Post

Python Data Structures

Tuples

  • Tuples are an ordered sequence
  • Here is a Tuple “Ratings”
  • Tuples are written as comma-separated elements within parentheses
  • Tuples concatenation is possible
  • Tuple slicing is also possible
  • Tuples are immutable
  • If one want to manipulate tuples, they have to create a new tuple with the desired values
  • Tuples nesting (tuple containing another tuple) is also possible

    1
    
    Ratings = (10, 9, 6, 5, 10, 8, 9, 6, 2)
    

    Python data Structures

    Python data Structures

    Python data Structures

    Python data Structures

    Python data Structures

    Python data Structures

Lists

  • Lists are also ordered in sequence
  • Here is a List “L”

    1
    
    L = ["Michael Jackson", 10.1, 1982]
    
  • A List is represented with square brackets
  • List is mutable
  • List can nest other lists and tuples
  • We can combine lists
  • List can be extended with extend() method
  • append.() adds only one element to the List, if we append L.append([1,2,3,4]), the List “L” will be:

    1
    
    L = ["Michael Jackson", 10.1, 1982,[1,2,3,4]]
    
  • The method split() can convert the string into the List

    1
    
    "Hello, World!".split()
    
  • The split() can be used with a delimiter we would like to split on as an argument

    1
    
    "A,B,C,D".split(",")
    
  • Multiple names referring to the same object is known as aliasing

Python data Structures

  • We can clone the list, where both lists will be of their independent copies
  • So changing List “A”, will not change List “B”

Python data Structures

Dictionaries

Python data Structures

  • Dictionaries are denoted with curly Brackets {}
  • The keys have to be immutable and unique
  • The values can be immutable, mutable and duplicates
  • Each key and value pair is separated by a comma

Python data Structures

Sets

  • Sets are a type of collection
    • This means that like lists and tuples you can input different python types
  • Unlike lists and tuples they are unordered
    • This means sets don’t record element position
  • Sets only have unique elements
    • This means there is only one of a particular element in a set

Sets: Creating a Set

Python data Structures

  • You can convert a list into set

    1
    2
    
    List = ['foo']
    set(List)
    
  • To add elements to the set, set.add('foo')
  • To remove an element, set.remove(‘foo’)
  • To check if an element is present in the set:

    1
    2
    
    'foo' in set
    True/False
    

Sets: Mathematical Expression

  • To find the intersection of the sets elements present in the both sets), set1 & set2 or set1.intersection(set2)

Python data Structures

  • Union of the sets, contain elements of both the sets combined, set1.union(set2)
  • To find the difference of sets:

    1
    2
    3
    4
    
    #set1 difference from set2
    set1.difference(set2)
    #set2 difference from set 1
    set2.difference(set1)
    

Python data Structures

  • To find is a set is a subset/superset (have all the elements of other set), `set1.issubset/issuperset(set2)
This post is licensed under CC BY 4.0 by the author.