In the last tutorials, you learnt about Python3: Variables. In this tutorial, you'll learn about lists and dictionaries. Let's get started!

Lists

Beside strings and integers, Python has all sorts of different types of objects. Now we're going to introduce one called list. Lists are exactly what you think they are: objects which are lists of other objects. :)

Go ahead and create a list:

type=codeblock|id=py3_empty_list|autocreate=python3
print([])
# Output: []

Yes, this list is empty. Not very useful, right? Let's create a list of lottery numbers. We don't want to repeat ourselves all the time, so we will put it in a variable, too:

type=codeblock|id=py3_list|autocreate=python3

Strings

Let's come back to strings. You already saw one in the beginning of the last tutorial.

How about your name? Type your first name in quotes like this:

type=codeblock|id=py3_strings|autocreate=python3
print("Commonlounge")

Output:

Commonlounge

As we said before, a string is a sequence of characters that can be processed by a computer. The string must always begin and end with the same character. This may be single (') or double (") quotes (there is no difference!) The quotes tell Python that what's inside of them is a string.

Strings can be strung together. Try this:

You can use Python on your computer in two ways — using the Python console, or by writing a Python program and running it. Let's discuss these one by one.

Python prompt

To start playing with Python, open up the command line on your computer. You should already know how to do that – you learned it in the Introduction to the Command-line Interface chapter.

Once you're ready, follow the instructions below.

We want to open up a Python console, so type in python on Windows or python3 on Mac OS/Linux and hit enter.

$ python3
Python 3.6.1 (...)
Type "help", "copyright", "credits" or "license" for more information.
>>>

After running the Python command, the prompt changed...

In this course, you will review the mathematics background required for data science, machine learning and deep learning.

The first 2 tutorials (+1 quiz) are a review of linear algebra and statistics. The 3rd tutorial (+1 quiz) is a review of probability.

These tutorials are meant to be a short review, they...

This short 5-part course provides a review of math topics for machine learning (linear algebra and statistics). It also teaches the Python NumPy library, which is used to handle vector and matrices in Python.

This is a 24-part course which will teach you JavaScript from scratch. It's designed to be very hands-on, and each new concept is followed with demonstrations, examples and exercises. You don't need to have any previous knowledge of programming or JavaScript!

The course is divided into three sections — set-up and installation, JavaScript programming and Web Development.

The quizzes, coding exercises and projects get more ...