Welcome! Today, we're diving into Python dictionaries. These store items as key-value pairs, much like a real dictionary where you look up a word (key) to find its meaning (value). By the end of this lesson, you’ll have a good grasp of dictionaries.

Dictionaries in Python are unordered collections of data values. This differentiation sets them apart from lists and tuples, which have specific orders. In a dictionary, each item possesses a key associated with a specific value, enhancing its efficiency in data access and management.

Here's a simple dictionary:

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1# A dictionary storing names as keys and ages as values
2dictionary_example = {"Alice": 25, "Bob": 28, "Charlie": 30}
3print(dictionary_example)  # Outputs: {'Alice': 25, 'Bob': 28, 'Charlie': 30}

In dictionary_example, the keys are "Alice", "Bob", and "Charlie", and the values are 25, 28, and 30, respectively. Key uniqueness is integral to the design of dictionaries - for example, that means we can only have a single key called "Alice".

Dictionaries are initiated by placing key-value pairs within {}. Another way to create a dictionary is by using a dict() method.

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1# An empty dictionary
2empty_dict_1 = {} # an empty dictionary
3empty_dict_2 = dict()   # another empty dictionary
4
5# A dictionary of students and their ages
6student_age = {"Alice": 12, "Bob": 13, "Charlie": 11}

Keys and values can be of different data types.

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1# A dictionary with diverse key and value types
2student_info = {
3    "name": "Alice",
4    "age": 12,
5    "subjects": ["Math", "Science", "English"],
6    (90, 80): "Coordinates"    # Tuple used as a key
7}

Unlike lists, dictionaries are collections of items accessed by their keys, not by their positions.

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1print(student_age["Alice"])  # Outputs: 12

get() is a safer method for retrieving values as it returns None or a default value if the key is nonexistent.

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1print(student_age.get("David"))       # Outputs: None
2print(student_age.get("David", 10))   # Outputs: 10

To check whether the key exists in the dictionary, use the in operator:

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1print("David" in student_age) # Outputs: False
2print("Alice" in student_age) # Outputs: True

Python dictionaries are mutable, meaning we can add, modify, or delete elements.

We can add a new key-value pair like this:

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1student_age["David"] = 14
2print(student_age)    # Outputs: {'Alice': 12, 'Bob': 13, 'Charlie': 11, 'David': 14}

Here's how to modify a value in a dictionary:

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1student_age["Alice"] = 15
2print(student_age)    # Outputs: {'Alice': 15, 'Bob': 13, 'Charlie': 11, 'David': 14}

Here's how to delete a key-value pair:

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1del student_age["David"]
2print(student_age)    # Outputs: {'Alice': 15, 'Bob': 13, 'Charlie': 11}

Python dictionaries provide several handy methods, like keys(), values(), and items().

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1print(student_age.keys())   # Outputs: dict_keys(['Alice', 'Bob', 'Charlie'])
2print(student_age.values()) # Outputs: dict_values([15, 13, 11])
3print(student_age.items())  # Outputs: dict_items([('Alice', 15), ('Bob', 13), ('Charlie', 11)])

It isn't uncommon to nest dictionaries within other dictionaries, forming what we call nested dictionaries.

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1teams = {
2  "team1" : {
3    "name" : "Tigers",
4    "players" : 11
5  },
6  "team2" : {
7    "name" : "Hawks",
8    "players" : 11
9  }
10}
11
12print(teams['team1']['name']) # Output: 'Tigers'

Nested dictionaries can be manipulated similarly to simple dictionaries.

Great work! We've delved into Python dictionaries: understanding their structure, creating and using them, and exploring their real-life applications. Next, let's reinforce this knowledge with some hands-on exercises!