I have 4 subplot and each subplot holds 3 graph. We then saw how to use the fontsize and prop parameters to change the font size of a Matplotlib legend.Python Dictionaries Access Items Change Items Add Items Remove Items Loop Dictionaries Copy Dictionaries Nested Dictionaries Dictionary Methods Dictionary Exercise Python If.Else Python While Loops Python For Loops Python Functions Python Lambda Python Arrays Python Classes/Objects Python Inheritance Python Iterators Python Polymorphism Python Scope Python Modules Python Dates Python Math Python JSON Python RegEx Python PIP Python Try. How to select legend in multiple subplot Follow 2 views (last 30 days) Show older comments Fahmy Shandy on Vote Edited: Fahmy Shandy on And Suppose i have 3 programs in one script. We first saw what a legend is in Matplotlib, and some examples to show its basic usage and parameters. It can be used to describe the elements that maker up a graph. In this article, we talked about the legend function in Matplotlib. Here's the output: matplotlib legend size using prop parameter Summary Here's how to use it: import matplotlib.pyplot as plt How To Change Legend Font Size in Matplotlib Using the prop ParameterĪnother way of changing the font size of a legend is by using the legend function's prop parameter. You'd also notice the legend was placed at the upper left corner of the graph using the loc parameter. We assigned a font size of 20 to the fontsize parameter to get the legend size in the image above: fontsize="20". Here's what the legend would look like: matplotlib legend size using fontsize parameter Plt.legend(, fontsize="20", loc ="upper left") Here's another code example with the fontsize parameter included: import matplotlib.pyplot as plt Plt.show() matplotlib graph with default legend font size Here's what the default legend font size looks like: import matplotlib.pyplot as plt You can change the font size of a Matplotlib legend by specifying a font size value for the fontsize parameter. How To Change Legend Font Size in Matplotlib Using the fontsize Parameter You can change the position of the legend using the following values of the loc parameter: 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. In the graph above, we've used the legend function to describe each line in the plot. Plt.show() two line graph with different legend descriptions Here's an example: import matplotlib.pyplot as plt With the legend function, you can assign different descriptions to each line of a graph. 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. In the graph above, we described the plot using a legend. Each of your p is formed as p plot(num(6:end,2:2),num(6:end,7:7), 'x', 'DisplayName' ,num2str(n)) The 2:2 and the 7:7 there result in a column vector for the x value and a column vector for the y value, so you are plotting one vector against another, which is an operation that is going to produce a single line object rather than an array of. Plt.show() matplotlib graph with a legend x linspace (0,pi) y1 cos (x) plot (x,y1) hold on y2 cos (2x) plot (x,y2) legend ( 'cos (x)', 'cos (2x)') If you add or delete a data series from the axes, the legend updates accordingly. Specify the legend labels as input arguments to the legend function. You'll then learn how to change the font size of a Matplotlib legend using:Ī legend is a Matplotlib function used to describe elements that make up a graph.Ĭonsider the graph below: import matplotlib.pyplot as plt Plot two lines and add a legend to the current axes. 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. a 2 by 1 grid of subplots for two plots one on top of each other a 1 by 2 grid. You can also delete legends by unchecking the Show legend option at the bottom of the first tab of the. You can modify different properties of a plot - color, size, label, title and so on - when working with Matplotlib. all) and press the Delete key to delete them all.
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