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.
Line Plots with Pygal
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來自 Rice University 的課程
Python Data Visualization
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Week 2
This module will teach you about packages and modules in Python, including how to install packages and how to create your own modules. You will also learn to use the Pygal plotting library.
與講師見面
Scott RixnerProfessor
Computer Science
Joe WarrenProfessor
Computer Science
[MUSIC]
In this video I'm going to show you how to create basic line plots using pygal.
I'll show you both how to create a conventional line plot and
how to create an xy scatter plot.
This will also allow you to see the differences between these two types
of plots.
This will give you a feel for how you can go about creating plots using pygal.
I'm going to show you two functions here.
The first one is going to allow us to draw a line plot.
And I'm going to take 3 arguments.
The title that I'd like to appear in the plot and then a sequence of x values and
a sequence of y values.
And the first thing we need to do is create the line plot on which we're going
to put our data.
And you do that by calling pygal.Line.
And you'd see here I passed the height value, you need not to do that.
But it's going to make it easier to display the results in a way that you'll
be able to see in this video.
Then I can set the title to be whatever I want, so
I say lineplot.title equals some string that will become the title of the plot.
Then I want to use the x values to label the x axis of the plot.
So I set lineplot.x_labels to be xvals, so that sequence now
becomes the x values that are labeling the x axis of my plot.
Then I use lineplot.add and .add in pygal is the way to
add new sequences of data that you want to actually plot.
And you first give it the name of that data so that it'll appear in the legend.
I'm just going to call it "Data" and then you give it the actual data,
which in this case is just a sequence of y values.
And then finally, I have to render the plot somehow and I'm just going to show
them the browser, so I'm going to use lineplot.render_in_browser().
It took a little set up to get that working.
There are other rendering options that may work a little bit easier for you.
Now I have two sequences of data,
both have ten numbers in them called xvals here and yvals.
And then I'm going to call draw_line with the name "My Line Plot" and
the sequences of xvals and yvals.
So let's see what happens here.
Well, it rendered a line plot, and we can see the title, My line plot, and
then we can see my data.
Now something to notice here, notice what happened on the x-axis.
The numbers that I had in my xvals are evenly spaced, so
it doesn't interpret what's going on at all.
When I do a line plot in pygal,
all of the successive data items get plotted, evenly space.
And so you can see we have 0, 1, 3, 5, 6, and so on along the x-axis.
They're evenly spaced, there's a point at each location with a corresponding yval.
Now let's go back to the program, take a look at the program here.
I also have a function that I am calling draw_xy.
In the draw_xy function also takes a title, takes a sequence of x values and
the sequence of y values, and now I'm going to draw an xy scatter plot.
The difference between an xy plot is that I provide both the x value and
the y value of the coordinate as a tuple so
that pygal knows exactly where you want that point placed.
It does not assume that all of the values in the data should be
evenly spaced consecutively.
So at first I have to take that sequence of x values and y values, and
turn them into a sequence of tuples.
And to do this I'm going to use a list comprehension,
that list comprehension creates a tuple, xval, yval for
all the xval and yval values in, now what do we have here?
zip(xvals, yvals).
While I encourage you to read the documentation on zip, but effectively what
zip does is it takes multiple sequences and it zips them together, like a zipper.
So it takes the first element off of each of the sequences and
puts them in a tuple and returns that.
And then it takes the next element off each of the sequences,
puts them into tuple and returns that is the next value of the iteration.
So if I do that, I'm going to get a sequence of tuples where all the x
values and y values are put together and correlated.
So, you can see here, the xvals start with 0, 1, 3.
The yvals start with 4, 3, 1.
This will create tuple of 0, 4 then tuple 1, 3 then tuple 3, 1 and so on.
Instead of calling pygal.line, we now call pygal.XY.
That creates an XY plot that we can add data to.
We set the title in exactly the same way, xyplot.title = title.
Now we don't have to tell it what the x labels are,
because it's going to figure it out based on the data that we pass it.
So then we add our data in.
We can call it data for the legend, but we're passing now a sequence of
coordinates that have xy values in them and then rendering in the browser.
So let's see what happens here.
All right, as you can see our plot looks a little bit different.
There is now not a point at every tick.
You can see that we have a point at the x value of 0, point at the x value of 1.
We don't have any point at the x value 2.
And then we have one at 3, nothing at 4, and 5 and so on.
So now because we passed xy tuples,
pygal places the points at exactly the xy coordinates we specified.
Instead of just using the x values as the labels for the x axis and
the y values as the height for each particular label.
This is more realistic if we were actually trying to
plot data that did not have sequential x values.
If the data did have sequential x values though,
you've probably realized that we'd end up with
basically exactly the same plots whether we do a line plot or an XY scatter plot.
Now you should have a feel for how to create plots using pygal.
It's reasonably straightforward.
You simply have to create a plot of the appropriate type and
then you add data to it.
You can also set the title for the plot, you can set titles for the axis as well.
I encourage you to read the documentation to find out more about the capabilities
of pygal.
But this should be enough to get you started.
So go ahead and start planning your favorite data.
