To increase the size of the points in the legend, you can use the markerscale argument within the matplotlib legend() function: import matplotlib. You can increase the density of hatching, by repeating symbols (in the example below, the '' is repeated in the R/H pane note that to obtain NW->SE diagonal lines the symbol must be escaped so needs twice as many characters to really double it - '\\\\' is density 2 while '' is density 4).
However, the size of the points in the legend have remained the same. You just need to set the linewidth to control the marker border thickness. Notice that the size of the points has increased. scatterplot(data=df, x=' day', y=' sales', hue=' store', s= 200) #create scatterplot with increased marker size We can use the s argument to increase the size of the points in the plot: import seaborn as sns lgnd.legendHandles 0.sizes 200 lgnd.legendHandles 1.sizes 200 this is affecting the size of reddot only. For that, I have tried adding this to the above code. scatterplot(data=df, x=' day', y=' sales', hue=' store') Now I want to change the size of the markers in the legend so that all the markers are of equal size.
#create scatterplot with default marker size We can use the scatterplot() function in seaborn to create a scatterplot that displays the sales made each day at each store import seaborn as sns Suppose we have the following pandas DataFrame that contains information about the sales made during five consecutive days at two different retail stores: import pandas as pdĭf = pd. Example: Change Marker Size in Seaborn Scatterplot
#Matplotlib scatter marker size constant how to
The following example shows how to use this syntax in practice. s float or array-like, shape (n, ), optional. The greater the value you provide for the s argument, the larger the points in the plot will be. Parameters: x, y float or array-like, shape (n, ) The data positions. You can use the s argument within the scatterplot() function to adjust the marker size in a seaborn scatterplot: import seaborn as sns
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