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I have created a scatter plot using seaborn:
import seaborn as sns sns.set(style="ticks", color_codes=True) g=sns.scatterplot(x="length", y="coverage", data=df, hue = 'Products', edgecolors=None, alpha = 0.7) g.set(yscale="log") plt.xlabel("Length(bp)") plt.ylabel("Coverage") plt.legend(loc = 'lower right') plt.savefig('ATN_plot.png',dpi = 600) The original data(Partial):
contig length coverage pathway Products 53 1230 2423 stigmatellin Yes 58 1195 885 curacin Yes 65 1161 598 jamaicamide Yes 68 1159 8001 jamaicamide Yes 79 1113 1423 curacin Yes 105 1042 1106 stigmatellin Yes 727 666 223 HSAF (heat stable antifungal factor) Yes 787 655 37 curacin Yes 791 654 13 stigmatellin Yes 798 652 49 stigmatellin Yes 844 642 5774 jamaicamide Yes 89 1090 13 No No 90 1089 10 No No 91 1086 26 No No 92 1080 16 No No 93 1079 10 No No 94 1079 13 No No And the final plot looks like this:
I don't like the white edge of the spots. The left bottom part of the image where most spots are accumulated looks too white. I already included edgecolors=None in my code but it seems not working. Does anyone know how to remove the edge color or change it to others?
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Changing Marker Color on a Scatter Plot Behind the scenes, Seaborn scatter plots use the Matplotlib color styles. Here are the color codes for the basic colors you can use for your scatter plot markers. Pass the value in the argument column to the color parameter to change your marker colors.
To set the size of markers, we can use the s parameter. This parameter can be used since seaborn is built on the matplotlib module. We can specify this argument in the scatterplot() function and set it to some value. Alternatively, we can control the size of the points based on some variables.
In Seaborn's scatterplot() function, we can change the shape of markers by a variable using style argument. In this example, we have changed the marker's shape based on the value of the variable, “sex” in the dataframe. Notice that data points corresponding to males are different from females.
Show activity on this post. Those are linked to the plot and line that appear in the figure. If we use scatter_kws={"s": 780} meaning the greater value given, the greater plot/node. If we use line_kws={"lw":5} meaning the greater the value given, the thicker the line.
Replace edgecolors=None with linewidth=0
Something like:
g=sns.scatterplot(x="length", y="coverage", data=df, hue = 'Products', linewidth=0, alpha = 0.7) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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