Python

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