hw02

pdf

School

University of California, Berkeley *

*We aren’t endorsed by this school

Course

C100

Subject

Computer Science

Date

Feb 20, 2024

Type

pdf

Pages

Uploaded by CoachScienceRook44

hw02 February 4, 2024 [ ]: # Initialize Otter import otter grader = otter . Notebook( "hw02.ipynb" ) 1 Homework 2: Arrays and Tables Please complete this notebook by filling in the cells provided. Before you begin, execute the previous cell to load the provided tests. [ ]: # Run this cell and ignore the output. It is checking to see if you ran the ␣ ↪ first cell! # If you get a NameError, please run the cell at the very TOP of this notebook! grader Helpful Resource: - Python Reference : Cheat sheet of helpful array & table methods used in Data 8! Recommended Readings: - Arrays - What is Data Science? - Causality and Experiments - Programming in Python For all problems that you must write explanations and sentences for, you must provide your answer in the designated space. Moreover, throughout this homework and all future ones, please be sure to not re-assign variables throughout the notebook! For example, if you use max_temperature in your answer to one question, do not reassign it later on. Otherwise, you will fail tests that you thought you were passing previously! Note: This homework has hidden tests on it. That means even though tests may say 100% passed, it doesn’t mean your final grade will be 100%. We will be running more tests for correctness once everyone turns in the homework. Directly sharing answers is not okay, but discussing problems with the course staff or with other students is encouraged. Refer to the policies page to learn more about how to learn cooperatively. You should start early so that you have time to get help if you’re stuck. 1

1.1 1. Creating Arrays [ ]: # Run this cell to set up the notebook, but please don't change it. import numpy as np from datascience import * import d8error import warnings warnings . simplefilter( 'ignore' , FutureWarning ) Question 1. Make an array called weird_numbers containing the following numbers (in the given order) (4 Points) : 1. -2 2. the floor of 12.6 3. 3 4. 5 to the power of the ceil of 5.3 Hint: floor and ceil are functions in the math module. Importing modules is covered in Lab 2! Note: Python lists are different/behave differently than NumPy arrays. In Data 8, we use NumPy arrays, so please make an array , not a Python list. [ ]: # Our solution involved one extra line of code before creating # weird_numbers. ... weird_numbers = ... weird_numbers [ ]: grader . check( "q1_1" ) Question 2. Make an array called book_title_words containing the following three strings: “Eats”, “Shoots”, and “and Leaves”. (4 Points) [ ]: book_title_words = ... book_title_words [ ]: grader . check( "q1_2" ) Strings have a method called join . join takes one argument, an array of strings. It returns a single string. Specifically, the value of a_string.join(an_array) is a single string that’s the concatenation (“putting together”) of all the strings in an_array , except a_string is inserted in between each string. Question 3. Use the array book_title_words and the method join to make two strings (4 Points) : 1. “Eats, Shoots, and Leaves” (call this one with_commas ) 2. “Eats Shoots and Leaves” (call this one without_commas ) 2

Hint: If you’re not sure what join does, first try just calling, for example, "data8".join(book_title_words) . [ ]: with_commas = ... without_commas = ... # These lines are provided just to print out your answers. print ( 'with_commas:' , with_commas) print ( 'without_commas:' , without_commas) [ ]: grader . check( "q1_3" ) 1.2 2. Indexing Arrays These exercises give you practice accessing individual elements of arrays. In Python (and in many programming languages), each element is accessed by its index ; for example, the first element is the element at index 0. Indices must be integers . Note: If you have previous coding experience, you may be familiar with bracket notation. DO NOT use bracket notation when indexing (i.e. arr[0] ), as this can yield different data type outputs than what we will be expecting. This can cause you to fail an autograder test. Be sure to refer to the Python Reference on the website if you feel stuck! Question 1. The cell below creates an array of some numbers. Set third_element to the third element of some_numbers . (4 Points) [ ]: some_numbers = make_array( -1 , -3 , -6 , -10 , -15 ) third_element = ... third_element [ ]: grader . check( "q2_1" ) Question 2. The next cell creates a table that displays some information about the elements of some_numbers and their order. Run the cell to see the partially-completed table, then fill in the missing information (the cells that say “Ellipsis”) by assigning blank_a , blank_b , blank_c , and blank_d to the correct elements in the table. (4 Points) Hint: Replace the ... with strings or numbers. As a reminder, indices should be integers . [ ]: blank_a = ... blank_b = ... blank_c = ... blank_d = ... elements_of_some_numbers = Table() . with_columns( "English name for position" , make_array( "first" , "second" , blank_a, ␣ ↪ blank_b, "fifth" ), "Index" , make_array(blank_c, 1 , 2 , blank_d, 4 ), 3

