Python Lists

Python Lists

Python lists are

• ordered collections of arbitrary objects

• mutable sequence

  • mutable: can be changed in place

  • sequence operations: indexing, slicing, concatenation, iteration (sequences maintain a left-to-right positional ordering among the items they contain)

'''Basic List Operations'''

# ------- basic ------- #
L1 = [1, 2, 3] + [4, 5, 6]                      # concatenation
L2 = ['Ni!'] * 4                                # repetition
print(L1)
print(len(L1))                                  # length

    
# ------- iteration and comprehensions ------- #
print(3 in L1)                                  # membership test
for x in L1:                                    # iteratiom
    print(x)



# ------- indexing, slicing, nesting ------- #
L = ['spam', 'Spam', 'SPAM!']
print(
    L[2],                                       # positive: offsets start at 0
    L[-2],                                      # negative: count from the right, offsets start at -1 
    L[1:]                                       # slicing returns a new list
    )
'''
one of the simplest ways to represent matrixes (multidimensional arrays) in Python is as lists with nested sublists.
For an array of size N × M, the rows and columns are numbered from 0 to N-1 and columns are numbered from 0 to M-1, respectively
Here is a basic 3 × 5 two-dimensional list-based array
'''
matrix = [[1, 2, 3, 4, 5], 
       [6, 7, 8, 9, 10], 
       [11, 12, 13, 14, 15]]
print(matrix[1],                                # with one index, get an entire row
    matrix[1][1])                               # with two indexes,get an item within the row


'''
True
6
123456SPAM! Spam ['Spam', 'SPAM!']
[6, 7, 8, 9, 10] 7
'''

list comprehensions are a way to build a new list by applying an expression to each item in a sequence (really, in any iterable), and are close relatives to for loops

the map built-in function does similar work, but applies a function to items in a sequence and collects all the results in a new list:

'''Changing Lists in Place'''

# ------- index and slice assignments ------- #
L = ['spam', 'Spam', 'SPAM!']
L[2] = 'eggs'                                   # index assignment
L[0:2] = ['eat', 'more', 'and', 'more' ]        # slice assignment: delete + insert
print(L)                                        # the number of items inserted doesn’t have to match the number of items deleted

# slice assignment is a powerful operation
number = [1, 2, 3]
number[1:2] = [4, 5]                            # replace by overwriting
number[1:1] = [6, 7]                            # expand by inserting (replace nothing)
number[1:2] = []                                # shrink by deleting (insert nothing)

a = [1]
a[:0] = [2, 3, 4]                               # insert at the front
a[len(a):] = [5, 6, 7]                          # insert at the end

# ------- list method calls ------- #
# https://docs.python.org/3/tutorial/datastructures.html#more-on-lists
fruits = ['orange', 'apple', 'pear', 'banana', 'kiwi', 'apple', 'banana']
fruits.append('grape')                          # list.append(x) equivalent to a[len(a):] = [x]
fruits.extend(['lemon', 'watermelon'])          # list.extend(iterable) equivalent to a[len(a):] = iterable
lastFruit = fruits.pop()                        # list.pop([i]) i deault to -1
firstFruit = fruits.pop(0)

# ------- other common list operations ------- #
# del statement
food = ['spam', 'eggs', 'ham', 'toast']
del food[0]                                     # delete one item
del food[1:]                                    # delete an entire section, same as food[1:] = []
print(food)

# L[i:j] = []
mylist = ['Already', 'got', 'one']
mylist[1:] = []
mylist[0] = []
print(mylistt)