Python Data Visualization Transcripts
Lecture: Quick reference
0:00 Now that we've done a little bit of matplot lib coding. I'm gonna take a step back and walk through a couple of quick reference items.
0:07 That will be useful for you for the rest of this training as well as your continued development with matplot lib.
0:14 First thing I wanted to lay out are the common imports that you'll use when working with matplot lib, you'll import pyplot as 'plt'.
0:22 And then it's also convention that matplot lib is imported as 'mpl'. When working in a jupyter notebook,
0:29 you can display the matplot lib images in line using the magic command, matplot lib inline, as well as using the notebook command to offer a
0:39 more interactive approach. When setting up figures and axes. Use 'plt.subplots' to configure how many images you want to combine into a single
0:49 figure. And then on each of these axes you can plot your display, such as a histogram, box plot or some of the other visualizations that we'll talk
0:58 about. And then finally, when you want to update the display, you can use, set X label, Y label, or title as we've shown,
1:06 as well as some of the other options that we've reviewed and are available through the matplot lib documentation.