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Decision Process
9:22With our tasks assigned, let's see how we can visualize our data to make better business decisions.
Let's start by thinking
about our three tasks and
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what charts would be appropriate for
their needs.
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Number one, average time of an eruption.
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We could use a box plot to showcase the
median time along with the quartile data,
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which should be helpful.
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We could also look at
a histogram here to see if
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it provides any better visualization.
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Number two, for the wait time information,
I think a box plot is a good tool here.
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Number three, since we're wanting
to determine a correlation
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between a couple of variables,
a scatter plot is a nice plot for this.
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Unlike our data, the old_faithful.csv
file includes a header row.
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We'll have to pop that
off to use our data.
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Let's start a new notebook called
old_faithful, and start with our imports.
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We'll import csv, and
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we'll import matplotlib.pyplot as plt.
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Now we'll set up our input file and
styling.
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This one is old_faithful.csv.
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Do our plot figure.
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We'll give it a figure size.
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Again, the 7.5 and 4.25 seems to work
pretty well for this screen resolution.
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And it's figsize, not figuresize.
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And we'll use the classic style again.
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Now we can read in our data, pop off our
header row, and create our eruption and
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wait times list.
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With open,
we'll bring in our input_file as read,
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as old_faithful data eruptions
will be our list name.
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And we are missing an underscore there.
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Pop off the header row.
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And create our empty list,
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For eruption_times and waiting_times.
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Now let's loop over the events and
append the data to the necessary list, for
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event, 0 through the length
of our eruptions,
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-1 there, so eruption_times,
and we're gonna append,
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The eruption event data.
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Move that up for clarity.
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Waiting_times, we'll do something similar.
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And that's in our second column.
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Great, now let's work through our
task list and generate our plots.
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Let's make these all subplots as well,
just to save some screen space.
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We'll start with a box plot
of our eruption time data.
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Subplot 2, 2, 1.
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Recall that this is saying that our
plot will have subplots of 2 rows,
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and 2 columns, and
this is the number 1 subplot.
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Make it a boxplot, and
we're passing in our eruption_times data.
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Let's make sure to give our
subplot titles and labels.
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Plt.title Old Faithful Eruptions.
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We'll adjust those xticks.
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So instead of a 1, It will be Eruptions
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The xlabel is the Length
of Eruption in minutes.
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Great, I think that does it for
our first plot.
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Now, we wanted to add a histogram here,
too, to see if that might be useful.
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So let's add another subplot and
create an 8-bin histogram.
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We'll move that up,
start our second subplot.
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8 bins, create our histogram
with the eruption_times.
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Then our number of bins variable.
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And add our labeling.
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And for our xlabel, Again,
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it's Length of Eruption in minutes.
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There we go,
that should take care of task one.
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Let's get our box plot for
the waiting time for task two.
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I'll cut and paste the eruptions box
plot and make the needed changes.
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So our subplot is gonna be plot 3.
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And we want waiting_times here and
not eruption_times.
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We'll just call this Old Faithful Waiting.
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And our tick will be Waiting.
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And Length of Waiting.
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Now for our scatter plot for task three.
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We'll make another subplot.
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And this will be in position 4.
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Let's give a little more space here.
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Plt.scatter eruption_times and
waiting_times.
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And add our title and labels.
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Old Faithful Eruptions.
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Xlabel, the Length of the Eruption,
again, in minutes.
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And our ylabel,
Time Between Eruptions, minutes.
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Now we can call plt.show and run our cell.
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There's all of our plots, but
they're all smooshed together,
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not a great presentation.
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Matplotlib provides a method to adjust
padding between subplots called
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tight_layout.
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Let's call that before we call show and
see how that cleans things up.
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I'll put a link to more information
about tight_layout in the teacher's
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notes as well.
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And run our cell.
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That looks a lot better.
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You'll notice here that based
on the eruption duration and
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waiting times, combining those
two charts won't be super useful.
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Eruption duration is very short
in comparison to waiting time.
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This is a great example of
where scale is important.
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I'm also not entirely certain of
the usefulness of the histogram for
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Steve's purposes.
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So in the final presentation,
we may wanna leave that out.
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Now that we've generated a few charts,
let's have a quick break.
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When we get back,
we'll sum up our project tasks and
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get our presentation ready for Steve.
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