neila

# First subarray is arr[l..m]
# Second subarray is arr[m+1..r]
def merge(arr, l, middle, r):
    leftlength = middle - l + 1
    rightlength = r - middle

    # create temporary arrays
    left = []
    right = []

neila

######### RUN THE CODE BELOW IN R. R-STUDIO IS THE RECOMMENDED IDE. BOTH R AND R-STUDIO ARE FREE.
######### QUESTIONS SHOULD BE POSTED TO PIAZZA
######### THE ACTUAL ASSIGNMENT BEGINS ON LINE 71


#########Provided Code (some parts commented out because I didn't want it)#########

### Multilateral Development Institution Data
foo <- read.csv("https://tinyurl.com/yb4phxx8") # read in the data

neila

def increment_max(lst, prevmax):
    currentmax = prevmax
    for i in range(len(lst)):
        if sum(lst[i:len(lst)]) > currentmax:
            currentmax = sum(lst[i:len(lst)])
    return currentmax

###test####
sho = [-2,-3,4,-1,-2,1,5,-2]    #max subarray has sum 7 at sho[2:6]
increment_max(sho, 7)

neila

def swap(lst,i,j):
    lst[i],lst[j] = lst[j],lst[i]

def heapify(lst,n,i):
    root = i   # initialize root
    left = 2*i + 1  #define left child
    right = 2*i + 2  #define right child
    if left < n and lst[root] < lst[left]: #if the left child is bigger than root, switch
        root = left
    if right < n and lst[root] < lst[right]: #if the right child is bigger than root, switch

neila

def swap(lst,i,j):
    lst[i],lst[j] = lst[j],lst[i]

def heapify(lst,n,i):
    root = i   # initialize root
    left = 2*i + 1  #define left child
    right = 2*i + 2  #define right child
    if left < n and lst[root] < lst[left]: #if the left child is bigger than root, switch
        root = left
    if right < n and lst[root] < lst[right]: #if the right child is bigger than root, switch

neila

import random
import math
import matplotlib.pyplot as plt
import numpy as np

masterinterview = []
masterhire = []
for apps in range(1,1501):
    interviewlist = []
    hirelist = []

neila

import random
import numpy as np


def hatproblem(people):
    hats = [i for i in range(1,people+1)]
    hatsreplica = [i for i in range(1,people+1)]
    random.shuffle(hatsreplica)
    count = 0
    for i in range(len(hats)):

neila

import random

def check(list):
    for i in range(len(list) - 1):
        if list[i] > list[i + 1]:
            return False
    return True

def badsort(list):
    while not check(list):

neila

import random
import numpy as np

for i in range(100):
    list = [int(100*random.random()) for i in range(100)]
    sigma = random.randint(1,49)
    sigma

    low = np.percentile(list, 50-sigma)
    high = np.percentile(list, 50+sigma)

neila

def swap(lst, a, b):
    lst[a], lst[b] = lst[b], lst[a]

def median(lst):
	n = len(lst)
	return sorted(lst)[n//2]

def partition(lst,low,high):
    i = ( low-1 )
    pivot = lst[high]