Data Structures in Python

Python provides a bunch of data structures in distinct forms for distinct goals. In the high level, we can group these by below categories:

1. Sequences Types: List, Tuple, Range, String (we've talked about this)
2. Set Types: Set, Frozen Set
3. Mapping Types: Dictionary

All those common types apply some common operations in the following table.

Based on the ability to re-define items, sequences are categorized into these groups:

1. Immutable sequence
2. Mutable sequence. Common operations applied for mutable sequences are mentioned in the following table.

Lists

• A mutable sequence
• Used to store collections of homogeneous items (or heterogenous items)
• Can be constructed in several ways:
  • square brackets for empty list: []
  • square brakets and separating items with commas: [a], [a, b, c]
  • using list comprehension: [x for x in iterable_list] (later)
  • using a constructor fucntion: list(), list("abc"), list((1, 2, 3))

Let's try to create some lists!

Let's applies some operations in the previus tables.

Tuples

• An immutable sequence
• Used to store collections of heterogeneous data (or homogeneous) that is rarely changed
• Can be constructed in several ways below:
  • pair of parentheses to denote emtpy tuple: ()
  • trailing comma for a singleton tuple: a,, `(a,)
  • separating items with comma: a, b, c, or (a, b, c)
  • use constructor function tuple()

Remember that since tuple is immutable, we can't modify the items after assignment.

Let's create some tuples!

Set Types

• An unordered collection
• Unordered collection means it can't be indexed and sliced (or other sequence-like behavior)
• set is mutable (the content can be changed), but frozenset is immutable.
• Usually used to remove duplicates, math operations in set (e.g. intersection, etc.)
• Can be constructed in several ways below:
  • use comma-separated list of items within curly braces: {'hack', 'active'}
  • use a set comprehension (similar to list comprehension) <- later on this
  • use constructor function set()

Unordered collection means that it can be indexed since Python doesn't know which item is the first to be indexed. Hence, doing all_set[0] will throw an error. Let's catch one!

Dictionary

• A mutable collection
• A mapping object which consists of key-value pairs
• A key in dictionary is almost arbitrary values (except unhashable object, e.g. lists, dictionary, or other mutable objects)
• Can be constructed in several ways:
  • using comma-separated list of key: value pairs within curly braces: {"jack": 2048, "paul": 4127}
  • using constructor function dict()
  • using dictionary comprehension

Case Study

1. Finding Nemo

Given a list of fish, using looping, we will find if a fish has a string nemo in it.

list_fishes = ["emo", "sprout", "shark", "nemoo", "bynemo", "neemoo", "turtleish", "moo", "nemmo", "nemo"]

2. Merging Data into Dictionary

Given 2 list of data, names and credits, using looping, create a dictionary transactions that consists of keys names and the value for data names and credits consecutively.

names = ["michael", "lucifer", "dosan", "queen"]
credits = [109.29, 549.919, 800.13, 949.01]