# List Comprehensions

## The preferred 'pythonic' way to create a list

```python
numbers_0_to_9 = [x for x in range(10)]
print("Numbers 0 to 9", numbers_0_to_9)
```

```python
Numbers 0 to 9 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
```

## The above is equivalent to the following just more compact:

```python
numbers_0_to_9 = []
for x in range(10):
    numbers_0_to_9.append(x)
print("Numbers 0 to 9", numbers_0_to_9)
```

```
Numbers 0 to 9 [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
```

## You can also choose to do computation / flow control when generating lists

```python
squares = [x * x for x in range(10)]
print("Squares       ", squares)
```

```
Squares        [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]
```

## This example uses the "modulo" operator

```python
odds = [x for x in range(10) if x % 2 == 1]
print("Odds          ", odds)
```

## Advanced List Comprehensions \[optional]

If you're already an advanced programmer, you may be interested in some of these more advanced list comprehensions. They're one of the things that experienced Python users learn to love about Python.

This example also uses a data type called a namedtuple which is similar to a `struct` data type in other languages.

```python
# Import the module collections and be able to access namedtuple
# wihtout having to write collections.namedtuple each time.
from collections import namedtuple
# Create a tuple of class 'Person'
Person = namedtuple("Person", ["name", "age", "gender"])

# Build a list of people by using Person
people = [
    Person("Andy", 30, "m"),
    Person("Ping", 1, "m"), 
    Person("Tina", 32, "f"),
    Person("Abby", 14, "f"),
    Person("Adah", 13, "f"),
    Person("Sebastian", 42, "m"),
    Person("Carol" , 68, "f"),
]

# first, let's show how this namedtuple works.
# Get the first entry in the list (which is Andy from above)
andy = people[0]

# From here, you can access andy like it was a class with attributes
# name, age, and gender (as seeon from the namedtuple)
print("name:  ", andy.name)
print("age:   ", andy.age)
print("gender:", andy.gender)
```

```
name:   Andy
age:    30
gender: m
```

## now let's show what we can do with a list comprehension

```python
male_names = [person.name for person in people if person.gender=="m"]
print("Male names:", male_names)
```

```
Male names: ['Andy', 'Ping', 'Sebastian']
```

## Create a list of names where there age

```python
teen_names = [p.name for p in people if 13 <= p.age <= 18 ]
print("Teen names:", teen_names)
```