We use the () method to mark out and label the elements of the graph. We can add a legend to the plot using the matplotlib module. Generate a Plot: Use the show() method to visualize the plot on the user’s windows.Add Legend: By using the legend() method we can add a legend to a plot.Plot scatter graph: By using the scatter() method we can draw a plot.Define X and Y: Define the data coordinates values used for the x-axis and y-axis.Defining Libraries: Import the important libraries which are required for data creation and manipulation ( Numpy and Pandas) and for data visualization ( pyplot from matplotlib).The following steps are used to plot scatter graph and add a legend to it are outlined below: It represent the reletionship between two variables in a data-set. Scatter Plot is a graph in which the values of two variables are plotted along two axes. Legendis an area that outlines the elements of the plot. Now before starting the topic firstly, we have to understand what does “legend” means and how “scatter plot created”.
#SEABORN SCATTER PLOT LEGEND NUMBER HOW TO#
In this section, we learn about how to add a legend to the Scatter Plot in matplotlib in Python. Matplotlib scatter plot legend by color.Python seaborn scatter plot legend outside.Matplotlib scatter plot legend facecolor.Matplotlib scatter plot legend position.Although written for the scatterplot, this tutorial is applicable for the different Seaborn charts for raw data, bi-variate / categorical analysis: catplot, plotbox, barplot, paiplots etc’.We’ll cover that in subsequent tutorials. There is more to customize for Seaborn legends (handlers, labels etc’).We can also modify the background color of our legend, as shown below: scatter.legend(shadow = True, facecolor = 'grey') Bringing all of it together scatter.legend(fontsize = 15, \ scatter.legend(title="Delivery Type") Set the Legend background color Next we would like to provide a meaningful title to our legend. Scatter.legend(fontsize = 15) Modify the Seaborn legend title We can fix it with ease: #tweak the font heights in px The second issue we recognize in our chart is that by default our legend fonts are too small for the figsize we set.
Note: We can also use the loc parameter to specify a location for the legend size on the the chart. You might want to tweak it as per your needs.
The bbox_to_anchor parameter allows us to pass an (x,y) tuple with the required offset. What if we want to display it outside the figure, so it doesn’t overlap with any observation we plot? Probably the most visible issue we have with our chart is the location of the legend. Seaborn will display the following warning: No handles with labels found to put in legend. Scatter = sns.scatterplot(x = x, y =y, data=deliveries, hue='type', legend= False)
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