Notice that when we want to invoke the
randint() function we call
random.randint(). This is default behavior where Python offers a namespace for the module. A namespace isolates the functions, classes, and variables defined in the module from the code in the file doing the importing. Your local namespace, meanwhile, is where your code is run.
Python defaults to naming the namespace after the module being imported, but sometimes this name could be ambiguous or lengthy. Sometimes, the module’s name could also conflict with an object you have defined within your local namespace.
Fortunately, this name can be altered by aliasing using the
import module_name as name_you_pick_for_the_module
Aliasing is most often done if the name of the library is long and typing the full name every time you want to use one of its functions is laborious.
You might also occasionally encounter
import *. The
* is known as a “wildcard” and matches anything and everything. This syntax is considered dangerous because it could pollute our local namespace. Pollution occurs when the same name could apply to two possible things. For example, if you happen to have a function
floor() focused on floor tiles, using
from math import * would also import a function
floor() that rounds down floats.
Let’s combine your knowledge of the
random library with another fun library called
matplotlib, which allows you to plot your Python code in 2D.
You’ll use a new
random.sample() that takes a range and a number as its arguments. It will return the specified number of random numbers from that range.
#random.sample takes a list and randomly selects k items from it new_list = random.sample(list, k) #for example: nums = [1, 2, 3, 4, 5] sample_nums = random.sample(nums, 3) print(sample_nums) # 2, 5, 1
import codecademylib3_seaborn, import
pyplot from the module
matplotlib with the alias
random below the other import statements. It’s best to keep all imports at the top of your file.
Create a variable
numbers_a and set it equal to the range of numbers 1 through 12 (inclusive).
Create a variable
numbers_b and set it equal to a random sample of twelve numbers within
Feel free to print
numbers_b to see your random sample of numbers.
Now let’s plot these number sets against each other using
plt.plot() with your two variables as its arguments.
plt.show() and run your code!
You should see a graph of random numbers displayed. You’ve used two Python modules to accomplish this (