What is the difference between "in" and "not in" in Python?

Question

Jayant Kumar · Accepted Answer

Table of Contents
Introduction
In Python, the in and not in operators are used for membership testing, which allows you to check if a value exists within a collection such as a list, tuple, or dictionary. These operators are fundamental for conditional statements and data manipulation. This article will detail the differences between in and not in, explaining their usage and providing practical examples to illustrate their application.
Key Differences Between in and not in
1. Purpose and Function

**in**: The in operator checks if a specified value is present within a collection. It returns True if the value exists in the collection and False otherwise.
**not in**: The not in operator checks if a specified value is not present within a collection. It returns True if the value is not found and False if the value exists in the collection.

Example:
# Using in
my_list = [1, 2, 3, 4, 5]
print(3 in my_list)  # Output: True
print(6 in my_list)  # Output: False

# Using not in
print(3 not in my_list)  # Output: False
print(6 not in my_list)  # Output: True

2. Use with Different Data Types

**in**: Can be used with various data types, including lists, tuples, strings, sets, and dictionaries. For dictionaries, in checks if a key exists in the dictionary.
**not in**: Functions similarly to in, working with lists, tuples, strings, sets, and dictionaries. For dictionaries, it checks if a key does not exist.

Example:
# Using in with different data types
string = "hello"
print('e' in string)  # Output: True
print('a' in string)  # Output: False

# Using not in with different data types
print('e' not in string)  # Output: False
print('a' not in string)  # Output: True

# Using in with a dictionary
my_dict = {'a': 1, 'b': 2}
print('a' in my_dict)  # Output: True
print(1 in my_dict)    # Output: False (checks for key, not value)

# Using not in with a dictionary
print('a' not in my_dict)  # Output: False
print(1 not in my_dict)    # Output: True (checks for key, not value)

3. Conditional Statements

**in**: Commonly used in if statements to perform actions based on the presence of an item in a collection.
**not in**: Used to check for the absence of an item and can be employed in if statements to handle cases where a value is missing.

Example:
# Conditional check using in
colors = ['red', 'green', 'blue']
if 'green' in colors:
    print("Green is in the list.")
else:
    print("Green is not in the list.")

# Conditional check using not in
if 'yellow' not in colors:
    print("Yellow is not in the list.")
else:
    print("Yellow is in the list.")

Practical Examples
Example : Checking Membership in a List
# Checking if an item is in a list
fruits = ['apple', 'banana', 'cherry']
if 'banana' in fruits:
    print("Banana is in the list.")  # Output: Banana is in the list.

# Checking if an item is not in a list
if 'orange' not in fruits:
    print("Orange is not in the list.")  # Output: Orange is not in the list.

Example : Membership Testing with Strings
# Checking if a character is in a string
sentence = "The quick brown fox"
if 'quick' in sentence:
    print("The word 'quick' is in the sentence.")  # Output: The word 'quick' is in the sentence.

# Checking if a character is not in a string
if 'slow' not in sentence:
    print("The word 'slow' is not in the sentence.")  # Output: The word 'slow' is not in the sentence.

Conclusion
The in and not in operators in Python are essential for membership testing in various data structures. in checks for the presence of a value, returning True if the value is found, while not in checks for the absence of a value, returning True if the value is not present. Understanding these operators and their applications helps in writing efficient and effective conditional statements and managing collections in Python.

What is the difference between "in" and "not in" in Python?

Table of Contents

Introduction

Key Differences Between `in` and `not in`

1. Purpose and Function

Example:

2. Use with Different Data Types

Example:

3. Conditional Statements

Example:

Practical Examples

Example : Checking Membership in a List

Example : Membership Testing with Strings

Conclusion

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