https://github.com/hcvazquez/python-basic-data-structures
Python basic data structures
https://github.com/hcvazquez/python-basic-data-structures
data-structures programming-language python
Last synced: 18 days ago
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Python basic data structures
- Host: GitHub
- URL: https://github.com/hcvazquez/python-basic-data-structures
- Owner: hcvazquez
- Created: 2019-05-27T01:10:38.000Z (about 7 years ago)
- Default Branch: master
- Last Pushed: 2019-05-30T02:57:49.000Z (about 7 years ago)
- Last Synced: 2025-12-01T20:38:56.402Z (7 months ago)
- Topics: data-structures, programming-language, python
- Language: Python
- Size: 10.7 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Python Basic Data Structures
Python has four basic inbuilt data structures namely Lists, Dictionary, Tuple and Set. These almost cover 80% of the our real world data structures. This article will cover the above mentioned topics.
## Lists
Lists : Lists in Python are one of the most versatile collection object types available. The other two types are dictionaries and tuples, but they are really more like variations of lists.
* Python lists do the work of most of the collection data structures found in other languages and since they are built-in, you don’t have to worry about manually creating them.
* Lists can be used for any type of object, from numbers and strings to more lists.
* They are accessed just like strings (e.g. slicing and concatenation) so they are simple to use and they’re variable length, i.e. they grow and shrink automatically as they’re used.
* In reality, Python lists are C arrays inside the Python interpreter and act just like an array of pointers.
```python
# Python program to illustrate
# A simple list
# Declaring a list
L = [1, "a" , "string" , 1+2]
print L
# add 6 to the above list
L.append(6)
print L
# pop deletes the last element of the list
L.pop()
print L
print L[1]
```
Output:
```python
[1, 'a', 'string', 3]
[1, 'a', 'string', 3, 6]
[1, 'a', 'string', 3]
a
```
There are various Functions that can be carried out on lists like append(), extend(), reverse(), pop() etc. To read more about lists methods you can click here.
## Dictionary
In python, dictionary is similar to hash or maps in other languages. It consists of key value pairs. The value can be accessed by unique key in the dictionary.
* Keys are unique & immutable objects.
* Syntax:
> dictionary = {"key name": value}
```python
# Python program to illustrate
# dictionary
# Create a new dictionary
d = dict() # or d = {}
# Add a key - value pairs to dictionary
d['xyz'] = 123
d['abc'] = 345
# print the whole dictionary
print d
# print only the keys
print d.keys()
# print only values
print d.values()
# iterate over dictionary
for i in d :
print "%s %d" %(i, d[i])
# another method of iteration
for index, value in enumerate(d):
print index, value , d[value]
# check if key exist
print 'xyz' in d
# delete the key-value pair
del d['xyz']
# check again
print "xyz" in d
```
Output:
```python
{'xyz': 123, 'abc': 345}
['xyz', 'abc']
[123, 345]
xyz 123
abc 345
0 xyz 123
1 abc 345
True
False
```
## Tuples
Python tuples work exactly like Python lists except they are immutable, i.e. they can’t be
changed in place. They are normally written inside parentheses to distinguish them from lists (which use square brackets), but as you’ll see, parentheses aren’t always necessary. Since tuples are immutable, their length is fixed. To grow or shrink a tuple, a new tuple must be created.
Here’s a list of commonly used tuples:
> () An empty tuple\
> t1 = (0, ) A one-item tuple (not an expression)\
> t2 = (0, 1, 2, 3) A four-item tuple\
> t3 = 0, 1, 2, 3 Another four-item tuple (same as prior line, just minus the parenthesis)\
> t3 = (‘abc’, (‘def’, ‘ghi’)) Nested tuples\
> t1[n], t3[n][j] Index\
> t1[i:j], Slice\
> len(tl) Length
```python
# Python program to illustrate
# tuple
tup = (1, "a", "string", 1+2)
print tup
print tup[1]
```
Output:
```python
(1, 'a', 'string', 3)
a
```
## Sets
Unordered collection of unique objects.
* Set operations such as union (|) , intersection(&), difference(-) can be applied on a set.
* Sets are immutable i.e once created further data can’t be added to them
* () are used to represent a set.Objects placed inside these brackets would be treated as a set.
```python
# Python program to demonstrate working of
# Set in Python
# Creating two sets
set1 = set()
set2 = set()
# Adding elements to set1
for i in range(1, 6):
set1.add(i)
# Adding elements to set2
for i in range(3, 8):
set2.add(i)
print("Set1 = ", set1)
print("Set2 = ", set2)
print("\n")
```
Output:
```python
('Set1 = ', set([1, 2, 3, 4, 5]))
('Set2 = ', set([3, 4, 5, 6, 7]))
```