Plot legend python

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, plot legend python. 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.

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 the location of the legend. Its default value is 1. Below are some examples that can see the Matplotlib interactive mode setup using Matplotlib. In this example, both the sine and cosine functions are plotted against the range [0, 10] on the x-axis.

Plot legend python

Go to the end to download the full example code. This legend guide extends the legend docstring - please read it before proceeding with this guide. A legend is made up of one or more legend entries. An entry is made up of exactly one key and one label. Calling legend with no arguments automatically fetches the legend handles and their associated labels. This functionality is equivalent to:. Proxy artists for further details. For full control of what is being added to the legend, it is common to pass the appropriate handles directly to legend :. In the rare case where the labels cannot directly be set on the handles, they can also be directly passed to legend :. Not all handles can be turned into legend entries automatically, so it is often necessary to create an artist which can. Legend handles don't have to exist on the Figure or Axes in order to be used. Suppose we wanted to create a legend which has an entry for some data which is represented by a red color:.

Whilst the power here is clear, remember that there are already many handlers implemented and plot legend python you want to achieve may already be easily possible with existing classes. The attribute Loc in legend is used to specify the location of the legend.

The elements to be added to the legend are automatically determined, when you do not pass in any extra arguments. In this case, the labels are taken from the artist. A string starting with an underscore is the default label for all artists, so calling Axes. For full control of which artists have a legend entry, it is possible to pass an iterable of legend artists followed by an iterable of legend labels respectively:. This call signature is discouraged, because the relation between plot elements and labels is only implicit by their order and can easily be mixed up. To make a legend for all artists on an Axes, call this function with an iterable of strings, one for each legend item.

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. If this is not what is desired, we can fine-tune which elements and labels appear in the legend by using the objects returned by plot commands.

Plot legend python

Go to the end to download the full example code. This legend guide extends the legend docstring - please read it before proceeding with this guide. A legend is made up of one or more legend entries. An entry is made up of exactly one key and one label. Calling legend with no arguments automatically fetches the legend handles and their associated labels. This functionality is equivalent to:. Proxy artists for further details.

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Working with Legends Matplotlib. BoundaryNorm matplotlib. Discrete distribution as horizontal bar chart Discrete distribution as horizontal bar chart. MarkerStyle matplotlib. Syntax : matplotlib. If False , legend marker is placed to the right of the legend label. The strings 'upper center' , 'lower center' , 'center left' , 'center right' place the legend at the center of the corresponding edge of the axes. This has been done so that it is possible to call legend repeatedly to update the legend to the latest handles on the Axes. Similar Reads. Previous How to set the spacing between subplots in Matplotlib in Python? LinearSegmentedColormap matplotlib. Notice how now both Line2D instances get 4 markers.

The elements to be added to the legend are automatically determined, when you do not pass in any extra arguments.

The vertical offset relative to the font size for the markers created for a scatter plot legend entry. A custom handler can be implemented to turn any handle into a legend key handles don't necessarily need to be matplotlib artists. Using Matplotlib Axes and subplots Legend guide. Contourf Hatching Contourf Hatching. The legend's background patch edge color. Go to the end to download the full example code. We can then pass the mapping of instance to Handler as a keyword to legend. In [5]:. We'd like a legend that specifies the scale of the sizes of the points, and we'll accomplish this by plotting some labeled data with no entries:. Last Updated : 10 Jan, This functionality is equivalent to:.