05-04: Exercises — Dictionaries¶

Notes reference: 05-04: Dictionaries

Q1: Create and access¶

Create a dictionary for a student with keys name, age, city, gpa. Access each value.

Solution

student = {
    "name": "Jahid",
    "age" : 28,
    "city": "New York",
    "gpa" : 3.8,
}
print(student["name"])        # Jahid
print(student.get("gpa"))     # 3.8
print(student.get("major", "Undeclared"))  # Undeclared (default)

Q2: Add, update, delete¶

Start with scores = {"Math": 85, "Physics": 78}. Add "Chemistry": 92, update "Math" to 90, and delete "Physics".

Solution

scores = {"Math": 85, "Physics": 78}
scores["Chemistry"] = 92
scores["Math"]      = 90
del scores["Physics"]
print(scores)   # {'Math': 90, 'Chemistry': 92}

Q3: keys, values, items¶

Iterate over a country → capital dictionary and print each pair.

Solution

capitals = {
    "Bangladesh": "Dhaka",
    "USA"       : "Washington D.C.",
    "Germany"   : "Berlin",
    "Japan"     : "Tokyo",
    "Kenya"     : "Nairobi",
}
for country, capital in capitals.items():
    print(f"{country}: {capital}")

Q4: dict.get with default¶

Ask the user for a city name and look it up in the population dictionary. If not found, print "City not found".

Solution

population = {
    "Dhaka"   : 21_006_000,
    "New York": 8_336_817,
    "Berlin"  : 3_769_000,
}
city = input("Enter city: ")
pop  = population.get(city, "City not found")
print(pop)

Q5: update() and merge¶

Merge two dictionaries: user defaults and user preferences.

Solution

defaults = {"theme": "light", "language": "en", "font_size": 14}
prefs    = {"theme": "dark",  "font_size": 16}

settings = {**defaults, **prefs}   # merge, prefs override defaults
print(settings)
# {'theme': 'dark', 'language': 'en', 'font_size': 16}

# Alternative:
defaults.update(prefs)
print(defaults)

Q6: Dictionary comprehension¶

Build a dictionary mapping numbers 1–8 to their cubes.

Solution

cubes = {n: n**3 for n in range(1, 9)}
print(cubes)
# {1: 1, 2: 8, 3: 27, 4: 64, 5: 125, 6: 216, 7: 343, 8: 512}

Q7: Nested dictionary¶

Create a nested dictionary for two employees. Access a specific nested value.

Solution

employees = {
    "E001": {"name": "Rahul", "dept": "Engineering", "salary": 95000},
    "E002": {"name": "Sarah", "dept": "Data Science", "salary": 105000},
}
print(employees["E002"]["name"])      # Sarah
print(employees["E001"]["salary"])    # 95000

Q8: Count word frequency¶

Count how many times each word appears in a sentence.

Solution

sentence = "the cat sat on the mat and the cat ate the rat"
freq     = {}
for word in sentence.split():
    freq[word] = freq.get(word, 0) + 1

for word, count in sorted(freq.items(), key=lambda x: -x[1]):
    print(f"{word}: {count}")

Alternative — using collections.Counter:

from collections import Counter
freq = Counter(sentence.split())
print(freq.most_common(5))

Q9: setdefault and grouping¶

Group a list of names by their first letter.

Solution

names  = ["Alice", "Bob", "Anna", "Ben", "Carol", "Chris"]
groups = {}
for name in names:
    groups.setdefault(name[0], []).append(name)

print(groups)
# {'A': ['Alice', 'Anna'], 'B': ['Bob', 'Ben'], 'C': ['Carol', 'Chris']}

⬅️ Previous: 05-03: Exercises — Sets ➡️ Next: 05-05: Exercises — Slicing