Join us and get access to thousands of tutorials and a community of expert Pythonistas.

Unlock This Lesson

This lesson is for members only. Join us and get access to thousands of tutorials and a community of expert Pythonistas.

Unlock This Lesson

Reviewing the Key Input Parameters

For more information about concepts covered in this lesson, you can check out:

00:00 Reviewing the key input parameters. In the previous sections of this course, you’ve learned about the main input parameters to create scatter plots. Here’s a brief summary of key points to remember about the main input parameters.

00:16 x and y: These parameters represent the two main variables and could be any array-like data type, such as lists or NumPy arrays.

00:25 These are required parameters. s: This parameter defines the size of the marker. It can be a float if all the markers have the same size or an array-like data structure if the markers have different sizes.

00:42 c: This parameter represents the color of the markers. It can take an array of colors either in RGB or RGBA format, a sequence of values that will be mapped onto a colormap using the parameter cmap, or it can take a color format string.

01:00 marker: This parameter is used to customize the shape of the marker. It typically takes a text value, as you saw earlier in the course, but these are shorthand for one of Matplotlib’s marker class instances, which is the other form it can accept.

01:16 cmap: If a sequence of values is used for the parameter c, then this parameter can be used to select the mapping between values and colors, typically by using one of the standard colormaps or a custom colormap.

01:32 alpha: This parameter is a float that can take any value between 0 and 1 and represents the transparency of the markers, where 1 represents a completely opaque marker. While these aren’t the only input parameters available to you, these are the most important ones, and having a good knowledge of these will mean you’ll be able to get started quickly with most of your scatter plotting.

01:56 You can access the full list of input parameters from the documentation linked onscreen.

02:03 Now that you’ve covered all the elements of this course, in the next section, there’s a summary of what you’ve learned.

Become a Member to join the conversation.