    "\n",
    "| City      | Snowfall |\n",
    "|-----------|----------|\n",
    "| Denver    | 2.1      |\n",
    "| Boulder   | 3.2      |\n",
    "| Nederland | 7.7      |\n",
    "| Phoenix   | 0.0      |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "superior-virtue",
   "metadata": {},
   "outputs": [],
   "source": [
    "snowfall_list = "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "funded-utility",
   "metadata": {},
   "source": [
    "# 5. Lists part 2\n",
    "Retrieve the second element of `snowfall_list` and store it in the variable `boulder`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "alternative-husband",
   "metadata": {},
   "outputs": [],
   "source": [
    "boulder = "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "wired-solid",
   "metadata": {},
   "source": [
    "<!-- # 6. Lists part 3\n",
    "Store the length of the list in the `num_cities` variable. -->\n",
    "\n",
    "# 6. Lists part 3\n",
    "Calculate and store the length of `snowfall_list` in the variable `num_cities`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "explicit-polymer",
   "metadata": {},
   "outputs": [],
   "source": [
    "num_cities = "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "egyptian-waste",
   "metadata": {},
   "source": [
    "# 7. Lists part 4\n",
    "Using the `append()` method of lists, add the value 17 to the end of the `sun_index` list."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "future-estimate",
   "metadata": {},
   "outputs": [],
   "source": [
    "sun_index = [5, 11, 23]\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "raised-fundamentals",
   "metadata": {},
   "source": [
    "<!-- # 8. Dictionaries\n",
    "Create a dictionary named `snowfall_dictionary` from the\n",
    "\n",
    "| City          | Snowfall |\n",
    "|---------------|----------|\n",
    "| Denver        | 2.1      |\n",
    "| Boulder       | 3.2      |\n",
    "| Nederland     | 7.7      |\n",
    "| Phoenix       |   0      | -->\n",
    "\n",
    "# 8. Dictionaries\n",
    "Create a dictionary named `snowfall_dictionary` from the snowfall table below, where the city names are the keys and the snowfall values are the values.\n",
    "\n",
    "| City      | Snowfall |\n",
    "|-----------|----------|\n",
    "| Denver    | 2.1      |\n",
    "| Boulder   | 3.2      |\n",
    "| Nederland | 7.7      |\n",
    "| Phoenix   | 0.0      |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "eastern-harvard",
   "metadata": {},
   "outputs": [],
   "source": [
    "snowfall_dictionary = "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "running-gnome",
   "metadata": {},
   "source": [
    "<!-- # 9. Dictionaries part 2\n",
    "Retrieve the value for Boulder's snowfall from `snowfall_dictionary`. -->\n",
    "\n",
    "# 9. Dictionaries part 2\n",
    "Retrieve the snowfall value for Boulder from the `snowfall_dictionary` and store it in the variable `boulder_snowfall`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "phantom-silicon",
   "metadata": {},
   "outputs": [],
   "source": [
    "boulder_snowfall = "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "parliamentary-library",
   "metadata": {},
   "source": [
    "# 10. Functions\n",
    "Complete the function `get_biggest_snowfall` to retrieve the largest snowfall value from the input list `a_snowfall_list`.\n",
    "\n",
    "<!-- # 10. Functions\n",
    "Complete the function to retrieve the biggest snowfall value from the input list to the function. -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "hungry-ebony",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_biggest_snowfall(a_snowfall_list):\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "earlier-friend",
   "metadata": {},
   "source": [
    "<!-- # 11. `for` loops\n",
    "Loop through `snowfall_list` and complete the function to print out each snowfall value. -->\n",
    "\n",
    "# 11. `for` loops\n",
    "Complete the function to loop through `snowfall_list` and print out each snowfall value."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "baking-account",
   "metadata": {},
   "outputs": [],
   "source": [
    "def loop_thru_snowfall(a_snowfall_list):\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "frequent-insulin",
   "metadata": {},
   "source": [
    "# 12. `while` loops\n",
    "Modify the code below so that the loop terminates when the `counter` reaches 10.\n",
    "\n",
    "<!-- # 12. `while` loops\n",
    "Modify the code so the loop terminates when the counter has reached 10. -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "outstanding-defeat",
   "metadata": {},
   "outputs": [],
   "source": [
    "counter = 0\n",
    "while True:\n",
    "    counter += 1\n",
    "    break"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "charming-recommendation",
   "metadata": {},
   "source": [
    "# 13. `if` statements\n",
    "Complete the function `print_snowfall` so that it:\n",
    "\n",
    "- Prints the name of the city, followed by a colon, and then the snowfall value (e.g., `Boulder: 3.2`).\n",
    "- Only prints the snowfall value if it is greater than 3.\n",
    "- If the snowfall is 0, prints the city name followed by a colon and \"No snow!\" (e.g., `Phoenix: No snow!`).\n",
    "\n",
    "You can test it with the `snowfall_dictionary`. Your results should look like:\n",
    "\n",
    "```\n",
    "Boulder: 3.2\n",
    "Nederland: 7.7\n",
    "Phoenix: No snow!\n",
    "```\n",
    "\n",
    "<!-- \n",
    "# 13. `if` statements\n",
    "Finish the function so that:\n",
    "- it prints the name of the city, then a colon, then the value (example: `Boulder: 3.2`)\n",
    "- the snowfall value is only printed out if it is greater than 3\n",
