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With our tasks assigned, let's see how we can visualize our data to make better business decisions.
Matplotlib Version Update
At around 8:20 in the video, the scatter plot shown doesn't show a good correlation between data points. This course was recorded with matplotlib version 2.0.2 and in current versions of the library, the implementation of scatter plots has changed.
Instructions to add files to your notebook
- Download the project files using the Download tab above.
- Unzip the file and navigate to the folder "s3v2" (Stage 3, Video 2).
- In your Notebook, go to File > Open and navigate to the unzipped folder.
From there you can view files just like we're doing in the video.
Further Reading
- Matplotlib Tight Layout Guide
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Let's start by thinking
about our three tasks and
0:00
what charts would be appropriate for
their needs.
0:03
Number one, average time of an eruption.
0:05
We could use a box plot to showcase the
median time along with the quartile data,
0:10
which should be helpful.
0:15
We could also look at
a histogram here to see if
0:17
it provides any better visualization.
0:20
Number two, for the wait time information,
I think a box plot is a good tool here.
0:23
Number three, since we're wanting
to determine a correlation
0:29
between a couple of variables,
a scatter plot is a nice plot for this.
0:33
Unlike our data, the old_faithful.csv
file includes a header row.
0:37
We'll have to pop that
off to use our data.
0:44
Let's start a new notebook called
old_faithful, and start with our imports.
0:46
We'll import csv, and
0:54
we'll import matplotlib.pyplot as plt.
0:57
Now we'll set up our input file and
styling.
1:06
This one is old_faithful.csv.
1:14
Do our plot figure.
1:19
We'll give it a figure size.
1:23
Again, the 7.5 and 4.25 seems to work
pretty well for this screen resolution.
1:24
And it's figsize, not figuresize.
1:34
And we'll use the classic style again.
1:45
Now we can read in our data, pop off our
header row, and create our eruption and
1:51
wait times list.
1:56
With open,
we'll bring in our input_file as read,
2:00
as old_faithful data eruptions
will be our list name.
2:05
And we are missing an underscore there.
2:23
Pop off the header row.
2:30
And create our empty list,
2:35
For eruption_times and waiting_times.
2:48
Now let's loop over the events and
append the data to the necessary list, for
2:51
event, 0 through the length
of our eruptions,
2:56
-1 there, so eruption_times,
and we're gonna append,
3:07
The eruption event data.
3:19
Move that up for clarity.
3:25
Waiting_times, we'll do something similar.
3:29
And that's in our second column.
3:39
Great, now let's work through our
task list and generate our plots.
3:47
Let's make these all subplots as well,
just to save some screen space.
3:53
We'll start with a box plot
of our eruption time data.
3:57
Subplot 2, 2, 1.
4:02
Recall that this is saying that our
plot will have subplots of 2 rows,
4:05
and 2 columns, and
this is the number 1 subplot.
4:10
Make it a boxplot, and
we're passing in our eruption_times data.
4:17
Let's make sure to give our
subplot titles and labels.
4:25
Plt.title Old Faithful Eruptions.
4:33
We'll adjust those xticks.
4:43
So instead of a 1, It will be Eruptions
4:47
The xlabel is the Length
of Eruption in minutes.
4:58
Great, I think that does it for
our first plot.
5:08
Now, we wanted to add a histogram here,
too, to see if that might be useful.
5:13
So let's add another subplot and
create an 8-bin histogram.
5:17
We'll move that up,
start our second subplot.
5:23
8 bins, create our histogram
with the eruption_times.
5:35
Then our number of bins variable.
5:43
And add our labeling.
5:46
And for our xlabel, Again,
5:59
it's Length of Eruption in minutes.
6:04
There we go,
that should take care of task one.
6:11
Let's get our box plot for
the waiting time for task two.
6:15
I'll cut and paste the eruptions box
plot and make the needed changes.
6:19
So our subplot is gonna be plot 3.
6:29
And we want waiting_times here and
not eruption_times.
6:35
We'll just call this Old Faithful Waiting.
6:43
And our tick will be Waiting.
6:52
And Length of Waiting.
6:58
Now for our scatter plot for task three.
7:04
We'll make another subplot.
7:09
And this will be in position 4.
7:15
Let's give a little more space here.
7:16
Plt.scatter eruption_times and
waiting_times.
7:22
And add our title and labels.
7:32
Old Faithful Eruptions.
7:36
Xlabel, the Length of the Eruption,
again, in minutes.
7:45
And our ylabel,
Time Between Eruptions, minutes.
7:56
Now we can call plt.show and run our cell.
8:08
There's all of our plots, but
they're all smooshed together,
8:16
not a great presentation.
8:19
Matplotlib provides a method to adjust
padding between subplots called
8:22
tight_layout.
8:25
Let's call that before we call show and
see how that cleans things up.
8:27
I'll put a link to more information
about tight_layout in the teacher's
8:31
notes as well.
8:33
And run our cell.
8:43
That looks a lot better.
8:47
You'll notice here that based
on the eruption duration and
8:49
waiting times, combining those
two charts won't be super useful.
8:52
Eruption duration is very short
in comparison to waiting time.
8:57
This is a great example of
where scale is important.
9:01
I'm also not entirely certain of
the usefulness of the histogram for
9:04
Steve's purposes.
9:08
So in the final presentation,
we may wanna leave that out.
9:09
Now that we've generated a few charts,
let's have a quick break.
9:13
When we get back,
we'll sum up our project tasks and
9:17
get our presentation ready for Steve.
9:20
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