10.4 Conditionals and looping in dictionaries

Dictionaries in Python offer powerful tools for data manipulation. Conditional checks and looping techniques allow you to search, filter, and process dictionary contents efficiently. These methods are essential for working with complex data structures in real-world programming scenarios.

Advanced dictionary operations take your skills further. Dictionary comprehensions and boolean operators enable you to create and modify dictionaries based on specific conditions. These techniques streamline your code and enhance your ability to work with structured data.

Conditionals and Looping in Dictionaries

Conditional checks in dictionaries

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• Check if a key exists in a dictionary using the

  in

  keyword
  • Evaluates to

    [True](https://www.fiveableKeyTerm:TRUE)

    if the key is found,

    [False](https://www.fiveableKeyTerm:FALSE)

    otherwise
  • Example:

    if 'name' in student_info:

• Check if a value exists in a dictionary by iterating through the

  [values()](https://www.fiveableKeyTerm:values())

  view

  • values()

    returns a view object containing all the values in the dictionary
  • Iterate through the view to find a specific value
  • Example:

    if 'John' in student_info.values():

• Use the

  [get()](https://www.fiveableKeyTerm:get())

  method to retrieve the value associated with a key, providing a default value if the key is not found
  • Syntax:

    dictionary.get(key, default_value)

  • Returns the value if the key exists, otherwise returns the default value
  • Example:

    age = student_info.get('age', 18)

• Use conditional expressions for concise key-value checks
  • Example:

    result = 'Adult' if age >= 18 else 'Minor'

Iteration through dictionary components

• Iterate through dictionary keys using a

  for

  loop
  • By default, iterating over a dictionary yields its keys
  • Access the corresponding value using the key within the loop
  • Example:

    for name in phone_book:
        print(name, phone_book[name])
    

• Iterate through dictionary values using the

  values()

  method

  • values()

    returns a view object containing all the values in the dictionary
  • Useful when only the values are needed, not the keys
  • Example:

    for phone_number in phone_book.values():
        print(phone_number)
    

• Iterate through dictionary key-value pairs using the

  [items()](https://www.fiveableKeyTerm:items())

  method

  • items()

    returns a view object containing tuples of key-value pairs
  • Unpack the tuple in the

    for

    loop to access both the key and value
  • Example:

    for name, phone_number in phone_book.items():
        print(name, phone_number)
    

• Use iteration to process nested dictionaries
  • Example:

    for department, employees in company.items():
        for employee, details in employees.items():
            print(f"{employee} works in {department}")
    

Application of dictionary methods

• Use the

  [keys()](https://www.fiveableKeyTerm:keys())

  method to get a view of all keys in the dictionary
  • Useful for checking the existence of keys or iterating through them
  • Example:

    if 'address' in student_info.keys():

• Use the

  values()

  method to get a view of all values in the dictionary
  • Useful for checking the existence of values or iterating through them
  • Example:

    for grade in student_grades.values():
        if grade >= 90:
            print("A")
    

• Use the

  items()

  method to get a view of all key-value pairs as tuples
  • Useful for iterating through both keys and values simultaneously
  • Example:

    for item, price in store_inventory.items():
        if price > 100:
            print(item, "is expensive")
    

• Combine dictionary methods with conditional statements
  • Check for specific keys or values while iterating through a dictionary
  • Example:

    for name, score in exam_scores.items():
        if score < 60:
            print(name, "failed the exam")
    

Advanced dictionary operations

• Use dictionary comprehension for creating dictionaries based on conditions
  • Example:

    squared_numbers = {x: x**2 for x in range(10) if x % 2 == 0}

• Apply boolean operators in dictionary operations
  • Example:

    valid_entries = {k: v for k, v in data.items() if v is not None and v != ''}

• Utilize conditional expressions in dictionary comprehensions
  • Example:

    grade_status = {name: 'Pass' if score >= 60 else 'Fail' for name, score in exam_scores.items()}