<jupyter_start><jupyter_text>Instructions**When taking this exam, you agree to follow the Duke Honor Code.**- This is a closed book exam. You can use the `help()` function, and the `?` prefix or suffix but are restricted to a SINGLE browser tab.- All necessary imports are provided. You should not need to import any other packages.- Answer all 5 questions.<jupyter_code>%matplotlib inline
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import string
import collections
import seaborn as sns
from functools import reduce
sns.set_context('notebook', font_scale=1.5)<jupyter_output><empty_output><jupyter_text>**1**. 20 pointsThe four adjacent digits in the 1000-digit number that have the greatest product are 9 × 9 × 8 × 9 = 5832.```7316717653133062491922511967442657474235534919493496983520312774506326239578318016984801869478851843858615607891129494954595017379583319528532088055111254069874715852386305071569329096329522744304355766896648950445244523161731856403098711121722383113622298934233803081353362766142828064444866452387493035890729629049156044077239071381051585930796086670172427121883998797908792274921901699720888093776657273330010533678812202354218097512545405947522435258490771167055601360483958644670632441572215539753697817977846174064955149290862569321978468622482839722413756570560574902614079729686524145351004748216637048440319989000889524345065854122758866688116427171479924442928230863465674813919123162824586178664583591245665294765456828489128831426076900422421902267105562632111110937054421750694165896040807198403850962455444362981230987879927244284909188845801561660979191338754992005240636899125607176060588611646710940507754100225698315520005593572972571636269561882670428252483600823257530420752963450```Find the thirteen adjacent digits in the 1000-digit number that have the greatest product. What is the value of this product?(Source: Project Euler Problem 8)<jupyter_code><jupyter_output><empty_output><jupyter_text>**2**. 20 pointsCount the unique words in s1, s2, and s3 combined after removing punctuation and converting to lower case.<jupyter_code>s1 = 'Twinkle, twinkle, little star, How I wonder what you are. Up above the world so high, Like a diamond in the sky. Twinkle, twinkle, little star, How I wonder what you are!'
s2 = 'Jack and Jill went up the hill, To fetch a pail of water. Jack fell down and broke his crown, And Jill came tumbling after.'
s3 = 'Oh, do you know the muffin man, The muffin man, the muffin man, Oh, do you know the muffin man, That lives on Drury Lane?'<jupyter_output><empty_output><jupyter_text>**3**. 20 pointsGenerate a DataFrame of word counts for each "document" from problem 2. Show the top 3 rows with the largest row sums.<jupyter_code><jupyter_output><empty_output><jupyter_text>**4**. 20 pointsUsing the data provided, recreate this plot.- Top row is plotted with `matplotllib` functions `plot` and `hist`- Bottom row is plotted with `seaborn` functions `kdeplot` and `regplot`![](plots.png)<jupyter_code>n = 100
xs = np.linspace(0, 4*np.pi, n)
ys = np.sin(xs) + np.random.normal(0, 0.5, n)<jupyter_output><empty_output><jupyter_text>**5** 20 pointsSum the nested list using only anonymous functions, and one or more of map, reduce and filter.<jupyter_code>xxs = [[1,2,3], [4,5,6], [7,8,9]]<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.06732792305380222, 'fraction_numerical': 0.3186053501653141, 'mean_word_length': 8.193370165745856, 'pattern_counts': {'":': 0, '<': 25, '<?xml version=': 0, '>': 25, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '6', 'dir': 'jupyter-structured-clean-dedup', 'id': '283191', 'license': 'MIT', 'n_tokens_mistral': 1771, 'n_tokens_neox': 1139, 'n_words': 314, 'path': 'exams/MockExam01.ipynb', 'repo_name': 'cliburn/sta-662-2020', 'size': '3327'}