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

"Element" , some_numbers) elements_of_some_numbers [ ]: grader . check( "q2_2" ) Question 3. You’ll sometimes want to find the last element of an array. Suppose an array has 142 elements. What is the index of its last element? (4 Points) [ ]: index_of_last_element = ... [ ]: grader . check( "q2_3" ) More often, you don’t know the number of elements in an array, its length . (For example, it might be a large dataset you found on the Internet.) The function len takes a single argument, an array, and returns an integer that represents the len gth of that array. Question 4. The cell below loads an array called president_birth_years . Calling tbl.column(...) on a table returns an array of the column specified, in this case the Birth Year column of the president_births table. The last element in that array is the most recent among the birth years of all the deceased Presidents. Assign that year to most_recent_birth_year . (4 Points) [ ]: president_birth_years = Table . read_table( "president_births.csv" ) . column( 'Birth ␣ ↪ Year' ) most_recent_birth_year = ... most_recent_birth_year [ ]: grader . check( "q2_4" ) Question 5. Finally, assign min_of_birth_years to the minimum of the first, sixteenth, and last birth years listed in president_birth_years . (4 Points) [ ]: min_of_birth_years = ... min_of_birth_years [ ]: grader . check( "q2_5" ) 1.3 3. Basic Array Arithmetic Question 1. Multiply the numbers 42, -4224, 424224242, and 250 by 157. Assign each variable below such that first_product is assigned to the result of 42 ∗ 157 , second_product is assigned to the result of −4224 ∗ 157 , and so on. (4 Points) Note : For this question, don’t use arrays. [ ]: first_product = ... second_product = ... third_product = ... 4

fourth_product = ... print ( "First Product:" , first_product) print ( "Second Product:" , second_product) print ( "Third Product:" , third_product) print ( "Fourth Product:" , fourth_product) [ ]: grader . check( "q3_1" ) Question 2. Now, do the same calculation, but using an array called numbers and only a single multiplication ( * ) operator. Store the 4 results in an array named products . (4 Points) [ ]: numbers = ... products = ... products [ ]: grader . check( "q3_2" ) Question 3. Oops, we made a typo! Instead of 157, we wanted to multiply each number by 1577. Compute the correct products in the cell below using array arithmetic. Notice that your job is really easy if you previously defined an array containing the 4 numbers. (4 Points) [ ]: correct_products = ... correct_products [ ]: grader . check( "q3_3" ) Question 4. We’ve loaded an array of temperatures in the next cell. Each number is the highest temperature observed on a day at a climate observation station, mostly from the US. Since they’re from the US government agency NOAA , all the temperatures are in Fahrenheit. Convert all the temperatures to Celsius by first subtracting 32 from them, then multiplying the results by 5 9 , i.e. 𝐶 = (𝐹 − 32) ∗ 5 9 . After converting the temperatures to Celsius, make sure to ROUND the final result to the nearest integer using the np.round function. (4 Points) [ ]: max_temperatures = Table . read_table( "temperatures.csv" ) . column( "Daily Max ␣ ↪ Temperature" ) celsius_max_temperatures = ... celsius_max_temperatures [ ]: grader . check( "q3_4" ) Question 5. The cell below loads all the lowest temperatures from each day (in Fahrenheit). Compute the daily temperature range for each day. That is, compute the difference between each daily maximum temperature and the corresponding daily minimum temperature. Pay attention to the units and give your answer in Celsius! Make sure NOT to round your answer for this question! (4 Points) 5

Note: Remember that in Question 4, celsius_max_temperatures was rounded, so you might not want to use that variable in this question. [ ]: min_temperatures = Table . read_table( "temperatures.csv" ) . column( "Daily Min ␣ ↪ Temperature" ) celsius_temperature_ranges = ... celsius_temperature_ranges [ ]: grader . check( "q3_5" ) 1.4 4. Old Faithful Old Faithful is a geyser in Yellowstone that erupts every 44 to 125 minutes (according to Wikipedia ). People are often told that the geyser erupts every hour , but in fact the waiting time between eruptions is more variable. Let’s take a look. Question 1. The first line below assigns waiting_times to an array of 272 consecutive waiting times between eruptions, taken from a classic 1938 dataset. Assign the names shortest , longest , and average so that the print statement is correct. (4 Points) [ ]: waiting_times = Table . read_table( 'old_faithful.csv' ) . column( 'waiting' ) shortest = ... longest = ... average = ... print ( "Old Faithful erupts every" , shortest, "to" , longest, "minutes and ␣ ↪ every" , average, "minutes on average." ) [ ]: grader . check( "q4_1" ) Question 2. Assign biggest_decrease to the biggest decrease in waiting time between two consecutive eruptions. For example, the third eruption occurred after 74 minutes and the fourth after 62 minutes, so the decrease in waiting time was 74 - 62 = 12 minutes. (4 Points) Hint : We want to return the absolute value of the biggest decrease. Note : np.diff() calculates the difference between subsequent values in an array. For example, calling np.diff() on the array make_array(1, 8, 3, 5) evaluates to array([8 - 1, 3 - 8, 5 - 3]) , or array([7, -5, 2]) . [ ]: # np.diff() calculates the difference between subsequent values # in a NumPy array. differences = np . diff(waiting_times) biggest_decrease = ... biggest_decrease [ ]: grader . check( "q4_2" ) 6

