In this article, I have explained how to add a legend to the plot bar using legend() and using its syntax and Parameters how we can change the location of the legend in different ways and also explain how we can customize the legend using various legend parameters with multiple visualization examples. Matplotlibs plt.plot() is a general-purpose plotting. Plt.legend(loc='center left', bbox_to_anchor=(1.0, 0.5)) You can also produce the scatter plot shown above using another function within matplotlib.pyplot. Pass bbox_to_anchor into legend() function, it will create the legend outside of the plot. Now we will see the legend which, will add the outside of the plot in Pandas using legend() function. So far, we have learned, how to add a legend to the plot and how to customize the legend using plt.legend() function. This argument accepts both hex codes and normal words. # Death Rate 316.3 321.3 117.2 38.25 302.2Īdd legend at out side of the Pandas plot bar 6. You can also change the color of the data points within a matplotlib scatterplot using the color argument. Plt.title("Death Rate of Covid-19", color = 'red') Quick Examples of How to Add Plot Legends in pandas?ĭf = pd.DataFrame(, In this article, I will explain the plt.legend() function and using this syntax and parameters how we can add a legend to bar plot with several examples. This function creates a legend automatically for any labeled plot elements. matplotlib library provides a legend() function, using this we can modify, customize the legends and change the place of the legend for any type of plot. Plot legends provide clear visualization by telling the functionality of plot elements. A legend is nothing but an area of the plot. We then saw how to use the fontsize and prop parameters to change the font size of a Matplotlib () is used to change the location of the legend of the plot in Pandas. 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. However, we are doing science here, and esthetic is just a side. Here's the output: matplotlib legend size using prop parameter Summary A colormap is a key ingredient to produce both readable and visually pleasing figures. 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 can specify one color for all the circles, or you can vary the color. You'd also notice the legend was placed at the upper left corner of the graph using the loc parameter. scatter( x, y, sz, c ) specifies the circle colors. 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. Plt.show() matplotlib graph with a legend 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 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. You can modify different properties of a plot - color, size, label, title and so on - when working with Matplotlib.
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