DATA
S T R U C T U R E S
CH E A T
S H E E T
L i s t s a n d T u p l e s i
n P y t h o n
Ordered sequence of values indexed by integer numbers. Tuples are
immutable
• To specify size of tuple/list:
• To initialize empty list /tuple: Synatx:
len(myListOrTuple)
Syntax: Lists: myList = []
D i c t i o n a r i e s
It is an unordered set of key value pairs
• Initialize an empty Dict
Syntax: myDict = {}
• Add an element with key "k" to the Dict
D a t a T y p e s
It is a way of organizing data that contains the items stored
and their relationship to each other
The areas in which Data Structures are applied:
Tuples: myTuple = ()
• To get an element in position x in
list/tuple: Syntax: "x" in
myListOrTuple
• Index of element ‘X’ of list/tuple
Syntax:
myListOrTuple.index("x") -
- If not found, throws a
ValueError exception
• Number of occurance of X in
list/tuple:
Syntax:
myListOrTuple.count("x")
• Remove element in position X of
list/tuple:
Syntax: Lists: del
myList[x] Tuples: tuples
are immutable!
• Concatenate two lists/tuples:
Lists: myList1 + myList2
Tuples: myTuple1 +
myTuple2
Concatenating a List and a
Tuple will produce a
TypeError exception
• Insert element in position x of a
list/tuple Syntax: Lists:
myList.insert(x,
Syntax: myDict["k"] = value
• Update the element with key "k"
Syntax: myDict["k"] = newValue
• Get element with key "k"
Syntax: myDict["k"] -- If the key is
not present, a KeyError is raised
• Check if the dictionary has key "k"
Syntax: "k" in myDict
• Get the list of keys
Syntax: myDict.keys()
• Get the size of the
dictionary
• Compiler design
• Operating system
• Database Management
System
• Statistical Analysis
Package
• Numerical Analysis
• Graphics
• Artificial Intelligence
• Simulations
Data structures can be
used in the following
areas:
• RDBMS: Array (
Array of structure)
• Network data
model: Graph
• Hierarchical Data
model: Trees
• Update an item of List/tuple:
Syntax: Lists: myList[x] =
"x“
Tuples: tuples are
immutable!
• Remove element in position X of
list/tuple:
Syntax: Lists: del myList[x]
Tuples: tuples are
immutable!
"value")
Tuples: tuples are
immutable!
• Append "x" to a list/tuple:
Syntax: Lists:
myList.append("x") Tuples:
tuples are immutable!
• Convert a list/tuple to tuple/list:
Syntax: List to Tuple:
tuple(myList) Tuple to List:
list(myTuple)
Syntax: len(myDict)
• Delete element with key "k" from the dictionary
Syntax: del myDict["k"]
• Delete all the elements in the dictionary
Syntax: myDict.clear()
Data Structures
Primitive Data
Structures:
T y p e s o f D a t a S t
r u c t u r e s
Non- Primitive Data Structures:
1 † - Uniform hashing assumption
• Integer: It is used to represent numeric data, more specifically
whole numbers from negative infinity to infinity. Eg: 4, 5, -1 etc
• Float: It stands for floating point number. Eg: 1.1,2.3,9.3 etc
• String: It is a collection of Alphabets, words or other characters.
In python it
• Array: It is a compact way of collecting data types where all entries must
be of the same data type.
Syntax of writing an array in
python: import array as arr
a = arr.array("I",[3,6,9])
S e t s
It is an unordered collection with no duplicate elements. It supports mathematical
operations like union, intersection, difference and symmetric difference.
Primitive Non -
Primitive
can be created by using a pair of single or double quotes for
the sequence.
Eg: x = 'Cake’
y = '’Cookie’’
type(a)
• Linked list: List in Python is used to store collection of
heterogeneous items. It is described using the square brackets []
and hold elements separated by comma
Eg: x = [] # Empty list
• To initialize an empty
set:
Syntax: mySet =
set()
• Initialize a non empty set
• Union of two sets
Syntax:
Method 1:
mySet1.union(mySet2)
Method 2: mySet1 |
mySet2
Integer Float String Boolean
Certain operations can be performed on
a string:
type(x)
oThe list can be classified into linear and non-linear
data structures
Syntax: mySet =
set(element1, element2...) • Intersection of two
sets
Array List
Tuple
Dictiona
ry
Set File
oWe can use * to repeat the
string for a specific number of
times. Eg: x*2
oString can be sliced, that is to
select parts of the string.
Eg: Coke
z1 = x[2:]
print(
z1) # Slicing
z2 = y[0] + y[1]
print(z2) Output: ke
Co oTo capitalize the strings
Eg: str.capitalize('cookie')
oTo retrieve the length of the strings
Eg:
str1 = "Cake 4 U" str2 = "404" len(str1)
oTo replace parts of a string with another string
Python - Data Structure
Algorithm Best case Average
case Worst case Remarks
Selecti
on
sort
½ n 2½ n 2½ n 2n exchanges,
quadratic is the best case
Insertion
sort n ¼ n 2½ n 2Used for small or partial-
sorted arrays
Bubb
le
sort
n ½ n 2½ n 2
Rarely useful,
Insertion sort can be
used instead
Shell sort n log3 n unknown c n 3/2
Tight code,
Sub quadratic
Merge
sort ½ n lg n n lg n n lg n n log n guarantee;
stable
Quick sort n lg n 2 n ln n ½ n 2
n log n probabilistic
guarantee;
fastest in practice
Heap sort
n
†
2 n lg n 2 n lg n n log n guarantee;
in place
Worst Case Average Case
Data Structure Search Insert Delete Search Insert Delete
Sequential
search n n n n n n
Binary search log n n n log n n n
Binary search
tree n n n log n log n sqrt(n)
Red-black BST log n log n log n log n log n log n
Hash table n n n
1
†
1
†
1
†