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

Question 3. The faithful_with_eruption_nums table contains two columns: eruption_number , which represents the number of that eruption, and waiting , which represents the time spent waiting after that eruption. For example, take the first two rows of the table: eruption number waiting 1 79 2 54 We can read this as follows: after the first eruption, we waited 79 minutes for the second eruption. Then, after the second eruption, we waited 54 minutes for the third eruption. Suppose Oscar and Wendy started watching Old Faithful at the start of the first eruption. Assume that they watch until the end of the tenth eruption. For some of that time they will be watching eruptions, and for the rest of the time they will be waiting for Old Faithful to erupt. How many minutes will they spend waiting for eruptions? (4 Points) Hint #1: One way to approach this problem is to use the take or where method on the table faithful_with_eruption_nums . Hint #2: first_nine_waiting_times must be an array. [ ]: # The following two lines load in our faithful_with_eruption_nums table faithful = Table . read_table( 'old_faithful.csv' ) . drop( "eruptions" ) faithful_with_eruption_nums = faithful . with_column( "eruption number" , np . ↪ arange(faithful . num_rows) + 1 ) . select( 1 , 0 ) first_nine_waiting_times = ... total_waiting_time_until_tenth = ... total_waiting_time_until_tenth [ ]: grader . check( "q4_3" ) Question 4. Let’s imagine your guess for the next waiting time was always just the length of the previous waiting time. If you always guessed the previous waiting time, how big would your error in guessing the waiting times be, on average? (4 Points) For example, since the first four waiting times are 79, 54, 74, and 62, the average difference be- tween your guess and the actual time for just the second, third, and fourth eruptions would be |79−54|+|54−74|+|74−62| 3 = 19 . [ ]: differences = np . diff(waiting_times) average_error = ... average_error [ ]: grader . check( "q4_4" ) 7

1.5 5. Tables Question 1. Suppose you have 4 apples, 3 oranges, and 3 pineapples. (Perhaps you’re using Python to solve a high school Algebra problem.) Create a table that contains this information. It should have two columns: fruit name and count . Assign the new table to the variable fruits . (4 Points) Note: Use lower-case and singular words for the name of each fruit, like "apple" . [ ]: # Our solution uses 1 statement split over 3 lines. fruits = ... ... ... fruits [ ]: grader . check( "q5_1" ) Question 2. The file inventory.csv contains information about the inventory at a fruit stand. Each row represents the contents of one box of fruit. Load it as a table named inventory using the Table.read_table() function. Table.read_table(...) takes one argument (data file name in string format) and returns a table. (4 Points) [ ]: inventory = ... inventory [ ]: grader . check( "q5_2" ) Question 3. Does each box at the fruit stand contain a different fruit? Set all_different to True if each box contains a different fruit or to False if multiple boxes contain the same fruit. (4 Points) Hint: You don’t have to write code to calculate the True/False value for all_different . Just look at the inventory table and assign all_different to either True or False according to what you can see from the table in answering the question. [ ]: all_different = ... all_different [ ]: grader . check( "q5_3" ) Question 4. The file sales.csv contains the number of fruit sold from each box last Saturday. It has an extra column called price per fruit ($) that’s the price per item of fruit for fruit in that box. The rows are in the same order as the inventory table. Load these data into a table called sales . (5 Points) [ ]: sales = ... sales [ ]: grader . check( "q5_4" ) 8

Question 5. How many fruits did the store sell in total on that day? (5 Points) [ ]: total_fruits_sold = ... total_fruits_sold [ ]: grader . check( "q5_5" ) Question 6. What was the store’s total revenue (the total price of all fruits sold) on that day? (5 Points) Hint: If you’re stuck, think first about how you would compute the total revenue from just the grape sales. [ ]: total_revenue = ... total_revenue [ ]: grader . check( "q5_6" ) Question 7. Make a new table called remaining_inventory . It should have the same rows and columns as inventory , except that the amount of fruit sold from each box should be subtracted from that box’s original count, so that the count column is updated to be the amount of fruit remaining after Saturday. (5 Points) [ ]: remaining_inventory = ... ... ... ... remaining_inventory [ ]: grader . check( "q5_7" ) You’re done with Homework 2! Important submission steps: 1. Run the tests and verify that they all pass. 2. Choose Save Notebook from the File menu, then run the final cell . 3. Click the link to download the zip file. 4. Then submit the zip file to the corresponding assignment according to your instructor’s directions. It is your responsibility to make sure your work is saved before running the last cell. 1.6 Submission Make sure you have run all cells in your notebook in order before running the cell below, so that all images/graphs appear in the output. The cell below will generate a zip file for you to submit. Please save before exporting! [ ]: # Save your notebook first, then run this cell to export your submission. grader . export(pdf = False , run_tests = True ) 9

Your preview ends here

Eager to read complete document? Join bartleby learn and gain access to the full version

Access to all documents
Unlimited textbook solutions
24/7 expert homework help

hw02

Related Documents