Legend placement matplotlib

A legend is an area describing the elements of the graph. In this article, we will learn about the Matplotlib Legends. Syntax : matplotlib. The attribute Loc in legend is used to specify legend placement matplotlib location of the legend.

Matplotlib is the package used for data visualization and is one of the most popular packages in python. Each pyplot function takes is used to make some changes to a figure e. A legend is used to describe elements for a particular area of a graph. Python has a function called legend which is used to place a legend on the axis. The legend function has an attribute called loc which is used to denote the location of the legend. The default value of attribute loc is upper left. Other string, such as upper right , lower left , lower right can also be used.

Legend placement matplotlib

You can modify different properties of a plot — color, size, label, title and so on — when working with Matplotlib. In this article, you'll learn what a legend is in Matplotlib, and how to use some of its parameters to make your plots more relatable. In the graph above, we described the plot using a legend. A description of "Data" was assigned to the legend, and was placed in the upper right corner of the graph using the upper right value of the loc parameter. With the legend function, you can assign different descriptions to each line of a graph. In the graph above, we've used the legend function to describe each line in the plot. This makes it easier for anyone viewing the graph to know that the blue line denotes age while the orange line denotes number in the graph. You can change the position of the legend using the following values of the loc parameter:. You can change the font size of a Matplotlib legend by specifying a font size value for the fontsize parameter. You'd also notice the legend was placed at the upper left corner of the graph using the loc parameter. Another way of changing the font size of a legend is by using the legend function's prop parameter. In this article, we talked about the legend function in Matplotlib. It can be used to describe the elements that maker up a graph. We first saw what a legend is in Matplotlib, and some examples to show its basic usage and parameters. We then saw how to use the fontsize and prop parameters to change the font size of a Matplotlib legend.

Skip to content. A string starting with an underscore is the default label for all artists, so calling Axes.

It is unlikely that you would ever create a Legend instance manually. Most users would normally create a legend via the legend function. For more details on legends there is also a legend guide. The Legend class is a container of legend handles and legend texts. The legend handler map specifies how to create legend handles from artists lines, patches, etc. While not all artist types are covered by the default legend handlers, custom legend handlers can be defined to support arbitrary objects.

When you're diving into the world of data visualization, one of the key components you'll encounter is the legend. In the simplest terms, a legend is a guide that helps anyone looking at your chart to understand what each graphical element represents. Think of it as a map legend that tells you what different symbols and colors mean, but for your chart. In Matplotlib, which is a plotting library for Python, legends are incredibly useful for distinguishing between different datasets or categories within your plot. Adding a legend can turn a confusing jumble of lines or bars into a clear and interpretable visualization. So, let's learn how to add and customize legends in Matplotlib. To begin with, let's see how you can add a basic legend to a plot. When you create a plot with multiple lines or markers, you can label each one using the label parameter within plotting functions like plot , scatter , bar , etc. After labeling, you can call the legend function to display the legend on the plot.

Legend placement matplotlib

If you find this content useful, please consider supporting the work by buying the book! Plot legends give meaning to a visualization, assigning meaning to the various plot elements. We previously saw how to create a simple legend; here we'll take a look at customizing the placement and aesthetics of the legend in Matplotlib. The simplest legend can be created with the plt. But there are many ways we might want to customize such a legend. For example, we can specify the location and turn off the frame:. We can use a rounded box fancybox or add a shadow, change the transparency alpha value of the frame, or change the padding around the text:. As we have already seen, the legend includes all labeled elements by default.

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Contribute to the GeeksforGeeks community and help create better learning resources for all. FuncNorm matplotlib. BoxStyle matplotlib. Polar legend. By utilizing these techniques, we can customize our legends to be both informative and aesthetically pleasing. Gitter Discourse GitHub Twitter. Wedge matplotlib. Please Login to comment The legend's title. NoNorm matplotlib.

To change the position of a legend in Matplotlib, you can use the plt. For example, you can use the following syntax to place the legend in the upper left corner of the plot:.

A description of "Data" was assigned to the legend, and was placed in the upper right corner of the graph using the upper right value of the loc parameter. Work Experiences. LinearSegmentedColormap matplotlib. This option can be quite slow for plots with large amounts of data; your plotting speed may benefit from providing a specific location. Pierian Training. In order to effectively analyze time series data, it is important to visualize it in a way that is easy to understand. Labelcolor can be set globally using rcParams["legend. For back-compatibility, 'center right' but no other location can also be spelled 'right' , and each "string" location can also be given as a numeric value:. Note Go to the end to download the full example code. Search Submit your search query. Engineering Exam Experiences. HandlerTuple which simply plots the handles on top of one another for each item in the given tuple. Without setting location of legend best. AxLine matplotlib. Section Navigation matplotlib matplotlib.