Python Data Visualization Transcripts
0:00 During the exercises, we went through a lot of different examples of how to configure and customize your matplot lib plots.
0:07 So I want to summarize the work we did to create the plot shown here on the screen so that you can refer back to it when you're done with the course
0:15 The first thing we did is configured the style and created our figure. In this case we use the 'ggplot' style and then configured a figure that
0:25 has two axes, axes1 and axis 2 then we plot our scatter plot and line on the first axes. We also label the X and Y axis.
0:37 Set the limits set a formatter on the Y axis so that we have currency We also added a horizontal line and annotated that line on the second axis.
0:48 We plot the histogram and in a similar way, set a formatter, add a vertical line and annotate that vertical line.
0:56 And then when we're all done we can save the image. In this example we added an additional title and then save the image as a transparent
1:05 svg. There are a lot of configuration options in matplot lib. The API is very large.
1:13 So I wanted to also recommend the official cheat sheet that's available with matplot lib It has a really nice summary of all of the functions.
1:23 We've only scratched the surface of all the options available to you. So I encourage you to look at this cheat sheet,
1:29 there is also one available for beginners and they're both available at the matplotlib/cheatsheets github location.