The list data type has the following built-in methods
- append(x)
- extend(iterable)
- insert(i, x)
- remove(x)
- pop(\[i\])
- clear()
- index(x\[, start\[, end\]\])
- count(x)
- sort(*, key=None, reverse=False)
- reverse()
- copy()

Built-in methods of Lists

The various sequence operations on lists in ascending priority are listed below. 

- in
- not in
- "+"
- "*"
- indexing i th item of a list
- slicing the list from i to j  ( i and j are integers )
- slicing with a step
- len() ( length of a list which is passed as the argument of the function len() ) 
- min() ( smallest item in the list )
- max() ( largest item in the list )
- index of an element in the list at or after an index and before another index
- count ( total number of occurrences of a particular element in the list )

Common Sequence Operations on Lists

The Map() function can be used to apply a function to a sequence of elements.


An example:
```python

def square(num):
    return num * num

my_map = map(square, [1, 3, 9])
# my_map returns -> [1, 9, 81]
```

Map() in Python

List Comprehension in Python provides an easy way to initialize and populate a list in one line. It consists of an expression followed by a ```for``` clause and an ```if```` clause if necessary. For example, if you have a list of words and want to create a list of only those words which contain the letter i, you could use the example code below.
```python
words = ["icky", "gross", "nasty", "illness", "disease"]
newWords = []

for x in words:
  if "i" in x:
    newWords.append(x)

print(newWords) #this will print: ['icky', 'illness', 'disease']
```

List Comprehension

- List is a built-in data type, it is also a collection datatype(  lists accommodate elements/items of various datatype )
- List is also a sequence data type which can accommodate items of various basic data types  like integers, float etc. but usually items in a list are of same basic data type.
-  A list contains values separated by comma inside a square bracket.
- Lists are resizable. Items in a list can be added, removed and modified after the list is created.
- Lists are mutable, that means  contents of a list can be changed.
- Lists can be nested, that means we can create a list containing another list.

``` python
my_list = [1,"1cademy",12.59,True]
my_list
```
Output

``` python
[1, '1cademy', 12.59, True]
```

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Data structures facilitate the organization of data in computer memory in an efficient manner which further support faster and more flexible data manipulations.


The python interpreter offers the following built-in data structures:


- List
- Set
- Tuple
- Dictionary


Data Structures in Python

Python Documentation

List

- A set is an unordered collection of data.
- The items in a set are unordered, unmutable, and cannot contain duplicate values.
- Mathematical operations (e.g. union, intersection, difference, symmetric difference) can be performed on sets.
- To create a set, list elements separated by commas within two curly braces.

Example:
```python
set = {"apple", "orange", "banana"}
```


- A tuple is a data structure that can store items within a single variable.
- The items in a tuple are ordered (indexed) and are immutable (cannot be changed).
- Tuples can have duplicate items.
- To create a tuple, surround items (separated by commas) with parentheses.
Ex:
```python
tuple = ('apple', 34, 'banana')
```
- To access an element inside a tuple, use the tuple name along with square brackets and the desired index.
Ex:
```python
tuple[1] # access tuple index 1, which is 34.
```

Tuple

• Dictionary is a built-in data structure. A dictionary is an ordered and mutable collection of objects.
• It consists of Key-Value pairs. Each Key must be Unique.

Syntax:
```python
dictionary = {"key name": value}
```
```python
student_scores = {
    "John" : 76,
    "Peter": 95,
    "Mike": 84
}
```
We can access the Values using the Keys:
```python
print(student_scores["John"])
```
This ```python print() ``` statement would print out the value 76. It is also important to note that keys must map to a unique value. 


Dictionary 

There are other basic data structures that are not defined in the Python standard library. These include:

- Linked List
- Stack
- Queue
- Tree
- Heap
- Graph

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