{ "cells": [ { "attachments": {}, "cell_type": "markdown", "metadata": { "nbgrader": { "grade": false, "locked": true, "solution": false } }, "source": [ "# Exercises\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "You can easily start a live Jupyter session in the cloud directly from this book. To do this, just click on the Launch Button ({fa}`rocket`) located above on this page.\n", "\n", "You have a few options to choose from:\n", "\n", "1. Launch on Binder: By selecting this option, you can instantly launch a live Jupyter session using Binder.\n", "2. Launch on Google Colab: This option allows you to launch a live Jupyter session using Google Colab.\n", "\n", "Alternatively, you can also click on the *Jupyter Lite session* link, which will open a new tab where you can freely write and run your code." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "tags": [ "remove-input" ] }, "outputs": [], "source": [ "# ##-On Google colab uncomment and run the following code\n", "# ## to install and import the function that will be used to check your answers.\n", "# !pip install learn-python-check\n", "\n", "# ##-On Binder just uncomment and run the following line\n", "# import learn_python_check.check_answers as check" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "`````{admonition} Open the Python Calculator for this page\n", ":class: tip, dropdown\n", "Click this link and wait until the message \"You may begin!\" is printed to start evaluating code. More information about this tool can be found [here](calculator). \n", "\n", "Remember that most pages in this course can also be run interactively using the {fa}rocket icon above (read more about it [here](toolbox)).\n", "`````" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "nbgrader": { "grade": false, "locked": true, "solution": false } }, "source": [ "## Exercise 3.1.1\n", "\n", "Use the print() function and an f-string to make a statement about some car using all variables stored in the car_info dictionary.\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "_Type your code here where the three (*`...`*) dots are placed. Do not change the name of the variables._\n" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "collapsed": true }, "outputs": [], "source": [ "car_info = {\n", " 'top_speed' : '229', #km/h\n", " 'type' : 'Opel Astra'\n", "}\n", "\n", "message = ...\n" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "````{admonition} check your answer!\n", "To check your answer in a _Jupyter Lite session_, simply run the following line of code immediately after your code implementation. \n", "\n", "If your are in _Google Colab_ just run the cell bellow.\n", "````" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "check.notebook_3(question_number=0, arguments=[car_info, message])" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "nbgrader": { "grade": false, "locked": true, "solution": false } }, "source": [ "## Exercise 3.2.1\n", "\n", "Write a lambda function that converts a number from degrees to radians.\n", "\n", "_Type your code here where the three (*`...`*) dots are placed. Do not change the name of the variables._" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from math import pi \n", "\n", "DegToRad = ...\n", "\n", "angle = 20 # Degrees\n", "print(f\"An angle of {angle} Degrees is equal to {DegToRad(angle):.3f} radians\")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "````{admonition} check your answer!\n", "To check your answer in a _Jupyter Lite session_, simply run the following line of code immediately after your code implementation. \n", "\n", "If your are in _Google Colab_ just run the cell bellow.\n", "````" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "check.notebook_3(question_number=1, arguments=[angle,DegToRad])" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "nbgrader": { "grade": false, "locked": true, "solution": false } }, "source": [ "## Exercise 3.2.2\n", "\n", "Write a lambda function that takes four inputs: $(x_1, y_1, x_2, y_2)$ and computes the Euclidian distance between point 1 $(x_1,y_1)$ and point 2 $(x_2,y_2)$.\n", "\n", "_Type your code here where the three (*`...`*) dots are placed. Do not change the name of the variables._\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "from math import sqrt\n", "\n", "distance = ...\n", "\n", "\n", "x1, y1 = 1, 1\n", "x2, y2 = 4, 4\n", "\n", "print(f\"Distance between points ({x1}, {y1}) and ({x2}, {y2}) is {distance(x1, y1, x2, y2):.3f}\")" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "````{admonition} check your answer!\n", "To check your answer in a _Jupyter Lite session_, simply run the following line of code immediately after your code implementation. \n", "\n", "If your are in _Google Colab_ just run the cell bellow.\n", "````" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "check.notebook_3(question_number=2, arguments=[distance])" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "nbgrader": { "grade": false, "locked": true, "solution": false } }, "source": [ "## (Fixing) Exercise 3.4.1\n", "\n", "Fix the syntax errors so it prints \"AES\" without removing the variable that holds it. You'll need to fix 2 errors." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def get_abbreviation():\n", " my abbreviation = \"AES\"\n", " return my abbreviation\n", " \n", "print(get_abbreviation())" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "````{admonition} check your answer!\n", "To check your answer in a _Jupyter Lite session_, simply run the following line of code immediately after your code implementation. \n", "\n", "If your are in _Google Colab_ just run the cell bellow.\n", "````" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "check.notebook_3(question_number=3, arguments=[get_abbreviation])" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "nbgrader": { "grade": false, "locked": true, "solution": false } }, "source": [ "## (Fixing) Exercise 3.4.2\n", "\n", "Solve the runtime error so all values of $B$ are printed. The output after running create_string_from_lists() should be the following:
\n", "\n", "A[0] = 2\n", "B[0] = 5\n", "A[1] = 3\n", "B[1] = 6\n", "A[2] = 4\n", "B[2] = 7\n", "B[3] = 8\n", "" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def create_string_from_lists():\n", " s = \"\"\n", " \n", " A = [2, 3, 4]\n", " B = [5, 6, 7, 8]\n", " for i in range(4):\n", " s += f\"A[{i}] = {A[i]}\\n\"\n", " s += f\"B[{i}] = {B[i]}\\n\"\n", " print(s)\n", "\n", "\n", "create_string_from_lists()" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "````{admonition} check your answer!\n", "To check your answer in a _Jupyter Lite session_, simply run the following line of code immediately after your code implementation. \n", "\n", "If your are in _Google Colab_ just run the cell bellow.\n", "````" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "check.notebook_3(question_number=4, arguments=[create_string_from_lists])" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": { "nbgrader": { "grade": false, "locked": true, "solution": false } }, "source": [ "## (Fixing) Exercise 3.4.3\n", "\n", "Find the semantic error in this function:" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "collapsed": true }, "outputs": [], "source": [ "def factorial(x):\n", " \"returns the factorial of x\"\n", " if x == 0:\n", " return 1\n", " else: \n", " return x ** factorial(x-1)\n", "\n", "factorial(4)" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "````{admonition} check your answer!\n", "To check your answer in a _Jupyter Lite session_, simply run the following line of code immediately after your code implementation. \n", "\n", "If your are in _Google Colab_ just run the cell bellow.\n", "````" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "check.notebook_3(question_number=5, arguments=[factorial])" ] } ], "metadata": { "kernelspec": { "display_name": "base", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.13" }, "latex_envs": { "LaTeX_envs_menu_present": true, "autoclose": false, "autocomplete": true, "bibliofile": "biblio.bib", "cite_by": "apalike", "current_citInitial": 1, "eqLabelWithNumbers": true, "eqNumInitial": 1, "hotkeys": { "equation": "Ctrl-E", "itemize": "Ctrl-I" }, "labels_anchors": false, "latex_user_defs": false, "report_style_numbering": false, "user_envs_cfg": false } }, "nbformat": 4, "nbformat_minor": 2 }