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Complete TODO implementations in Problem Solving Patterns notebook #1

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11979ec
Checkpoint from VS Code for coding agent session
emaverick2001 Dec 19, 2025
e307e01
Complete TODO items: implement Pangram and fix Reverse Vowels solutions
Copilot Dec 19, 2025
ad17673
Fix spelling: psuedocode -> pseudocode
Copilot Dec 19, 2025
d50f76d
Add hash table/dictionary implementation with comprehensive examples …
emaverick2001 Dec 24, 2025
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1,055 changes: 937 additions & 118 deletions Datastructures + Algorithms/0_Problem_Solving_Patterns.ipynb
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Empty file removed Datastructures + Algorithms/10_graph.ipynb
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570 changes: 570 additions & 0 deletions Datastructures + Algorithms/1a_strings.ipynb
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465 changes: 211 additions & 254 deletions ...tures + Algorithms/1a_lists_strings.ipynb → Datastructures + Algorithms/1b_lists.ipynb
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142 changes: 21 additions & 121 deletions Datastructures + Algorithms/1b_sets.ipynb → Datastructures + Algorithms/1c_sets.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -65,29 +65,15 @@
"# Methods / Operations"
]
},
{
"cell_type": "markdown",
"id": "b682a1d6",
"metadata": {},
"source": [
"- Access an element from the array"
]
},
{
"cell_type": "markdown",
"id": "daea8755",
"metadata": {},
"source": [
"## .add(x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "d7834953",
"metadata": {},
"outputs": [],
"source": [
"## .add(x)\n",
"\n",
"# Add single element - O(1)\n",
"fruits = {'apple', 'banana', 'cherry'}\n",
"fruits.add('orange')\n",
Expand All @@ -97,21 +83,15 @@
"print(fruits)"
]
},
{
"cell_type": "markdown",
"id": "88b14760",
"metadata": {},
"source": [
"## .update(x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "42fcf8cf",
"metadata": {},
"outputs": [],
"source": [
"## .update(x)\n",
"\n",
"# Add multiple elements - O(k)\n",
"fruits.update(['mango', 'grape'])\n",
"print(fruits)\n",
Expand All @@ -121,21 +101,15 @@
"print(fruits)"
]
},
{
"cell_type": "markdown",
"id": "beb13645",
"metadata": {},
"source": [
"## .remove(x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c87f3d47",
"metadata": {},
"outputs": [],
"source": [
"## .remove(x)\n",
"\n",
"\"\"\"\n",
"### .remove(x)\n",
"\n",
Expand All @@ -151,21 +125,15 @@
"# fruits.remove('grape') # KeyError: 'grape'"
]
},
{
"cell_type": "markdown",
"id": "dea6410d",
"metadata": {},
"source": [
"## .discard(x)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "26dd28ed",
"metadata": {},
"outputs": [],
"source": [
"## .discard(x)\n",
"\n",
"\"\"\"\n",
"### .discard(x)\n",
"\n",
Expand All @@ -182,21 +150,15 @@
"print(fruits) # {'apple', 'cherry'}"
]
},
{
"cell_type": "markdown",
"id": "5f42fda1",
"metadata": {},
"source": [
"## .pop()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "639bc10d",
"metadata": {},
"outputs": [],
"source": [
"## .pop()\n",
"\n",
"\"\"\"\n",
"### .pop()\n",
"\n",
Expand All @@ -214,17 +176,9 @@
"# fruits.pop() # KeyError: 'pop from an empty set'"
]
},
{
"cell_type": "markdown",
"id": "bc3fee5e",
"metadata": {},
"source": [
"## .clear()"
]
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "9b570bce",
"metadata": {},
"outputs": [
Expand All @@ -238,6 +192,8 @@
}
],
"source": [
"## .clear()\n",
"\n",
"\"\"\"\n",
"### .clear()\n",
"\n",
Expand All @@ -251,21 +207,14 @@
"print(len(fruits)) # 0"
]
},
{
"cell_type": "markdown",
"id": "994e0c62",
"metadata": {},
"source": [
"## in / not in"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7442d5bf",
"metadata": {},
"outputs": [],
"source": [
"## in / not in\n",
"\"\"\"\n",
"### in / not in\n",
"\n",
Expand All @@ -283,21 +232,14 @@
"print('apple' in fruits_list) # True, but O(n)"
]
},
{
"cell_type": "markdown",
"id": "5863a494",
"metadata": {},
"source": [
"## .union()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "46887656",
"metadata": {},
"outputs": [],
"source": [
"## .union()\n",
"\"\"\"\n",
"### .union() / |\n",
"\n",
Expand All @@ -321,21 +263,14 @@
"print(union3) # {1, 2, 3, 4, 5, 6}"
]
},
{
"cell_type": "markdown",
"id": "448d41d1",
"metadata": {},
"source": [
"## .intersection()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "38312cb6",
"metadata": {},
"outputs": [],
"source": [
"## .intersection()\n",
"\"\"\"\n",
"### .intersection() / &\n",
"\n",
Expand All @@ -359,21 +294,14 @@
"print(intersection3) # {4}"
]
},
{
"cell_type": "markdown",
"id": "0de58e7c",
"metadata": {},
"source": [
"## .difference()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "23930ef8",
"metadata": {},
"outputs": [],
"source": [
"## .difference()\n",
"\"\"\"\n",
"### .difference() / -\n",
"\n",
Expand Down Expand Up @@ -401,21 +329,14 @@
"print(diff4) # {1}"
]
},
{
"cell_type": "markdown",
"id": "878fb1a9",
"metadata": {},
"source": [
"## .symmetric_difference() / ^"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "584dfa75",
"metadata": {},
"outputs": [],
"source": [
"## .symmetric_difference() / ^\n",
"\"\"\"\n",
"### .symmetric_difference() / ^\n",
"\n",
Expand All @@ -437,21 +358,14 @@
"print(set1 ^ set2 == set2 ^ set1) # True"
]
},
{
"cell_type": "markdown",
"id": "2a373278",
"metadata": {},
"source": [
"## .issubset() / <="
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c10c368c",
"metadata": {},
"outputs": [],
"source": [
"## .issubset() / <=\n",
"\"\"\"\n",
"### .issubset() / <=\n",
"\n",
Expand All @@ -473,21 +387,14 @@
"print(set().issubset(set1)) # True"
]
},
{
"cell_type": "markdown",
"id": "1b19f1a8",
"metadata": {},
"source": [
"## .issuperset() / >="
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2a6cda23",
"metadata": {},
"outputs": [],
"source": [
"## .issuperset() / >=\n",
"\"\"\"\n",
"### .issuperset() / >=\n",
"\n",
Expand All @@ -508,21 +415,14 @@
"print(set1.issuperset(set())) # True"
]
},
{
"cell_type": "markdown",
"id": "db339c1b",
"metadata": {},
"source": [
"## .isdisjoint()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b768920c",
"metadata": {},
"outputs": [],
"source": [
"## .isdisjoint()\n",
"\"\"\"\n",
"### .isdisjoint()\n",
"\n",
Expand Down
0 Datastructures + Algorithms/1c_tuples.ipynb → Datastructures + Algorithms/1d_tuples.ipynb
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