Python Nested Data Structures
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List of Lists
A list of lists is Python's standard way to represent a 2D grid or matrix, where the outer list holds rows and each inner list holds that row's columns -- grid[row][column] reads the element at that position, first indexing into the outer list, then the inner one.
Example: List of Lists
grid = [[1, 2], [3, 4]]
print(grid[1][0])Dictionary of Dictionaries
Nesting dictionaries inside a dictionary lets you group related records under a single parent key, like users[alice] = {age: 30, email: '...'} -- this mirrors how JSON APIs commonly structure profile or configuration data.
Example: Dictionary of Dictionaries
users = {"alice": {"age": 30, "email": "[email protected]"}}
print(users["alice"]["age"])List of Dictionaries
A list of dictionaries -- [{id: 1, name: A}, {id: 2, name: B}] -- is exactly the shape most database query results and JSON API responses take, with each dict representing one row or record and the list representing the full result set.
Example: List of Dictionaries
records = [{"id": 1, "name": "A"}, {"id": 2, "name": "B"}]
print(records[1]["name"])Dictionary of Lists
Mapping a single key to a list of values (a dict of lists) is the natural structure for grouping data by category, such as tags_to_articles[python] = [article1, article2] holding every article tagged python under one key.
Example: Dictionary of Lists
tags_to_articles = {"python": ["article1", "article2"]}
print(tags_to_articles["python"])Iterating through Nested Data
Walking nested structures usually means one loop per level of nesting -- a for loop over the outer list, with a nested for loop (or dict iteration) inside it -- and getting the loop variable names right at each level is what keeps the code readable.
Example: Iterating through Nested Data
grid = [[1, 2], [3, 4]]
for row in grid:
for value in row:
print(value)Chapter Quiz — Complete all 12 topics to unlock
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