Continuing with a functional approach of python we take a look to the List functions. we will provide a little example for each one of this functions. This functions are map, reduce and filter.

## Map

Map applies a function to each one of the elements of a sequence

```
secuence = list(range(0,10))
# secuence = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
f = lambda x: x + 1
map(f, secuence)
# result [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
```

## Filter

Filter reduces a secuence depending of a boolean function

```
secuence = list(range(0, 10))
# secuence = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
f = lambda x: x % 2 == 0
filter(f, secuence)
#result = [0, 2, 4, 6, 8]
```

## Reduce

Reduce, is a operation that "reduces a list" apliying an operator

```
from functools import reduce
secuence = list(range(0, 10))
# secuence = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
f = lambda x, y: x + y
reduce(f,secuence)
# result = 45
# Using initial value, thanks to @magicleon94
reduce(f,secuence, 10)
# result = 55
```

## Discussion

An interesting thing you might point out is that

`reduce`

takes an optional third parameter, which is an initial value. This could be useful in some situationI will add it to post, thanks!

Could you please explain statement ? I know

f = lambda x, y: x + y

is a function that add two numbers, i store it on a variable. You can use it with f(2, 1)