3 quick sort

1.py

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+# ### Binary Search Exercise
+# 1. When I try to find number 5 in below list using binary search, it doesn't work and returns me -1 index. Why is that?
+
+#     ```numbers = [1,4,6,9,10,5,7]```
+
+# This is because the array is not sorted in order from lowest to highest. 
+# Once it splits the first time, it starts looking in the [1,4,6] range and doesn't find 5
+
+# 1. Find index of all the occurances of a number from sorted list
+
+#     ```
+#     numbers = [1,4,6,9,11,15,15,15,17,21,34,34,56]
+#     number_to_find = 15  
+#     ```
+#    This should return 5,6,7 as indices containing number 15 in the array
+
+from util import time_it
+
+@time_it
+def linear_search(numbers_list, number_to_find):
+    for index, element in enumerate(numbers_list):
+        if element == number_to_find:
+            return index
+    return -1
+
+@time_it
+def binary_search(numbers_list, number_to_find):
+    left_index = 0
+    right_index = len(numbers_list) - 1
+    mid_index = 0
+
+    while left_index <= right_index:
+        mid_index = (left_index + right_index) // 2
+        mid_number = numbers_list[mid_index]
+
+        if mid_number == number_to_find:
+            return mid_index
+
+        if mid_number < number_to_find:
+            left_index = mid_index + 1
+        else:
+            right_index = mid_index - 1
+
+    return -1
+
+def binary_search_recursive(numbers_list, number_to_find, left_index, right_index):
+    if right_index < left_index:
+        return -1
+
+    mid_index = (left_index + right_index) // 2
+    if mid_index >= len(numbers_list) or mid_index < 0:
+        return -1
+
+    mid_number = numbers_list[mid_index]
+
+    if mid_number == number_to_find:
+        return mid_index
+
+    if mid_number < number_to_find:
+        left_index = mid_index + 1
+    else:
+        right_index = mid_index - 1
+
+    return binary_search_recursive(numbers_list, number_to_find, left_index, right_index)
+
+#this should run the binary search, find the index, and then recursively run the search on both the right and left side
+def binary_search_multiple(numbers_list, number_to_find):
+
+    index = binary_search(numbers_list,number_to_find)
+    result_indices = [index]
+
+    # find all indices on the left
+    i = index - 1
+    while i>=0:
+        if numbers_list[i] == numbers_list[index]:
+            result_indices.append(i)
+        else:
+            break
+        i = i-1
+
+    # find all indices on the right
+    i = index + 1
+    while i<len(numbers_list):
+        if numbers_list[i] == numbers_list[index]:
+            result_indices.append(i)
+        else:
+            break
+        i = i+1
+
+    return sorted(result_indices)
+
+numbers_list = [12, 15, 17, 19, 21, 21, 21, 21, 24, 45, 67]
+number_to_find = 21
+
+index = binary_search_multiple(numbers_list, number_to_find)
+print(f"Number found at index {index} using binary search")
+
+numbers = [1,4,6,9,11,15,15,15,15,17,21,34,34,56]
+number_to_find = 15
+
+index = binary_search_multiple(numbers, number_to_find)
+print(f"Number found at index {index} using binary search")
+
+#Lesson: I was approaching it wrong. If something isn't working, scratch the approach. 
+#Lesson #2: Try the simplest solution first. Although in this case it's a bit ugly since you're just doing a linear search after your binary search

2.py

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+# ### Bubble Sort Exercise
+
+# Modify [bubble_sort function](https://github.com/codebasics/data-structures-algorithms-python/blob/master/algorithms/2_BubbleSort/bubble_sort.py) such that it can sort following list of transactions happening in an electronic store,
+# ```
+# elements = [
+#         { 'name': 'mona',   'transaction_amount': 1000, 'device': 'iphone-10'},
+#         { 'name': 'dhaval', 'transaction_amount': 400,  'device': 'google pixel'},
+#         { 'name': 'kathy',  'transaction_amount': 200,  'device': 'vivo'},
+#         { 'name': 'aamir',  'transaction_amount': 800,  'device': 'iphone-8'},
+#     ]
+# ``` 
+# bubble_sort function should take key from a transaction record and sort the list as per that key. For example,
+# ```
+# bubble_sort(elements, key='transaction_amount')
+# ```
+# This will sort elements by transaction_amount and your sorted list will look like,
+# ```
+# elements = [
+#         { 'name': 'kathy',  'transaction_amount': 200,  'device': 'vivo'},
+#         { 'name': 'dhaval', 'transaction_amount': 400,  'device': 'google pixel'},
+#         { 'name': 'aamir',  'transaction_amount': 800,  'device': 'iphone-8'},
+#         { 'name': 'mona',   'transaction_amount': 1000, 'device': 'iphone-10'},
+#     ]
+# ``` 
+# But if you call it like this,
+# ```
+# bubble_sort(elements, key='name')
+# ```
+# output will be,
+# ```
+# elements = [
+#         { 'name': 'aamir',  'transaction_amount': 800,  'device': 'iphone-8'},
+#         { 'name': 'dhaval', 'transaction_amount': 400,  'device': 'google pixel'},
+#         { 'name': 'kathy',  'transaction_amount': 200,  'device': 'vivo'},
+#         { 'name': 'mona',   'transaction_amount': 1000, 'device': 'iphone-10'},
+#     ]
+# ``` 
+
+# base bubble_sort. you can use this to sort strings too
+def bubble_sort(elements):
+    size = len(elements)
+
+    for i in range(size-1):
+        swapped = False
+        for j in range(size-1-i):
+            if elements[j] > elements[j+1]:
+                tmp = elements[j]
+                elements[j] = elements[j+1]
+                elements[j+1] = tmp
+                swapped = True
+
+        if not swapped:
+            break
+
+def bubble_sort_by_key(elements, key):
+    size = len(elements)
+
+    for i in range(size-1):
+        swapped = False
+        for j in range(size-1-i):
+            if elements[j][key] > elements[j+1][key]:
+                tmp = elements[j]
+                elements[j] = elements[j+1]
+                elements[j+1] = tmp
+                swapped = True
+
+        if not swapped:
+            break
+
+
+elements = [5,9,2,1,67,34,88,34]
+elements = [1,2,3,4,2]
+elements = ["mona", "dhaval", "aamir", "tina", "chang"]
+
+bubble_sort(elements)
+print(elements)
+
+elements2 = [ { 'name': 'kathy',  'transaction_amount': 200,  'device': 'vivo'},
+        { 'name': 'dhaval', 'transaction_amount': 400,  'device': 'google pixel'},
+        { 'name': 'aamir',  'transaction_amount': 800,  'device': 'iphone-8'},
+        { 'name': 'mona',   'transaction_amount': 1000, 'device': 'iphone-10'},
+    ]
+bubble_sort_by_key(elements2,key='transaction_amount')
+print(elements2)

