In this lesson, we'll review what you learned in this section.
We began this section by getting some deeper practice with Python's most popular data visualization library, Matplotlib! We got some practice with things like different kinds of plots, setting labels and axes, modifying line ticks, adding a legend, and even using color in our visualizations. We also learned about how to place multiple plots together as a subplot, and how we can write clean, efficient code when building these by making use of the enumerate
keyword for our loops.
Next, we learned about the best and worst practices for data visualization. We learned about how to pack multiple kinds of information into a single plot, how to make effective use of color, and how to use Preattentive Attributes to make important parts of our visualization stand out. We also learned about common mistakes and errors, so that we can avoid them in the future.
Finally, we got some practice with a second visualization library, Seaborn. We learned about the relationship between Seaborn and Matplotlib, and saw some examples of when we may want to use Seaborn instead of Matplotlib.
In this section, you learned how to create meaningful visualizations.