Week 8 — collections & integration

Quiz 2 scope: Weeks 1–8 per IITM May 2026 foundation courses. Source baseline: IITM BS admissions important-dates calendar · May 2026 cycle. Times on assessments are operational conventions — verify hall ticket.

Week map

Classify → Represent → Execute → Trap-check

• Recognize: Ask: How do you reach column j of row i in a matrix list?
• Procedure: Identify outer index (row/key) then inner (col/subkey). Trace type at each level—dict vs list.
• Variations / traps: Watch for: Index order swapped in matrix access.

Formula chain (compressed)

list of dicts → nested loops over collections → mixed indexing.

1. List of dicts — [{...}, {...}] — records / rows
2. Nested access — rows[i]["key"] — index then key
3. Enumerate — for i, x in enumerate(L): — need index + value
4. Zip — zip(a, b) — parallel iteration
5. Copy trap — shallow copy shares inner refs — mutating nested structures

Deep study

Programming in Python · Week 8 — Mixed collections

Week map

Mixed structure notation

• List of dicts → table rows → [{"name": "A", "score": 90}, ...].
• Dict of lists → columns keyed by field → {"names": [...], "scores": [...]}.
• Dict of dicts → nested lookup → data[user][metric].
• Tuple in dict → immutable key bundle → {(x, y): value} for grid cells.

python
Run Inline
students = [
    {"id": 1, "grade": 85},
    {"id": 2, "grade": 91},
]
students[1]["grade"]   # 91

Access chain

python
Run Inline
matrix = [1, 2], [3, 4](/courses/may26-python/notes/1%2C%202%5D%2C%20%5B3%2C%204)
matrix[1][0]           # 3

registry = {"team": {"lead": "Sam", "size": 5}}
registry["team"]["lead"]  # 'Sam'

Common mixed patterns

Filter and collect

python
Run Inline
results = []
for row in table:
    if row["score"] >= 60:
        results.append(row["name"])

Group by key

python
Run Inline
groups = {}
for item in items:
    k = item["category"]
    if k not in groups:
        groups[k] = []
    groups[k].append(item)

Sort list of dicts (concept)

Pattern families

Easy — Nested access

Medium — Build mixed structure

Hard — Aggregate over mixed data

Worked mini-examples

python
Run Inline
books = [{"title": "A", "pages": 200}, {"title": "B", "pages": 150}]
total = 0
for b in books:
    total += b["pages"]
# total = 350

python
Run Inline
data = {"x": [1, 2], "y": [3, 4]}
data["x"].append(5)   # {"x": [1, 2, 5], "y": [3, 4]}

python
Run Inline
rows = [{"n": "a", "ok": True}, {"n": "b", "ok": False}]
passed = [r["n"] for r in rows if r["ok"]]
# ['a']

python
Run Inline
grid = {}
grid[(0, 0)] = "start"
grid[(1, 0)] = "path"
grid[(0, 0)]   # 'start'

python
Run Inline
record = {"tags": ["py", "stats"]}
record["tags"].append("ml")   # list inside dict — mutable
record["tags"][0]             # 'py'

Traps

• Wrong bracket type: d["key"] vs lst[0].
• Shallow copy of list-of-lists shares inner lists.
• Iterating dict gives keys, not values — use .values() or .items().
• Assuming all rows have same keys — missing key raises KeyError.
• Modifying list while iterating — use new list or iterate copy.

Diagnostic (try yourself)

1. Given d = {"a": [1, 2], "b": [3]}, what is d["a"][1]?
2. Build a list of dicts with keys "name" and "age" from names = ["Kim", "Lee"] and ages = [20, 22].
3. From records = [{"v": 3}, {"v": 7}, {"v": 5}], how would you find the dict with largest "v"?
4. What is data[0]["x"] if data = [{"x": 10}, {"x": 20}]?
5. Why might groups[key].append(item) require checking if key not in groups first?

ChatGPT prep archive

• Chatty reference archive

Archived import for extra depth — complements the notes above, not official IITM material.

Core concepts

• Nested list: matrix as list of rows; M[i][j] row then column.
• Dict of lists / list of dicts: common record shapes.
• Mixed iteration: outer over keys, inner over values or indices.
• Choose structure: fast lookup → dict; ordered sequence → list; fixed record → tuple.

Notation & vocabulary

Pattern families

Easy — Access nested element

Medium — Double loop aggregate

Hard — Integrate prior patterns

Drill these on the pattern atlas — filter to week 8.

Traps

• Index order swapped in matrix access.
• Mutating shared inner list across dict keys unintentionally.
• Deep copy vs shallow when resetting rows.
• Wrong loop variable used in inner body.

Retrieval prompts

1. How do you reach column j of row i in a matrix list?
2. When use dict of lists vs list of dicts?
3. What goes wrong if inner lists are aliased?

Practice loop

1. Read Deep study (if present) or core concepts once.
2. Recite the formula chain without looking.
3. Open one easy pattern on the interactive atlas for week 8.
4. Attempt without solutions; mark studied after an honest try.
5. Say one trap aloud before closing the tab.

Related

• Full weeks 1–8 prep guide
• Pattern atlas note
• Formula chain desk