3.py

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+def swap(a, b, arr):
+    if a!=b:
+        tmp = arr[a]
+        arr[a] = arr[b]
+        arr[b] = tmp
+
+# Sorts a (portion of an) array, divides it into partitions, then sorts those
+def quicksort(A, lo, hi):
+  if lo >= 0 and lo < hi:
+    lt, gt = partition(A, lo, hi) # Multiple return values
+    quicksort(A, lo, lt - 1)
+    quicksort(A, gt + 1, hi)
+
+# Divides array into three partitions
+def partition(A, lo, hi):
+  # Pivot value
+  pivot = A[(lo + hi) // 2] # Choose the middle element as the pivot (integer division)
+
+  # Lesser, equal and greater index
+  lt = lo
+  eq = lo
+  gt = hi
+
+  # Iterate and compare all elements with the pivot
+
+  while eq <= gt:
+    if A[eq] < pivot:
+        # Swap the elements at the equal and lesser indices
+        swap(eq, lt, A)
+        # Increase lesser index
+        lt += 1
+        # Increase equal index
+        eq += 1
+    elif A[eq] > pivot:
+        # Swap the elements at the equal and greater indices
+        swap(eq, gt, A)
+        # Decrease greater index
+        gt -= 1
+    else:  # A[eq] == pivot
+        # Increase equal index
+        eq += 1
+
+  # Return lesser and greater indices
+  return lt, gt
+
+elements = [11,9,29,7,2,15,28]
+# elements = ["mona", "dhaval", "aamir", "tina", "chang"]
+quicksort(elements, 0, len(elements)-1)
+print(elements)
+
+tests = [
+        [11,9,29,7,2,15,28],
+        [3, 7, 9, 11],
+        [25, 22, 21, 10],
+        [29, 15, 28],
+        [],
+        [6]
+]
+
+try:
+    # Your script's entry point, e.g., function calls
+    for elements in tests:
+        quicksort(elements, 0, len(elements)-1)
+        print(f'sorted array: {elements}')
+except Exception as e:
+    print(f"Error occurred: {e}")

4.py

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+# ### Exercise: Insertion Sort
+
+# Compute the running median of a sequence of numbers. That is, given a stream of numbers, print out the median of the list so far on each new element.
+
+# Recall that the median of an even-numbered list is the average of the two middle numbers in a *sorted list*.
+
+# For example, given the sequence `[2, 1, 5, 7, 2, 0, 5]`, your algorithm should print out:
+
+# ```
+# 2
+# 1.5
+# 2
+# 3.5
+# 2
+# 2
+# 2
+# ```
+
+def find_median_value(elements):
+    if len(elements) == 1: #if the array has 1 element
+        return elements[0]
+    if len(elements) % 2 != 0: #if the array has an odd number of elements
+        return elements[(len(elements)//2)]
+    else: #if the array has an even number of elements
+        return ((elements[int(len(elements)/2)]+elements[int(len(elements)/2-1)])/2)
+
+def insertion_sort(elements):
+    for i in range(1, len(elements)):
+        print(find_median_value(elements[0:i]))
+        anchor = elements[i]
+        j = i - 1
+        while j>=0 and anchor < elements[j]:
+            elements[j+1] = elements[j]
+            j = j - 1
+        elements[j+1] = anchor
+    print(find_median_value(elements))
+
+# print (find_median_value([1,2,3,4,5,7,20,33,34]))
+# print (find_median_value([1,2,3,4,8,7,20,33]))
+
+elements = [2, 1, 5, 7, 2, 0, 5]
+# print(elements[0:1])
+insertion_sort(elements)
+print(elements)