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Description
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Example
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List
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A container data type that stores a
sequence of elements. Unlike strings, lists
are mutable: modification possible.
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l = [1, 2, 2] print(len(l)) # 3
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Adding
elements
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Add elements to a list with (i) append, (ii)
insert, or (iii) list concatenation.
The append operation is very fast.
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[1, 2, 2].append(4) # [1, 2, 2,4] [1, 2, 4].insert(2,2) # [1, 2, 2, 4] [1, 2, 2] + [4] # [1, 2, 2, 4]
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Removal
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Removing an element can be slower.
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[1, 2, 2, 4].remove(1) # [2, 2, 4]
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Reversing
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This reverses the order of list elements.
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[1, 2, 3].reverse() # [3, 2, 1]
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Sorting
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Sorts a list. The computational complexity
of sorting is O(n log n) for n list elements.
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[2, 4, 2].sort() # [2, 2, 4]
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Indexing
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Finds the first occurence of an element in
the list & returns its index. Can be slow as
the whole list is traversed.
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[2, 2, 4].index(2) # index of element 4 is "0" [2, 2, 4].index(2,1) # index of element 2 after pos 1 is "1"
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Stack
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Python lists can be used intuitively as stack
via the two list operations append() and
pop().
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stack = [3] stack.append(42) # [3, 42] stack.pop() # 42 (stack: [3]) stack.pop() # 3 (stack: [])
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Set
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A set is an unordered collection of
elements. Each can exist only once.
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basket = {'apple', 'eggs', 'banana', 'orange'} same = set(['apple', 'eggs', 'banana', 'orange'])
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Dictionary
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The dictionary is a useful data structure for
storing (key, value) pairs.
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calories = {'apple' : 52, 'banana' : 89, 'choco' : 546}
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Reading and
writing
elements
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Read and write elements by specifying the
key within the brackets. Use the keys() and
values() functions to access all keys and
values of the dictionary.
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print(calories['apple'] < calories['choco']) # True calories['cappu'] = 74 print(calories['banana'] < calories['cappu']) # False print('apple' in calories.keys()) # True print(52 in calories.values()) # True
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Dictionary
Looping
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You can loop over the (key, value) pairs of
a dictionary with the items() method.
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for k, v in calories.items(): print(k) if v > 500 else None # 'chocolate'
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Membership
operator
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Check with the ‘in’ keyword whether the
set, list, or dictionary contains an element.
Set containment is faster than list
containment.
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basket = {'apple', 'eggs', 'banana', 'orange'} print('eggs' in basket} # True print('mushroom' in basket} # False
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List and Set Comprehens
ion
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List comprehension is the concise Python
way to create lists. Use brackets plus an
expression, followed by a for clause. Close
with zero or more for or if clauses. Set comprehension is similar to list
comprehension.
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# List comprehension l = [('Hi ' + x) for x in ['Alice', 'Bob', 'Pete']] print(l) # ['Hi Alice', 'Hi Bob', 'Hi Pete'] l2 = [x * y for x in range(3) for y in range(3) if x>y] print(l2) # [0, 0, 2] # Set comprehension squares = { x**2 for x in [0,2,4] if x < 4 } # {0, 4}
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