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At this point, you’ve learned how to find the numerical inputs to a histogram. Thus far the size of our datasets and bins have produced results that we can interpret. This becomes increasingly difficult as the number of bins in a histogram increases.

Because of this, histograms are typically viewed graphically, with bin ranges on the x-axis and counts on the y-axis. The figure below shows the graphical representation of the histogram for our exercise class example from last exercise. Notice, there are five equally-spaced bars, with each displaying a count for an age range. Compare the graph to the table, just below it. 20-29 30-39 40-49 50-59 60-69
7 4 4 3 2

Histograms are an easy way to visualize trends in your data. When I look at the above graph, I think, “More people in the exercise class are in their twenties than any other decade. Additionally, the histogram is skewed, indicating the class is made of more younger people than older people.”

We created the plot above using the `matplotlib.pyplot` package. We imported the package using the following code:

``from matplotlib import pyplot as plt``

We plotted the histogram with the following code. Notice, the `range` and `bins` arguments are the same as we used in the last exercise:

``````plt.hist(exercise_ages, range = (20, 70), bins = 5, edgecolor='black')

plt.xlabel("Ages")
plt.ylabel("Count")

plt.show()``````

In the code above, we used the `plt.hist()` function to create the plot, then added a title, x-label, and y-label before showing the graph with `plt.show()`.

### Instructions

1.

At the top of script.py, we’ve imported `codecademylib`, which is a package that Codecademy uses to plot your histogram in the panel to the right. Don’t worry about this library. Any Python development environment that you may use will take care of this for you.

From matplotlib, import `pyplot` as `plt`.

2.

Use the `plt.hist()` function to create a plot for each six-hour period in a day. Use the following range and number of bins.

• Range: 0 to 24
• Bins: 4
3.

Use `plt.show()` to show the figure.

Feel free to add a title, x-label, and y-label if you want. You can copy the code from the hint as an example.