From: http://interactivepython.org/courselib/static/pythonds/Introduction/GettingStartedwithData.html

Built-in Collection Data Types

Python has a number of very powerful built-in collection classes. Lists, strings, and tuples are ordered collections that are very similar in general structure but have specific differences that must be understood for them to be used properly. Sets and dictionaries are unordered collections.

  • List

    • A list is an ordered collection of zero or more references to Python data objects.
    • Lists are heterogeneous, meaning that the data objects need not all be from the same class and the collection can be assigned to a variable as below.

>>> [1,3,True,6.5]

[1, 3, True, 6.5]

>>> myList = [1,3,True,6.5]

>>> myList

[1, 3, True, 6.5]

    • Since lists are considered to be sequentially ordered, they support a number of operations that can be applied to any Python sequence.
Operation Name Operator Explanation
indexing [ ] Access an element of a sequence
concatenation + Combine sequences together
repetition * Concatenate a repeated number of times
membership in Ask whether an item is in a sequence
length len Ask the number of items in the sequence
slicing [ : ] Extract a part of a sequence
      Note that the indices for lists (sequences) start counting with 0.

myList = [1,2,3,4]
A = [myList]*3
print(A)
myList[2]=45
print(A)

Lists support a number of methods that will be used to build data structures.

Method Name Use Explanation
append alist.append(item) Adds a new item to the end of a list
insert alist.insert(i,item) Inserts an item at the ith position in a list
pop alist.pop() Removes and returns the last item in a list
pop alist.pop(i) Removes and returns the ith item in a list
sort alist.sort() Modifies a list to be sorted
reverse alist.reverse() Modifies a list to be in reverse order
del del alist[i] Deletes the item in the ith position
index alist.index(item) Returns the index of the first occurrence of item
count alist.count(item) Returns the number of occurrences of item
remove alist.remove(item) Removes the first occurrence of item

myList = [1024, 3, True, 6.5]
myList.append(False)
print(myList)
myList.insert(2,4.5)
print(myList)
print(myList.pop())
print(myList)
print(myList.pop(1))
print(myList)
myList.pop(2)
print(myList)
myList.sort()
print(myList)
myList.reverse()
print(myList)
print(myList.count(6.5))
print(myList.index(4.5))
myList.remove(6.5)
print(myList)
del myList[0]
print(myList)

One common Python function that is often discussed in conjunction with lists is the range function. range produces a range object that represents a sequence of values. By using the list function, it is possible to see the value of the range object as a list. This is illustrated below.

>>> range(10)
range(0, 10)
>>> list(range(10))
[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
>>> range(5,10)
range(5, 10)
>>> list(range(5,10))
[5, 6, 7, 8, 9]
>>> list(range(5,10,2))
[5, 7, 9]
>>> list(range(10,1,-1))
[10, 9, 8, 7, 6, 5, 4, 3, 2]
>>>
  • String

    • Strings are sequential collections of zero or more letters, numbers and other symbols.
>>> "David"
'David'
>>> myName = "David"
>>> myName[3]
'i'
>>> myName*2
'DavidDavid'
>>> len(myName)
5
>>>

Since strings are sequences, all of the sequence operations described above work as you would expect. In addition, strings have a number of methods.

>>> myName
'David'
>>> myName.upper()
'DAVID'
>>> myName.center(10)
' David '
>>> myName.find('v')
2
>>> myName.split('v')
['Da', 'id']

Of these, split will be very useful for processing data. split will take a string and return a list of strings using the split character as a division point. In the example, v is the division point. If no division is specified, the split method looks for whitespace characters such as tab, newline and space.

Method Name Use Explanation
center astring.center(w) Returns a string centered in a field of size w
count astring.count(item) Returns the number of occurrences of item in the string
ljust astring.ljust(w) Returns a string left-justified in a field of size w
lower astring.lower() Returns a string in all lowercase
rjust astring.rjust(w) Returns a string right-justified in a field of size w
find astring.find(item) Returns the index of the first occurrence of item
split astring.split(schar) Splits a string into substrings at schar

A major difference between lists and strings is that lists can be modified while strings cannot. This is referred to as mutability. Lists are mutable; strings are immutable. For example, you can change an item in a list by using indexing and assignment. With a string that change is not allowed.

>>> myList
[1, 3, True, 6.5]
>>> myList[0]=2**10
>>> myList
[1024, 3, True, 6.5]
>>>
>>> myName
'David'
>>> myName[0]='X' Traceback (most recent call last):
File "<pyshell#84>", line 1, in -toplevel-
myName[0]='X'
TypeError: object doesn't support item assignment
>>>
  • Tuples

Tuples are very similar to lists in that they are heterogeneous sequences of data. The difference is that a tuple is immutable, like a string.