    "- if the snowfall is 0, print out the city name, then a colon, then \"No snow!\".\n",
    "\n",
    "You can test it with the `snowfall_dictionary`. Your results should look like: \n",
    "\n",
    "```\n",
    "Boulder: 3.2\n",
    "Nederland: 7.7\n",
    "Phoenix: No snow!\n",
    "``` -->"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "objective-jewelry",
   "metadata": {},
   "outputs": [],
   "source": [
    "def print_snowfall(a_snowfall_dictionary):\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "confidential-blink",
   "metadata": {},
   "source": [
    "# 14. Classes\n",
    "Create a new variable from the `Mortgage` class called `new_mortgage`. The loan should be for a value of 10,000 with an annual rate of 8.5% (use 0.085 for the interest rate) for 2 years. Use the `makePayment()` method once to simulate making a single payment on the loan.\n",
    "\n",
    "(The code below is from the book used in MSC575: *Introduction to Computation and Programming Using Python* by John V. Guttag)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "israeli-thailand",
   "metadata": {},
   "outputs": [],
   "source": [
    "class Mortgage(object):\n",
    "    \"\"\"Abstract class for building different kinds of mortgages\"\"\"\n",
    "    def __init__(self, loan, annRate, months):\n",
    "        \"\"\"Assumes: loan and annRate are floats, months an int\n",
    "        Creates a new mortgage of size loan, duration months, and\n",
    "        annual rate annRate\"\"\"\n",
    "        self.loan = loan\n",
    "        self.rate = annRate/12\n",
    "        self.months = months\n",
    "        self.paid = [0.0]\n",
    "        self.outstanding = [loan]\n",
    "        self.payment = self.findPayment(loan, self.rate, months)\n",
    "        self.legend = None #description of mortgage\n",
    "        \n",
    "    def makePayment(self):\n",
    "        \"\"\"Make a payment\"\"\"\n",
    "        self.paid.append(self.payment)\n",
    "        reduction = self.payment - self.outstanding[-1]*self.rate\n",
    "        self.outstanding.append(self.outstanding[-1] - reduction)\n",
    "    \n",
    "    def getTotalPaid(self):\n",
    "        \"\"\"Return the total amount paid so far\"\"\"\n",
    "        return sum(self.paid)\n",
    "\n",
    "    def __str__(self):\n",
    "        return self.legend\n",
    "    \n",
    "    \n",
    "    def findPayment(self, loan, r, m):\n",
    "        \"\"\"Assumes: loan and r are floats, m an int\n",
    "        Returns the monthly payment for a mortgage of size\n",
    "        loan at a monthly rate of r for m months\"\"\"\n",
    "        return loan*((r*(1+r)**m)/((1+r)**m - 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "found-electron",
   "metadata": {},
   "outputs": [],
   "source": [
    "new_mortgage = "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "unusual-warren",
   "metadata": {},
   "source": [
    "# 15. Packages and modules\n",
    "Import the `os` module and use the `getcwd()` function to get your current working directory. Store this value in the variable `cwd`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cordless-carrier",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "cwd = "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "geological-booking",
   "metadata": {},
   "source": [
    "# Check your score\n",
    "That's the end! Run the cell below to check your score. If you scored 70% or more, you are ready to start MSDS600."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "split-awareness",
   "metadata": {},
   "outputs": [],
   "source": [
    "from solution.check_answers import calculate_score\n",
    "\n",
    "calculate_score(globals())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "marine-breakdown",
   "metadata": {},
   "source": [
    "If you got fewer than 5 questions correct or this took you more than an hour to complete, consider doing one of the following:\n",
    "\n",
    "- Take MSC575 Statistical Computing from Regis\n",
    "- Use online resources to learn some Python basics\n",
    "\n",
    "Some good online resources for learning Python are:\n",
    "- [Udacity: Introduction to Python Programming](https://www.udacity.com/course/introduction-to-python--ud1110)\n",
    "- [Kaggle: Python](https://www.kaggle.com/learn/overview) (not intended for complete beginners)\n",
    "- [DataQuest: Introduction to Python Programming](https://www.dataquest.io/course/introduction-to-python/)\n",
    "- [DataCamp: Python Data Fundamentals](https://www.datacamp.com/tracks/python-data-fundamentals) (intro/intermediate Python courses)\n",
    "- [Coursera: Python for Everybody Specialization](https://www.coursera.org/specializations/python)\n",
    "\n",
    "<!-- \n",
    " If you got fewer than 5 questions correct or this took you more than an hour to complete, you should consider doing one of the following:\n",
    "\n",
    "- take MSC575 Statistical Computing from Regis\n",
    "- use online resources to learn some Python basics\n",
    "\n",
    "Some good online resources for learning Python are:\n",
    "- [Udacity](https://www.udacity.com/course/introduction-to-python--ud1110)\n",
    "- [Kaggle](https://www.kaggle.com/learn/overview) (not intended for complete beginners)\n",
    "- [DataQuest](https://www.dataquest.io/course/python-for-data-science-fundamentals/)\n",
    "- [DataCamp's Python track](https://www.datacamp.com/tracks/python-fundamentals) (the intro/intermediate Python courses)\n",
    "- [Coursera](https://www.coursera.org/learn/python) -->"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2edeef50",
   "metadata": {},
   "source": []
  }
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