Data structures in Python

Data Structures in Python :
Lists
Dictionary
Tuples
Sets

 List is most versatile datatype available in Python, written
as a list of comma- separated values (items) between
square brackets.
 Items in a list can be Heterogenous types(need not be of
the same type).
 Lists are mutable
 Concatenation produces a new lists.
 Append function extends a list with a new value
without changing it.
 Example : s1=[‘abc’,’xyz’,’pqr’]

 A mutable object can be changed after it's created, and
an immutable object cannot be changed after its created.
 Examples of mutable objects are dictionary,lists etc

 list. append ( x) :Add an item to the
end of the list.
 list. extend ( L): Extend the list by appending all the
items in the given list.
 list. insert ( i, x): Insert an item at a given position.
 list. remove ( x) :Remove the ﬁrst item from the list
whose value is x.It gives an error if there is no such
item.

 list. pop ( [i]): Remove the item at the given position in the
list, and return it.
 list. clear ( ): Remove all items from the list.
Equivalent to del a[:] .
 list.reverse(): Reverse a given list.
 list. index ( x): Return the index in the list of the ﬁrst item
whose value is x. It is an error if there is no such item.
 list. count ( x): Return the number of times x appears in the
list.
 list. sort ( ): Sort the items of the
list in place.

 We can also use lists as a stack in Python.
 Stack follows a property of last in first out(LIFO Rule).
 To add an item to the top of the stack, use append() .
 To retrieve an item from the top of the stack, use pop()
without an explicit index.

 Dictionary is defined as an unordered set of
key:value pairs, with the requirement that the
keys are unique .
 Dictionary is a Mutable datatype.
 Dictionaries are sometimes found in other languages as
“associative memories”
or “associative arrays”.
 Dictionaries are indexed by keys, which can be any
immutable type or could be a string.
 A pair of braces creates an empty dictionary: {} , not [].
 Keys could be a string in dictionary.

 We can nest dictionaries.
 Directly assign values to a dictionary.
 Dictionary comprehensions can be used to create
dictionaries from arbitrary key and value expressions:
 The dict() constructor builds dictionaries directly from
sequences of key-value pairs:
 Example : { ‘name’: ‘John’, ‘age’ : ‘seven’}

 Tuple is a sequence data type.
 Tuples are immutable, and usually contain a
heterogeneous sequence of elements.
 Simultaneous assignment is possible in tuples.
 In tuple, we can assign a tuple of value to a name.
 Example : S1=(‘John’ , ‘Rajkot’ )

 Tuples may be nested.
 A tuple consists of a number of values separated by
commas.
 Extract positions in tuples using slices.

 A set is an unordered collection with no duplicate
elements.
 Set objects also support mathematical operations
like union, intersection, difference, and symmetric
difference.
 Curly braces or the set() function can be used to
create sets.
 Creates an empty set using
 Set membership in sets
 We can convert a list into sets.
 Example : {1,2,3,4,5}

 Union : union of two sets is done using
“set1|set2”
”
 Intersection : intersection of two sets can be done
using “set1&set2”
 Set difference: In this, elements present in set2 is not
included in the resultant set. It can be don using “set1-set2
 Exclusive or: The syntax for exclusive or is “set1^set2”

 String is defined as a sequence or list of characters.
 String is immutable in nature means once defined , they
cannot be changed.
 str is the type for strings in python.
 Define strings using quotes (“ or ‘ or “““)
>>> st = “Hello World”
>>> st = ‘Hello World’
>>> st = “““This is a multi-line
string that uses triple quotes.”””
‘ ‘ can be used to escape quotes:

STRINGS
 The string is enclosed in double quotes, if the string
contains a single quote
and no double quotes, otherwise it is enclosed in single
quotes.
 The print() function produces a more readable output, by
omitting the enclosing quotes and by printing escaped and
special characters:
 ‘n’ is used to place a string in newline.
 Example : x=“John”

 If you don’t want characters prefaced by to be interpreted
as special characters, you can use raw strings by adding
an r before the ﬁrst quote:
 Two or more string literals (i.e. the ones enclosed between
quotes) next to each
other are automatically concatenated.
 Attempting to use an index that is too large
result in an error.

 To access substrings, use the square brackets for
slicing along with the index or indices to obtain your
substring.

 CONCATENATION (+) :
 adds value on the either sde of operator.
 REPETITION (*) :
 creates new strings,concatenating multiple copies of the same
strings.
 SLICE ([]) :
 gives the character from the given index
 RANGE SLICE ([ :]) :
 gives the character from the given range.

 MEMBERSHIP (in) or (not in) : membership returns true or
false if the character exist in the given string.
 length (len): It is used to find the length of the string.
 upper() : upper() is used to uppercase the string .
 lower() : lower() operation is used to lowercase the string.

 Cannot update a string “in place” as strings are
immutable in nature.
 Instead ,use slices and concatenation for
modification of strings:-

 A slice is a segment of string.
 Slicing allows you to obtain substring
 Syntax:


Str[start : end]
Start: substring start from this element
End: end of substring excluding the element at
this index
 S[i:j] starts at s[i] and ends at s[j-1]
 S[:j] means start at s[0], so s[0:j]
 S[i:] means ends at s[len(s)-1]

 str.format () is used to format the string.
 Examples: Replace argument by position in message string.
 Replace argument by names in message string.

Data structures in Python

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