28. Improving Plots and Sharing Findings

Question:

Adding labels and titles

In matplotlib, you can add axis labels using plt.xlabel("Label for x axis") and plt.ylabel("Label for y axis"). For histograms, you usually only need an x-axis label, but for other plot types a y-axis label may also be needed. You can also add a title using plt.title("Title of plot").

Making plots look nicer with seaborn

You can automatically make matplotlib plots look nicer using the seaborn library. This library is not automatically included with Anaconda, but Anaconda includes something called a package manager to make it easier to add new libraries. The package manager is called conda, and to use it, you should open the Command Prompt (on a PC) or terminal (on Mac or Linux), and type the command conda install seaborn.

If you are using a different Python installation than Anaconda, you may have a different package manager. The most common ones are pip and easy_install, and you can use them with the commands pip install seaborn or easy_install seaborn respectively.

Once you have installed seaborn, you can import it anywhere in your code using the line import seaborn as sns. Then any plot you make afterwards will automatically look better. Give it a try!

If you're wondering why the abbreviation for seaborn is sns, it's because seaborn was named after the character Samuel Norman Seaborn from the show The West Wing, and sns are his initials.

The seaborn package also includes some extra functions you can use to make complex plots that would be difficult in matplotlib. We won't be covering those in this course, but if you'd like to see what functions seaborn has available, you can look through the documentation.

Adding extra arguments to your plot

You'll also frequently want to add some arguments to your plot to tune how it looks. You can see what arguments are available on the documentation page for the hist function. One common argument to pass is the bins argument, which sets the number of bins used by your histogram. For example, plt.hist(data, bins=20) would make sure your histogram has 20 bins.

Improving one of your plots

Use these techniques to improve at least one of the plots you made earlier.

Sharing your findings

Finally, decide which of the discoveries you made this lesson you would most want to communicate to someone else, and write a forum post sharing your findings.