dict.values()

dict.values()

Returns: dict_values · Updated March 13, 2026 · Dict Methods

dictionaries methods iteration views

The .values() method returns a view object that displays a list of all values in a dictionary. This view provides a dynamic view of the dictionary’s values, meaning it reflects any changes made to the dictionary.

Syntax

dict.values()

Parameters

None. This method takes no parameters.

Return Value

Returns a dict_values view object, which yields dictionary values on iteration. The view is dynamic—if the dictionary changes, the view reflects those changes.

Basic Examples

Getting all values from a dictionary

person = {"name": "Alice", "age": 30, "city": "New York"}

print(person.values())
# dict_values(['Alice', 30, 'New York'])

Iterating over values

The most common use is iterating over dictionary values:

scores = {"Alice": 95, "Bob": 87, "Charlie": 92}

for value in scores.values():
    print(value)
# 95
# 87
# 92

Converting values to a list

If you need an actual list instead of a view:

fruits = {"apple": 1, "banana": 2, "cherry": 3}

values_list = list(fruits.values())
print(values_list)
# [1, 2, 3]

How Views Work

A key distinction: .values() returns a view, not a copy. Changes to the dictionary are reflected in the view:

d = {"a": 1, "b": 2}
values_view = d.values()

# Add a new key-value pair to the dictionary
d["c"] = 3

# The view now shows the new value!
print(list(values_view))
# [1, 2, 3]

If you need a snapshot that won’t change, convert to a list first:

d = {"a": 1}
snapshot = list(d.values())

d["b"] = 2

# Snapshot unchanged
print(snapshot)
# [1]

Common Patterns

Getting the sum of all values

inventory = {"apples": 5, "bananas": 3, "oranges": 8}

total = sum(inventory.values())
print(total)
# 16

Finding the maximum or minimum value

temperatures = {"Monday": 20, "Tuesday": 18, "Wednesday": 22, "Thursday": 19}

highest = max(temperatures.values())
lowest = min(temperatures.values())

print(f"Highest: {highest}, Lowest: {lowest}")
# Highest: 22, Lowest: 18

Checking if a value exists

users = {"alice": "admin", "bob": "user", "charlie": "user"}

if "admin" in users.values():
    print("At least one admin exists")
# At least one admin exists

Using values() with other dict methods

data = {"x": 10, "y": 20, "z": 30}

# Get keys and values together
keys = list(data.keys())
values = list(data.values())

print(keys)
# ['x', 'y', 'z']

print(values)
# [10, 20, 30]

Dictionary comprehension with values

prices = {"apple": 1.5, "banana": 0.5, "cherry": 3.0}

# Create new dict with doubled values
doubled = {k: v * 2 for k, v in prices.items()}

print(doubled)
# {'apple': 3.0, 'banana': 1.0, 'cherry': 6.0}

Filtering by value

scores = {"Alice": 95, "Bob": 72, "Charlie": 88, "Diana": 91}

# Keep only scores above 80
passing = {k: v for k, v in scores.items() if v > 80}
print(passing)
# {'Alice': 95, 'Charlie': 88, 'Diana': 91}

Using zip to combine keys with values

keys = ["name", "age", "city"]
values = ["Alice", 30, "New York"]

# Combine into a dictionary
data = dict(zip(keys, values))
print(data)
# {'name': 'Alice', 'age': 30, 'city': 'New York'}

values() vs keys() vs items()

Method	Returns	Example
`.keys()`	View of keys	`['name', 'age']`
`.values()`	View of values	`['Alice', 30]`
`.items()`	View of (key, value) tuples	`[('name', 'Alice'), ('age', 30)]`

Performance Note

The .values() view is memory-efficient because it doesn’t create a copy of the data. For large dictionaries, this can save significant memory. The view supports common operations like iteration, len(), and membership tests:

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

# Iterate directly over values
for value in d.values():
    print(value)

# Get the count of values
print(len(d.values()))
# 3