This if the final course in the specialization which builds upon the knowledge learned in Python Programming Essentials, Python Data Representations, and Python Data Analysis. We will learn how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data. This course will combine the skills learned throughout the specialization to enable you to write interesting, practical, and useful programs. By the end of the course, you will be comfortable installing Python packages, analyzing existing data, and generating visualizations of that data. This course will complete your education as a scripter, enabling you to locate, install, and use Python packages written by others. You will be able to effectively utilize tools and packages that are widely available to amplify your effectiveness and write useful programs.
Using Python Documentation
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Do curso por Rice University
Python Data Visualization
110 classificações
Na lição
Week 1
This module will discuss the importance of using and writing documentation. The Python documentation is a valuable resource for learning about language features you haven't seen yet.
Conheça os instrutores
Scott RixnerProfessor
Computer Science
Joe WarrenProfessor
Computer Science
[MUSIC]
No matter how much we teach you about Python,
there will always be more to learn.
So it's important to be able to read the documentation
in order to find out what you don't know.
In this video, I'm going to walk you through the official Python documentation,
show you it's structure, and get you more comfortable with looking through it to
find out how to do different things in Python.
So, let's check it out.
So here we are at the front page of the official Python documentation.
As you can see, I'm currently looking at the documentation for Python 3.6.3.
You're going to be looking at probably a different version depending on what you
actually have installed when you're looking at the documentation.
If you go to this page, through, it will, by default,
go to the most recent version of Python.
And that's probably what you want.
Now, look here, we have a tutorial section.
This is a good place to start, although a lot of the things in here,
you've already learned.
But this tutorial goes about teaching you in a nice,
friendly way and shows you how to do things with examples.
So let's say I wanted to learn about if statements.
I could click here, and you can see that there is some nice code that shows me how
an if statement works, and a little bit of text explaining exactly what's going on.
Now, even though you probably know a lot of the things that are here in these
tutorials, there are some aspects of the language that we have not taught you.
And there are some nice tutorials that show you how they work, and so
you could still benefit from looking through the tutorials to see things that
you haven't learned yet.
Now, the tutorials just give you some quick examples on how to
use many different basic features of the language.
When you want to find out more comprehensive information about
how Python works and what the capabilities are,
the library reference, here, is really the place to go.
So if I look in the library reference,
this talks about pretty much all aspects of the Python language.
As such, it's probably the most valuable part of the Python documentation, and
this is probably where you're going to spend most of your time when you
are looking at the Python documentation for everyday use.
So let's first look at, we have a whole section here on built-in functions.
And so you can see,
here's a nice list of all the different built-in functions that Python has.
Let's check it out.
Hey, there's something called, any.
Wonder what that does.
We can see that, any, takes an iterable as an argument.
So what's an iterable?
Well that's any sort of sequence that I can iterate over,
so a list could be a dictionary, a tuple, and so on.
And what this does is it returns,
True, if any element of the iterable evaluates to, True.
If the iterable's empty, it returns, False,
and if nothing in the iterable is true, it also returns, False.
And you can see, they even give you a little snippet of Python code and said,
hey, you can write this code here and you'd get the same result.
Now, using, any, is likely to be far more efficient than writing that Python code,
because I'm sure they take shortcuts and
write it in a very efficient way since it's a built-in and
they know that everybody's going to be using it all the time.
Alright, what other built-ins do we have?
We can take a look here, again, and, hm, hey, there's something called, min.
I wonder what that does.
I can kind of guess from the name, unlike, any.
I wasn't really sure there.
If we look at, min, It says,
return the smallest item in an iretable or the smallest of two or more arguments.
So there's actually two different ways that I can call this.
I can either pass it in an iterable, and
it will find the minimum value within that iterable and return it to me.
Or I can pass it in a bunch of arguments, two or more,
and it will find the smallest of the arguments that I pass in.
Well, that seems handy if I want to find the minimum of something.
And then it goes on to give me a bunch of information
about some additional capabilities that this function has.
And I'll let you read that, but I can now learn something new here, right?
I now find out exactly how I can go about finding the minimum of numbers,
and I can actually do it in more complicated ways.
If you read through here, it's got some nice capabilities.
All right, let's see what else we can take a look at if we go back up to the top
level of the documentation here.
And, see, there's a whole section on built-in types, all right, and there
are some things that I'm familiar with, like int, or float, lists, and so on.
But here's one I'm not, there's these Set Types.
So there are two different set types, a set and a frozen set.
And if I just read a little bit here,
it says a set object is an unordered collection of distinct hashable objects.
Common uses include membership testing, removing duplicates from the sequence, and
computing mathematical operations, such as intersection, union difference, and
symmetric difference.
Hm, well, that sounds interesting.
This is basically the concept of a mathematical set.
We'll learn more about sets later in this course, but I just wanted to point out,
hey, I can find this in the documentation.
I can read up on here and
see all the different operations that I can perform on sets, right?
There are other data types that we could look in as well, but I also want to
keep scrolling down here and see what else we can find in the documentation.
All right, I'm starting to recognize some things.
If I look in the datetime section here, I see a date time module.
That may be familiar to those of you who have been with us throughout this
specialization.
So I look at datetime, basic date and time types.
The datetime module supplies classes for manipulating dates and times.
Well, we've used that before, and so
we can see that all of these modules have some comprehensive documentation.
Let's see what else we can find.
What have we been using lately?
The csv module.
Let's see if we can find the csv module anywhere, must be here, here we go.
Right here, I can find the csv module, and
now I can get comprehensive documentation for the csv module as well.
Now we saw that there was a built-in called, any.
I wonder if there's a built-in called, all.
And instead of going back to take a look at that,
I actually want to try and search for it.
So, If I move the window here a little bit,
you can see there is a search bar here, and I'm going to try it.
I'm just going to type, all, and see what happens.
Okay, so I search, and a whole bunch of things come up.
And if we look, hey, here is a Python function, a built-in function.
I can click on that, and
we will see information about the built-in function called, all.
As I was guessing, from the fact that there was one called, any, all returns,
True, if all elements of the iterable that it takes as an argument are true.
Or if it's empty, [INAUDIBLE] again, they give me a nice little snippet of code that
tells me what, all, is equivalent to if I were to write it myself.
Okay, so searching is also quite valuable if you know what you're looking for,
or at least you have a word that you feel like you could search for
that would maybe give you the kinds of things that you wanted.
And I just wanted to show you that that's also a possibility here.
So I've shown you,
in this video, a few of the highlights of the official Python documentation.
There are tutorials that help you get up to speed,
quickly, on some of the basic elements of the language.
And after having taken our classes,
you should be able to zip through a lot of those tutorials and
maybe find some new information in there that you can find valuable.
And then, the library reference is really
the main component of the documentation that I think you're going to find useful.
It had information about the built-in functions, the different types in Python,
and an exhaustive list of all the built-in modules in Python that give you
significant added capability to the language.
And I showed you how to look up a few things there, and
hopefully you will also be able to make use of the search function in
the documentation if you can't find it by browsing through.
Now that you have the documentation at your fingertips, hey,
I don't need to teach you anything anymore, right [LAUGH]?
You can just go read about it.
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