Welcome back! You've started with Python dictionaries; now, let's dive deeper. In this unit, we're exploring nested dictionaries - think of them as a multi-level travel guide with detailed information on various destinations.

Moving beyond the basic key-value pairs, we'll focus on nested dictionaries. Imagine organizing airports worldwide, with codes, locations, and amenities, all within nested structures. We'll cover:

• Creating nested dictionaries for structured, multi-level data organization.
• Accessing, manipulating, and updating data within these complex structures.
• Adding new information efficiently.

Nested dictionaries have other dictionaries as values:

Python
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1# Nested dictionary
2airport_codes = {
3    "JFK": {"city": "New York", "country": "USA"},
4    "LAX": {"city": "Los Angeles", "country": "USA"}
5}
6

As you can see in the example above, the airport_codes dictionary has keys "JFK" and "LAX" whose values are other dictionaries with their own key-value pairs. Values can be accessed, added and updated:

Python
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1airport_codes = {
2    "JFK": {"city": "New York", "country": "USA"},
3    "LAX": {"city": "Los Angeles", "country": "USA"}
4}
5
6# Add Osaka's Kansai International Airport
7airport_codes["KIX"] = {"city": "Osaka", "country": "Japan"}
8
9# Add airport elevation data to KIX
10airport_codes["KIX"]["elevation"] = 4
11
12# Update elevation data
13airport_codes["KIX"]["elevation"] = 5
14
15# Delete elevation data
16del airport_codes["KIX"]["elevation"]

Nested dictionaries are vital for managing intricate, hierarchical data, crucial for applications like our travel scenario. Understanding these advanced techniques enables sophisticated data modeling and improves problem-solving skills in real-world, data-rich environments.

Let's explore the power and potential of nested data structuring in Python through practice.