We've already covered strings, and learned about `bytes`

and `bytesarrays`

in the previous lesson. Now let's dive into the more interesting sequences - ranges, tuples and lists.

Ranges are a list of integers, usually in a consecutive order. They are most commonly used to initiate and feed values within loops.

There are several options for declaring a range.

`range(n)`

`0`

up to but not including`m`

.`range(m,n)`

`m`

up to but not including`n`

.`range(m, n, step)`

`m`

up to but not including`n`

with increments step.

Tuples are immutable sequences that can contain any type of element.

Tuples are declared with parentheses (`()`

). We can have a one-element tuples such as `test,)`

or an empty tuple `()`

. The comma for one-element tuples is necessary since the parentheses can be interpreted as a mathematical notation.

A simple example of a tuple is the a pair of numbers describing the xy-coordinate system.

given a sequence as an argument, tuple function creates a tuple containing the elements of the sequence

```
>>> tuple('banana')
('b', 'a', 'n', 'a', 'n', 'a')
>>> tuple(range(2, 10, 2))
(2, 4, 6, 8)
```

Since functions may return only one value, it's useful to use tuples when we want to return two or more datasets.

```
>>> def doubleTwoNumbers(x,y):
... return (2*x, 2*y)
>>> print(doubleTwoNumbers(4,5))
(8, 10)
```

You can easily exchange tuples with `left, right = right, let`

. Let's see how we can use tuples to write out the fibonacci sequence.

```
>>> def fib(n):
... a,b = 1,1
... for i in range(n-1):
... a,b = b,a+b
... return a
>>> fib(5)
5
```

Lists are a comma-separated series of mutable values of any type of element. They're like a tuples, but better, with added flexibility.

Lists may contain items of different data types, but *usually*, they're all of the same type.

Lists are declared between square brackets (`[]`

).

```
>>> fruits = ['apple', 'banana', 'pineapple']
>>> print(fruits)
['apple', 'banana', 'pineapple']
>>> min(fruits)
'apple'
>>> 'pineapple' in fruits
True
>>> vegetables = ['kale', 'carrot', 'lettuce']
>>> vegetables + fruits
['kale', 'carrot', 'lettuce', 'apple', 'banana', 'pineapple']
```

As you can see, you can apply any sequence functions to our lists.

You may also nest lists to create lists within lists.

```
>>> nested = [['a', 'b', 'c'], 'c']
>>> nested[0]
['a', 'b', 'c']
>>> nested[1]
'c'
```

One unique property of lists is that they are mutable. This means you can change a variable from within the list. Take a look here of the list `l`

and min/max indices `i`

and `j`

.

`l[i] = x`

- Replace value at index
`i`

with value`x`

. `l[i:j] = coll`

- Replace value from
`i`

up to but not including`j`

with`coll`

. `l[i:j] = []`

- Delete values stored from
`i`

up to but not including`j`

. `l[i:j:k] = coll`

- Replace incrementally with step size
`k`

. `l[n:n] = coll`

- Insert elements of
`coll`

before the`n`th element of the list. `l[:] = coll`

- Replace entire contents of list
`l`

with`coll`

.

Another way to remove list items is with the `del`

keyword.

`del lst[n]`

- Remove the
`n`

th element from lst. `del lst[i:j]`

- Remove elements from
`i`

through but not including`j`

. `del lst[i:j:k]`

- Remove every
`k`

th element from`i`

up to but not including`j`

.

`l.extend(L)`

- Extend the list by appending with collection
`L`

. `l.insert(i, x)`

- Inserts
`x`

before the`i`

th element of`l`

. `l.remove(x)`

- Remove the first occurrence of
`x`

. - If
`x`

does not exist, an error comes up. `l.append(x)`

- Append
`x`

to the end of`l`

. `l.pop([i])`

- Remove the
`i`

th element and return it. `l.reverse()`

- Reverses the list.
`l.sort()`

- Sort the list
`l`

.

Programming Python shows in-depth tutorials on the language's number of application domains including: system administration, GUIs, the Web, networking, front-end scripting layers, and more. This book focuses on commonly used tools and libraries to give you a comprehensive understanding of Pythonâ€™s many roles in practical, real-world programming.

$ Check price(56+ reviews)

Ever feel achy from sitting crunched up on your computer table? Try lying down with these optical glasses that allow you to work on your laptop while lying flat on your back. This is the perfect solution with those with limited mobility or those who wish to prevent neck cramps and back strains.

$ Check price(128+ reviews)

Ad