~/Dictionaries

19.1 Creating a Dictionary

19.2 Accessing an Item

Fetch a value by putting its key inside square brackets. If the key is not in the dict, Python raises KeyError.

student = {"name": "Kavya", "roll": 22, "marks": 91}

print(student["name"])      # Kavya
print(student["roll"])      # 22
# print(student["age"])     ❌ KeyError: 'age'

19.2.1 Safe access — get(key, default)

get() is the safer cousin of [ ]: if the key is missing it returns None (or a fall-back you supply) without raising an error.

print(student.get("name"))            # Kavya
print(student.get("age"))             # None
print(student.get("age", "N/A"))      # N/A

19.2.2 Test for a key — in

print("name" in student)         # True   — tests KEYS, not values
print("Kavya" in student)        # False
print("Kavya" in student.values())  # True   — explicit values check

19.3 Dictionaries Are Mutable

A dict can be changed in place: adding a new key, replacing an existing key's value, or removing a key.

student = {"name": "Kavya", "roll": 22}

# Add a new key — just assign to it
student["marks"] = 91
student["age"]   = 16
print(student)
# {'name': 'Kavya', 'roll': 22, 'marks': 91, 'age': 16}

# Modify an existing key — exactly the same syntax
student["roll"] = 23
print(student["roll"])           # 23

# Delete a key-value pair
del student["age"]
print(student)
# {'name': 'Kavya', 'roll': 23, 'marks': 91}

19.4 Traversing a Dictionary

Four common loops. By default, looping over a dict iterates over its keys.

prices = {"apple": 40, "banana": 10, "mango": 60}

# 1 — over keys (default)
for k in prices:
    print(k)                      # apple, banana, mango

# 2 — over keys explicitly
for k in prices.keys():
    print(k, prices[k])

# 3 — over values
for v in prices.values():
    print(v)                      # 40, 10, 60

# 4 — over key-value pairs (most useful)
for k, v in prices.items():
    print(f"{k}: ₹{v}")            # apple: ₹40 …

19.5 Built-in FUNCTIONS that work on Dicts

19.6 Dictionary METHODS

19.6.1 The "view" methods — keys(), values(), items()

The three views are live: if the dict changes, the views reflect the change automatically. Wrap in list() if you need a snapshot.

p = {"a":1, "b":2}
v = p.values()
p["c"] = 3
print(list(v))           # [1, 2, 3] — view already reflects the new item

19.6.2 Access & add — get, setdefault, update

counts = {}
for ch in "banana":
    counts[ch] = counts.get(ch, 0) + 1    # 0 when first seen, else prev count
print(counts)                          # {'b': 1, 'a': 3, 'n': 2}

# Merging two dicts
p = {"a":1, "b":2}
p.update({"b":20, "c":3})            # 'b' overwritten, 'c' added
print(p)                              # {'a': 1, 'b': 20, 'c': 3}

19.6.3 Remove — pop, popitem, clear, del

p = {"a":1, "b":2, "c":3}

print(p.pop("a"))      # 1          — returns the removed value
print(p)                # {'b': 2, 'c': 3}
print(p.popitem())     # ('c', 3)   — last inserted pair
print(p)                # {'b': 2}
p.clear()
print(p)                # {}

19.6.4 Construct — fromkeys & copy

# fromkeys — same default value for many keys
attendance = dict.fromkeys(["Mon", "Tue", "Wed"], True)
print(attendance)       # {'Mon': True, 'Tue': True, 'Wed': True}

# copy — independent shallow copy
a = {"x": 1, "y": 2}
b = a.copy()
b["z"] = 3
print(a)                # {'x': 1, 'y': 2} — unchanged
print(b)                # {'x': 1, 'y': 2, 'z': 3}

19.6.5 Cheat sheet — every CBSE method & function at a glance

19.7 Worked Programs

19.7.1 Count the frequency of each character in a string

The classic use of a dict: the key is the character, the value is the running count.

s = input("Enter a string: ")
freq = {}
for ch in s:
    freq[ch] = freq.get(ch, 0) + 1

for ch, c in freq.items():
    print(f"{ch!r} appears {c} time(s)")

'b' appears 1 time(s)
'a' appears 3 time(s)
'n' appears 2 time(s)

from collections import Counter
print(Counter("banana"))   # Counter({'a': 3, 'n': 2, 'b': 1})

19.7.2 Employee name → salary dictionary

Build a dict mapping employee names to their salaries, then look up values and answer queries.

# employees.py — name → salary dictionary

salary = {
    "Aarav":  45000,
    "Kavya":  52000,
    "Ishan":  38000,
    "Priya":  60000,
    "Rohan":  47500
}

print("Number of employees:", len(salary))
print("Total salary bill : ₹", sum(salary.values()))
print("Average salary    : ₹", sum(salary.values()) / len(salary))
print("Highest paid      :", max(salary, key=salary.get))
print("Lowest paid       :", min(salary, key=salary.get))

# Search by name
name = input("Search name: ")
if name in salary:
    print(f"{name} earns ₹{salary[name]}")
else:
    print(name, "is not in the records")

# Give everyone a 10% raise
for k in salary:
    salary[k] = int(salary[k] * 1.10)
print("After 10% raise:", salary)

Number of employees: 5
Total salary bill : ₹ 242500
Average salary    : ₹ 48500.0
Highest paid      : Priya
Lowest paid       : Ishan
Search name: Kavya
Kavya earns ₹52000
After 10% raise: {'Aarav': 49500, 'Kavya': 57200, 'Ishan': 41800, 'Priya': 66000, 'Rohan': 52250}

19.7.3 Bonus — Words longer than a given length

sentence = "Python dictionaries are really useful"
n = 6

counts = {}
for word in sentence.split():
    if len(word) >= n:
        counts[word] = len(word)

print(counts)       # {'Python': 6, 'dictionaries': 12, 'really': 6, 'useful': 6}

19.8 Comparing the Four Collections