>>> myTuple = (2,True,4.96)
>>> myTuple
(2, True, 4.96)
>>> len(myTuple)
3
>>> myTuple[0]
2
>>> myTuple * 3
(2, True, 4.96, 2, True, 4.96, 2, True, 4.96)
>>> myTuple[0:2]
(2, True)
>>> However, if you try to change an item in a tuple, you will get an error. Note that the error message provides location and reason for the problem.
>>> myTuple[1]=False

Traceback (most recent call last):
File "<pyshell#137>", line 1, in -toplevel-
myTuple[1]=False
TypeError: object doesn't support item assignment
>>>
  • Sets

A set is an unordered collection of zero or more immutable Python data objects. Sets do not allow duplicates and are written as comma-delimited values enclosed in curly braces. The empty set is represented by set(). Sets are heterogeneous, and the collection can be assigned to a variable as below.

>>> {3,6,"cat",4.5,False}
{False, 4.5, 3, 6, 'cat'}
>>> mySet = {3,6,"cat",4.5,False}
>>> mySet
{False, 4.5, 3, 6, 'cat'}
>>>

Even though sets are not considered to be sequential, they do support a few of the familiar operations presented earlier.

Operation Name Operator Explanation
membership in Set membership
length len Returns the cardinality of the set
| aset | otherset Returns a new set with all elements from both sets
& aset & otherset Returns a new set with only those elements common to both sets
- aset - otherset Returns a new set with all items from the first set not in second
<= aset <= otherset Asks whether all elements of the first set are in the second
>>> mySet
{False, 4.5, 3, 6, 'cat'}
>>> len(mySet)
5
>>> False in mySet
True
>>> "dog" in mySet
False
>>>

Sets support a number of methods that should be familiar to those who have worked with them in a mathematics setting.

Method Name Use Explanation
union aset.union(otherset) Returns a new set with all elements from both sets
intersection aset.intersection(otherset) Returns a new set with only those elements common to both sets
difference aset.difference(otherset) Returns a new set with all items from first set not in second
issubset aset.issubset(otherset) Asks whether all elements of one set are in the other
add aset.add(item) Adds item to the set
remove aset.remove(item) Removes item from the set
pop aset.pop() Removes an arbitrary element from the set
clear aset.clear() Removes all elements from the set
>>> mySet
{False, 4.5, 3, 6, 'cat'}
>>> yourSet = {99,3,100}
>>> mySet.union(yourSet)
{False, 4.5, 3, 100, 6, 'cat', 99}
>>> mySet | yourSet
{False, 4.5, 3, 100, 6, 'cat', 99}
>>> mySet.intersection(yourSet)
{3}
>>> mySet & yourSet
{3}
>>> mySet.difference(yourSet)
{False, 4.5, 6, 'cat'}
>>> mySet - yourSet
{False, 4.5, 6, 'cat'}
>>> {3,100}.issubset(yourSet)
True
>>> {3,100}<=yourSet
True
>>> mySet.add("house")
>>> mySet
{False, 4.5, 3, 6, 'house', 'cat'}
>>> mySet.remove(4.5)
>>> mySet
{False, 3, 6, 'house', 'cat'}
>>> mySet.pop()
False
>>> mySet
{3, 6, 'house', 'cat'}
>>> mySet.clear()
>>> mySet
set()
>>>

Dictionaries

Dictionaries are collections of associated pairs of items where each pair consists of a key and a value.This key-value pair is typically written as key:value.

>>> capitals = {'Iowa':'DesMoines','Wisconsin':'Madison'}
>>> capitals
{'Wisconsin': 'Madison', 'Iowa': 'DesMoines'}
>>>

capitals = {'Iowa':'DesMoines','Wisconsin':'Madison'}
print(capitals['Iowa'])
capitals['Utah']='SaltLakeCity'
print(capitals)
capitals['California']='Sacramento'
print(len(capitals))
for k in capitals:
print(capitals[k]," is the capital of ", k)

It is important to note that the dictionary is maintained in no particular order with respect to the keys.The placement of a key is dependent on the idea of “hashing“.
Dictionaries have both methods and operators.The keys, values, and items methods all return objects that contain the values of interest.You can use the list function to convert them to lists. You will also see that there are two variations on the get method. If the key is not present in the dictionary, get will return None. However, a second, optional parameter can specify a return value instead.
Operator Use Explanation
[] myDict[k] Returns the value associated with k, otherwise its an error
in key in adict Returns True if key is in the dictionary, False otherwise
del del adict[key] Removes the entry from the dictionary
>>> phoneext={'david':1410,'brad':1137}
>>> phoneext
{'brad': 1137, 'david': 1410}
>>> phoneext.keys()
dict_keys(['brad', 'david'])
>>> list(phoneext.keys())
['brad', 'david']
>>> phoneext.values()
dict_values([1137, 1410])
>>> list(phoneext.values())
[1137, 1410]
>>> phoneext.items()
dict_items([('brad', 1137), ('david', 1410)])
>>> list(phoneext.items())
[('brad', 1137), ('david', 1410)]
>>> phoneext.get("kent")
>>> phoneext.get("kent","NO ENTRY")
'NO ENTRY'
>>>
Method Name Use Explanation
keys adict.keys() Returns the keys of the dictionary in a dict_keys object
values adict.values() Returns the values of the dictionary in a dict_values object
items adict.items() Returns the key-value pairs in a dict_items object
get adict.get(k) Returns the value associated with k, None otherwise
get adict.get(k,alt) Returns the value associated with k, alt otherwise
 
												

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